Why Anthropic Thinks AI Should Have Its Own Computer — Felix Rieseberg of Claude Cowork & Claude Code Desktop

17 Mar 2026 · 1 h 27 min · 41 chapters

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In short

Latent Space Podcast Episode Notes

Podcast Information

  • Title: Latent Space: The AI Engineer Podcast
  • Description: A podcast dedicated to AI Engineers, discussing the latest news, research papers, and interviews with leading figures in the AI space, covering topics like Foundation Models, Code Generation, and more.

Episode Details

  • Episode Title: Why Anthropic Thinks AI Should Have Its Own Computer
  • Guest: Felix Rieseberg, Claude Cowork & Claude Code Desktop
  • Release Year: 2024

Episode Summary In this episode, Felix Rieseberg discusses the development of Claude Cowork, a user-friendly version of Claude Code that streamlines AI-assisted knowledge work for both technical and non-technical users. The conversation touches on the evolution of AI tools, the significance of local computing, and the impact of AI on the labor market, especially for junior roles.

Key Themes and Takeaways

  1. Introduction to Claude Cowork
  2. User-Friendly Design: Claude Cowork was designed to be more accessible for non-technical users, allowing them to automate various knowledge work tasks without needing terminal expertise.
  3. Rapid Development: The tool was built in just 10 days by leveraging existing internal components and prototypes.
  1. The Shift in AI Product Focus
  2. From Chat to Execution: The focus has shifted from enhancing chat capabilities to achieving trusted task execution.
  3. Prototype-First Culture: Anthropic emphasizes rapid prototyping and iteration over lengthy documentation processes.
  1. Local vs. Cloud Computing
  2. Value of Local Computing: Felix argues that local machines provide critical advantages for AI productivity, as they allow for direct access to tools and resources without the complications of cloud-based permissions.
  3. VM Safety Features: The use of a virtual machine (VM) in Claude Cowork acts as both a safety boundary and a capability unlock, allowing for autonomous task execution without constant human approval.
  1. Skills and Task Automation
  2. Skills as Building Blocks: Users can create skills that automate recurring tasks, promoting hands-off operation of the AI.
  3. Integration with Existing Workflows: Cowork aims to enhance existing applications (like Chrome and Office) rather than replace them, integrating smoothly with established processes.
  1. Impact on Employment
  2. Concerns for Junior Roles: The automation potential raises concerns about impacts on entry-level jobs, as many tasks traditionally assigned to junior employees may be automated.
  3. Need for Simulated Learning: Suggestions for creating simulated jobs to replace the on-the-job learning typically experienced by juniors are presented, potentially accelerating their development.
  1. Future Directions
  2. Expanding AI Capabilities: The future of Claude Cowork includes continuous enhancements to its capabilities, allowing for more independent task execution and improved integration with user environments.
  3. Multiplayer Functionality: The prospect of enabling multiple AI agents to collaborate and communicate on tasks within a shared workspace is discussed, raising questions about skill sharing and task handoffs.
  1. Anthropic's Labs
  2. Felix describes the internal labs culture at Anthropic, where wild and innovative ideas are explored, some of which may not yet be ready for public release.

Closing Remarks Felix emphasizes that the journey toward creating effective, user-friendly AI products is ongoing and that future developments will likely focus on enhancing the integration of AI into everyday workflows.

Additional Resources

  • Felix Rieseberg:
  • [Twitter](https://x.com/felixrieseberg)
  • [LinkedIn](https://www.linkedin.com/in/felixrieseberg)
  • [Website](https://felixrieseberg.com/)
  • Anthropic:
  • [Website](http://anthropic.com)

Timestamps

  • 00:00 - Introduction to the podcast and guest
  • 02:47 - Overview of Claude Cowork
  • 04:18 - User-friendly vs powerful tools
  • 07:09 - Building Cowork in 10 days
  • 08:00 - Prototype-first product development
  • 09:20 - Importance of local computing
  • 12:13 - Skills, primitives, and platform leverage
  • 20:16 - Evals, planning, and knowledge-work optimization
  • 52:00 - Future implications on junior jobs

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These notes summarize the key discussions and insights from the episode, providing a detailed overview of the topics explored and their implications for AI in the workplace.

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

Tap a time to open that second in VO

Exploring Cowork and Its Features

0:46 to 2:20

Discussion about the functionalities and experiences with Cloud Cowork.

“I've been using it a lot, even for managing latent space.”

Understanding Cloud Cowork's Design

2:21 to 3:45

Felix explains the user-friendly design of Cloud Cowork and its capabilities.

“Like there was a big obsidian moment that a lot of people liked.”

Transitioning to Cloud Cowork

3:46 to 5:00

Discussion on the transition from Cloud Code to Cloud Cowork and its execution process.

“Like, I think a similar thing happened to me about ten years ago, like maybe 12 years ago when I was at Microsoft, and we started working on Electron and browser based technologies and cross platform stuff.”

Prototyping and Decision-Making at Anthropic

5:01 to 6:45

Insights into the prototyping culture at Anthropic and decision-making processes.

“Cloud Co-Work because I mean you built it in only 10 days I'm sure there was some discussion before on what does easier to use mean?”

Value of Platforms in AI Development

6:46 to 8:38

Discussion on the importance of existing platforms and the balance between customization and usability.

“And then maybe what can you build to like address that need?”

Building and Testing Software Quickly

8:39 to 10:17

The approach of rapid prototyping and testing with user feedback in software development.

“Because like things change and it's easier to rewrite than reuse.”

Technical Architecture of Cloud Cowork

10:18 to 12:34

An overview of the technical architecture and features of Cloud Cowork.

“But the important stuff that I did was not write the electron bindings.”

Integrating Cloud and Chrome for Efficiency

12:35 to 14:03

Discussion on integrating Cloud and Chrome for improved user experience in Cloud Cowork.

“cloud aggressively and just be like, this is a person.”

Integrating Cloud and Chrome for Enhanced Productivity

14:03 to 15:10

Discover how tight integration with Cloud and Chrome simplifies coding tasks.

“You're noticing that a lot of people, especially as the models get better, a lot of people throw up their hands when it comes to MCP connectors in this era.”

Using Cloud to Streamline Bug Fixing

15:10 to 17:49

Learn how to utilize Cloud tools for efficient bug tracking and fixing.

“I found myself like on our internal tool that we have to collect crashes and just like debugging information.”
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The Value of Local Machines vs. Cloud Solutions

17:49 to 19:19

Explore the ongoing debate on the importance of local machines in a cloud-first world.

“for the amount of tools that I use, just don't have the patience to give another tool like permissions to every single thing and keep those permissions up to date.”

Permissions and Cloud Integration Challenges

19:19 to 20:50

Understand the complexities of granting permissions for cloud tools.

“is to like put it where you're working Anything else with our mental model?”

Evaluating Cloud Tools for Different Use Cases

20:50 to 22:36

Learn how to assess Cloud tools based on specific tasks and user needs.

“I think what I was referring to was also, it just, it qualitatively felt different when I, probably it's just out-prompting and I'm reading too much into it.”

Scaffolding vs. Capabilities in AI Tools

22:36 to 24:40

Dive into the balance between user scaffolding and AI capabilities.

“Just on the topic of evals, when you say eval, I think people are very vague about what it means.”

The Evolution of Skills in AI Applications

24:40 to 27:06

Examine how automating repetitive tasks with AI skills transforms workflows.

“Or is it to just give it as many capabilities as possible, try to make those safe so that the worst case scenario is not as bad as it might be otherwise, and then just simply wait a second for the next model drop?”

Personalizing AI Skills for Individual Needs

27:06 to 28:00

Discover how easy it is to create personalized AI skills for specific tasks.

“We literally at first, I didn't trust Cloud Core.”

Creating and Automating Skills

28:00 to 29:10

Learn about the process of creating reusable skills for automation.

“But then I asked it to make its own skill so that something that's repetitive and one-off and human-guided becomes more automated and I can use the skills independently and reuse them.”

Expanding Automation with Cloud Cowork

29:10 to 30:25

Discover how to progressively automate tasks and build a personal automation empire.

“Like actually looking at the docs to like programmatically upload to YouTube and then putting that in a skill.”

Managing Calendar Conflicts

30:25 to 31:30

Explore strategies for managing calendar conflicts using automation tools.

“My favorite skill has been every single morning, Koberk starts looking at my calendar and make sure that there's a conflict because people tend to schedule a lot of meetings, sometimes last minute or sometimes miss it.”

Organizing Digital Spaces

31:30 to 32:50

Hear about the importance and ease of organizing digital files with AI assistance.

“It was like, you have so many term sheets and there's like eight copies of your rental lease for your office.”

Integrating Tools for Enhanced Productivity

32:50 to 34:10

Learn how tool integration can enhance productivity and workflow efficiency.

“I have other things like sign up for PG &E.”

Exploring Browser Integration

34:10 to 35:35

Discover how browser capabilities enhance the functionality of automation tools.

“This thing is like a built-in browser, which is a thing a lot of products have.”

User-Centric Workflow Development

35:35 to 36:50

Discuss the importance of user-centric design in developing new workflows.

“And I've used all the other agentic browsers, and Enthropic didn't have to build an agentic browser because you just had cloud cowork, and that's enough.”

Skills Portability and Personalization

36:50 to 38:10

Learn about the challenges of skill portability in automation tools.

“default and which search engine is default within the browser.”

Combining Personal and Universal Skills

38:10 to 39:45

Explore the balance between personal preferences and universal skills in automation.

“I'm really leaning into the idea of like, it's all just files and folders.”

Navigating Productivity with AI

42:00 to 43:50

Explore how AI can function as a coworker and enhance productivity.

“like that almost feels like my personal productivity thing will be my skills.”

The Future of Industries: Automation Impact

43:50 to 46:00

Discuss the potential industries that may be affected by AI and automation.

“Potentially spicy question for both of you.”

Education and Entry-Level Jobs in an AI World

46:00 to 48:20

Analyzing how AI could change the landscape for entry-level job seekers and education.

“that we personally find annoying, that we maybe think it's not the best use of our time.”

Preparing for an AI-Driven Future

48:20 to 52:00

Discussing the importance of adapting to AI advancements in various fields.

“all of this happened, I've always had a lot of respect for the University of Waterloo.”

AI in Finance: Opportunities and Challenges

52:00 to 56:00

Exploring how AI tools can be utilized for financial tasks and their implications.

“whether or not it happens in four or five years.”

One Year Progress and Automation Insights

56:00 to 1:00:48

Discussion on the advancements in automation tools over the past year and personal experiences with them.

“Yeah, I remember it was barely usable, but isn't it wild how much better things have gone over like one year?”

Exploring Cloud's Relationship with User Computers

1:00:48 to 1:07:20

An exploration of the relationship between AI tools like Cloud and user computers, including challenges and trade-offs.

“machine and the machine guy because he has the Windows 95 project.”

Navigating Safety and Security in AI Usage

1:07:20 to 1:10:00

Insights into safety and security considerations for AI and automation in day-to-day workflows.

“If you want this to be useful, then you have to like approve every single step of the way.”

Exploring Engineer Risk Tolerance

1:10:00 to 1:10:57

Discussion on the risk tolerance of engineers and model safety.

“You might not always come up with the right answer.”

Future of Clockwork and User Independence

1:10:57 to 1:12:46

Insights on the future development of Clockwork and user autonomy.

“I'm going to continue probably to double down on your computer and like making you effective on your computer and making cloud effective on your computer.”

Importance of General Purpose Tools

1:12:46 to 1:14:41

The significance of building general-purpose tools over hyper-specialized ones.

“But like maybe to me on the other side as the person building this product still feels kind of heavy handed.”

The Role of Chromium in App Development

1:14:41 to 1:17:08

Understanding why Chromium is vital for modern applications and its advantages.

“And Electron itself is, like, very abstractable and generalizable, right?”

The Evolution of Electron and Future Predictions

1:17:08 to 1:19:02

Discussion on the future of Electron and its potential obsolescence due to advancements in app development.

“So if you're say a Slack and you have a critical rendering bug in WK WebView and some of the other WebView options, your only recourse is to tell your customer, oh, sorry, you're too poor.”

Multiplayer Capabilities in Co-Working Tools

1:19:02 to 1:24:00

Exploration of multiplayer modes for collaborative AI tools and their implications.

“Our next interview is with Mark Andreessen, who had the phrase like, desktop OSs are just poorly, poor implications of the actual OS, which is Chrome, which like actually works everywhere.”

Exploring Collaboration with Claude

1:24:00 to 1:25:16

Learn how Claude facilitates skill sharing and collaboration among coworkers.

“There's another thing you could do, right?”

Inside Anthropic's Labs Team

1:25:16 to 1:26:29

Discover the innovative projects being developed in Anthropic's Labs team.

“So you're probably working on the same thing.”
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Transcript

Automatic transcript. May contain errors.

0:06Felix Rieseberg:Hey everyone, welcome to the Layton Space podcast. Our first one in the new studio at Kernel. This is Alessio, founder of Kernel Labs, and I'm joined by Swix, editor of Layton Space. Yeah, so nice to be here. Thanks to TJ, Alessio, Alan, helping to set everything up. It looks beautiful. We even have the logo outside. Yeah, it's like really nice. When you walk in here as a guest, you're like, oh, this is a serious production. You like feel it immediately. Yeah. Felix, you've been, you're currently product manager of Cowork or? I'm really. Lead, yeah. The identities are kind of vague. Member technical staff.

0:41I know. Member technical staff is like the official title we'll carry around forever. Yeah. I basically kind of wanted, like, we've been kind of obsessed. I've been using it a lot, even for managing latent space. Like, Cowork helps me upload videos and like title things and like edits and everything. It's like really amazing. Cool. He's had multiple times co-workers, a GI in the group track. Yeah, yeah. So we have a second channel for the InSpace TV.

1:09And basically, this is our Discord meetup. And we have like cloud co-workers, it might be a GI. I don't know if we have uploaded it yet, but one of the sessions was like a cloud co-work thing. I would love to see it. Like, I'm so curious. Like one of the most fun parts of my job is that I constantly see the weird things people use co-work for. because it's obviously like very hard for us to actually design for specific use cases. We do. But like every single person who's like most amazed is usually amazed about a thing that I didn't even expect Cowork would be good at. We have a new designer and it's one of the first small tasks.

1:42I was like, hey, we need like a new emoji for Cowork for our internal stack. It's like a pretty small thing. I said, can you please do it? And he drew an SVG and just gave it to Cowork. I was like, can you animate this emoji? And now it has like this beautiful loopy animation. and I mean I think obviously this goes down to like it turns out you can do more things with code than you expected but it's like that kind of stuff that is really fun to me so long story short I would love to see like the kind of things you're doing I'll pull it up I'll put it up yeah yeah but before we get into it I think always want to start with like a top level what is Cloud Cowork for people who haven't heard of it haven't tried it out okay real quick Cloud Cowork is a user-friendly version of Cloud Code.

2:23So the way it basically works is we have Cloud Code and for us, fairly impressive agent harness that over December, we noticed more and more people are using either, even though they're not technical, they're not at home in the terminal, or they are at home in the terminal, but they started using Cloud Code for non-coding workloads, right, like managing expenses or like filling out receipts or organizing a knowledge base. Like there was a big obsidian moment that a lot of people liked. And we wanted to capitalize on that, but also bring this capability to people who are not terminal native and who might not know how to brew install something.

2:59So Cowork is cloud code running in a virtual machine with a little bit of padding, a little bit more guardrails, making it a little safer, a little bit more convenient for people who don't want to first open up the terminal and then go to work. It's interesting that it's kind of pitched that way as a more user-friendly thing, because I always feel like, to me, I treat it as like, well, I'm familiar with Cloud Code. Like we did a Cloud Code episode a year ago, but this one is like even more power user tools because it kind of integrates much better with like Cloud and Chrome and all the other tooling.

3:33But maybe that's like a perception thing, right? No, honestly, I don't think you're wrong. This is like a thing I've been thinking a lot about for like the last two weeks. So when they say user friendly, it's like, oh, it's the dumbed down version. But no, actually, this is the superset. Yeah. Like, I think a similar thing happened to me about ten years ago, like maybe 12 years ago when I was at Microsoft, and we started working on Electron and browser based technologies and cross platform stuff. And one of the first use cases was Visual Studio Code, which used to be a website. And the initial narrative was a Visual Studio Code is like a more user friendly version of Visual Studio.

4:09But in a similar vein, I think there were some voices saying, oh, this is not for serious developers. Like we're not going to use this, right? For like anything. And I think in the end what happened is people have different stories about why Visual Studio code became such a big thing. But my personal belief is that the hackability and the extendability has played a pretty big role, right? You can hook in Visual Studio code to like almost any workload. It's so easy to hack on, so easy to build extensions for it. and I think Co-Work might be hitting a similar thing where it's very easy to extend and it's very easy to bring into your workflows so the convenience I think is a bit of a it's obviously the thing we strive for as developers but I think the way people find value in it then is by probably mapping it onto whatever they actually have to do in their job

4:54Felix Rieseberg:so end of last year you see the spike of like non-technical usage in Cloud Code what's the design process to say we should make Cloud Co-Work because I mean you built it in only 10 days I'm sure there was some discussion before on what does easier to use mean? You know, like making like a desktop GUI is obviously one way to do it, but like there's a lot of nuance in the product. Like maybe talk people through what was like the trigger of like, we should build a separate thing. We should not build like a different plot code thing. And then maybe some of the more interesting design decisions that maybe you didn't take.

5:26Yeah, I think at Anthropic, we've been thinking about ways to move people who are comfortable with using cloud to answer questions and bring more of the power of like this thing to now like execute tasks for you, right? Can like solve problems for you, can like build things for you. How do we bring that capability to people who are currently mostly comfortable with like a question answer paradigm within the chat? And we've had a lot of prototypes around that. This going back as far as like easily a year and a half, like we had a lot of people working on that. And internally, Anthropic is a very prototype demo first culture.

6:01We have a lot of like internal prototypes that don't reach the public. And what cowork actually became is like we sort of picked the right pieces out of the many prototypes that we had, right? And that's maybe also like, I think an important qualifier whenever people mention this like 10-day number. I do think it's important to me to mention that we didn't start with scratch. There was like a lot of stuff already happening, right? Like, and I think it's important for people to remember that when you build a website, you use React, you use like a bunch of other things. And this is like a similar scenario with like a lot of pieces we already had.

6:31in terms of decision path I think we live in like an interesting new world where execution is actually quite cheap so maybe what you would do that's so crazy to hear and that's wild right? You should be ideas are cheap execution is the hard part I know but like we used to live in this world maybe where you would take a product manager and the product manager would go to a number of potential customers and in this like very low bandwidth way would try to try to like tease out what are the problems they're having what are they willing to buy? And then maybe what can you build to like address that need?

7:03And then you go back and you draft a spec and you think about it and then you make a design and you execute it. We internally at Anthropica are now pretty much closer to the point where like, don't even write a memo, just like, let's build all the candidates very quickly. Let's just build all of them and then pick the best ones. I think the decision that is most impactful both for the product as well for the users right now is like the way we put value on your local computer. I think that's a big decision point. A lot of people have thought about should this thing, whatever it is, should it ultimately run into computer or should it run in the cloud?

7:41Because they're big trade-offs, right?

7:43Felix Rieseberg:I guess like if we solved auth, it would be easy to do in the cloud. But I think like the fact that I can just download any file from anywhere and then put it in co-work there, it's like a big unlock. I mean, it's interesting you mentioned reusing certain pieces. I think this is something I've been thinking about even with cloud code, right? The price of like writing code is going to zero, blah, blah, blah. But it actually seems like the value of having some sort of platform substrate is like increasing because as you build these new things, you can kind of plug them together. So I almost feel like when people are saying, oh, the value of a lot of software is going to zero because you can recreate it.

8:17Felix Rieseberg:To me, it's almost like the opposite. It's like having an existing platform to build on top of is like even more valuable because you can kind of bolt things on. Yeah. You have obviously MCPs, you have skills, you have like obviously the models, which is a big part of these things kind of come together. Do you feel like that's a valid way to think about it where people should invest even more in kind of like this primitives to rebuild on or are you like recreating a lot of it each time? Because like things change and it's easier to rewrite than reuse. You know, I think I think you're right. I think you're right that the holistic platform is really useful.

8:52And this is maybe a whole, like somewhat contrarian view to a lot of people in AI. I actually don't think that the future is going to be hyper-personalized software down to the point where everyone is running their own version. Like, I actually think it's going to be quite hard for one of us to have our own internal chat tool. And like, if I want to talk to you, like, how is that going to work? Right. In the context of call work and how we build it, I think it's a bit of a combination. Like, the execution that gets cheap is not necessarily rebuilding all the primitives. I think a priori, there's also not a lot of value in it.

9:21So friends and my team do not think about rebuilding cloud code. We like very much started with the, with the core thesis of this should be cloud code. And then we'll like build things on top of it. The part of the execution that gets a little cheaper is like, how do you take all of these Lego pieces and put them together in a way that makes sense for users? It is like actually valuable. You have so many different approaches now in terms of what kind of, what kind of things do you actually elevate to a primitive? Do you strongly believe that all your products should be built by just combining primitives with about all sides available?

9:52Do you keep some things in total? And I think that's still evolving. But I think what's probably going to go away is like, I'm not sure if it's going to fully go away. But I'm going to say, I think for me personally, I will probably no longer try to come up with a really good product without testing it with people. this is not a new concept but wherever you used to have to make costly decisions around do we pick technology a or technology b or do we like um build it this way build it the other way i really strongly believe now you just build all of them and try them out with a small focus group and then whatever whatever is better is where you go with right and that that is probably quite different even from how we maybe worked a year ago right like i think i think this happened very

10:38Felix Rieseberg:recently yeah i started building something in on electron since you're here coincidence but then electron and like sequel light are like there's like some issues that like between development and like building anyway and i was like let's just rebuild the whole thing in swift and just recreated the whole thing in swift and it's like it's done you know it didn't take any effort i i don't even know swift yeah exactly i was like i'm not reviewing it anyway whatever you can write it whatever language you pick. But the important stuff that I did was not write the electron bindings. It was like the logic of what happens in the app.

11:13Felix Rieseberg:And then the model is like, yeah, I can just recreate the same things with. Yeah, I think you still want, especially for people who are doing high-performance software or very complex software, you still want some view of the architecture, but you can use Markdown for that. You don't actually have to read the code. again, I'm still on a definitional thing. Can we build a good mental model of cloud co-work? This is what I have, right? You said it's fundamentally cloud co-work, we don't want to touch it. There's the cloud app, there's cloud in Chrome. I think you guys do something different in planning, but I've been talking with Tariq, who is on the cloud co-team, and you guys are, he's like, no, we just exposed planning.

11:52Maybe you can clarify, what are the major pieces that people should be aware goes into co-work? I think you basically have them, so So you can take planning more or less out. I think that's a few things that are really valuable in Kovac. The virtual machine is probably the most powerful thing. So we currently run like a lightweight VM and we put Cloud Cloud into the VM. And we do that for a number of reasons. Safety and security is a big one. But even if you ignore for a second safety and security and you're just like, okay, YOLO, I want this thing to do whatever. It is quite powerful to give Cloud a sound computer.

12:28that is like generally a good idea. And in terms of architecture and UX and everything else that we've been working on Anthropic, it often is quite useful for you to like anthropomorphize cloud aggressively and just be like, this is a person. What would you do if you had a person, right? And the analogy I've given my dad this morning, who is still like quite insistent on using chat, even for like coding things, is if you were a developer and your employer told you that you don't need a computer, they're just going to like send you emails with the code and you send emails with code back, Like that maybe worked for Petr Mars in the back, but that is not very effective.

13:01So what we can do with the VM is because it's a Linux system, Cloud Code has more or less free reign to install whatever it needs to install. You can install Python, you can install Node.js. We do have strict network ingress and egress controls, so you can still, as a user in plain human language, make it clear to the entire system what you're okay with and what you're not okay with. But at no point do we have to ask a real person, like a person who might be in marketing or a lawyer, I don't have to go to the lawyer and be like, are you okay with me installing homebrew? Yeah. Right? Because the implications of the question and the answer are complex and nuanced and like not easy to reason about.

13:39And this gives us a lot of distraction that makes cloud very powerful. Now then around it, we do probably have a number of things that also keeps growing almost every single week that you're probably noticing that make Kovac maybe better for certain tasks than does cloud cloud on its own. Yeah. But most of those actually live in the system prompt. They're about like, what can we infer about the work that you do? What can we introduce into the system prompt to make that more effective? It's of course, like very tight integration with Cloud and Chrome. You're noticing that a lot of people, especially as the models get better, a lot of people throw up their hands when it comes to MCP connectors in this era.

14:13I'm not going to go through like 25 MCP connectors, click auth everywhere, and then like half of them don't let me do the things anyway. So Cloud and Chrome is quite powerful because we can just talk to the Cloud and Chrome subagent and that will just do things for you. Yeah. So one example, right? In MCP, I honestly, I think the state of MCP is kind of like really hard to integrate. I needed to add Figma MCP to the coding agent that I use. Yeah. And, but I didn't want to read the docs. So I just had caught to it. and it's great at reading docs and in the same way I had to set up like a Google Cloud account for some project I was working on and get some API key somewhere and Google Cloud is famously super hard to navigate so I just didn't want to deal with any of it I just used CloudCore.

14:59Within the first week of developing on CoreWeave this happened very very quickly I caught myself like starting to use CoreWeave for coding tasks which is not ostensibly what we built it for right we don't need to but I found myself I found myself like on our internal tool that we have to collect crashes and just like debugging information. And I found myself sort of like picking out the ones that I think we can easily fix versus the ones that might be like kernel corruption or something else on the operating system. And I found myself sort of picking these out and then just telling Claude, go fix this bug.

15:30I was like, what am I doing here? Go one level up, tell a cowork, I want you to go to all these crash tools. I want you to find all the bugs that you think are fixable and not like an operating system crash and then i want you to tell another cloud to like fix all of that um and that's that's that's sort of another cloud yeah so it can spin up another instance or uh it currently what i do is um and this is a bit of a hack but i tell it to use cloud code remote to just call it itself yeah that's interesting so you basically take if you if you imagine like a dashboard with like 20 bugs. This is remote control or Cloud Code remote?

16:06Sorry, I just wanted to confirm what. The way I'm using it is I have Cowork running and I'm telling Cowork, here's where I normally go every morning to find the latest bugs. Go read the entire bug list, separate out which ones are fixable, which ones are not fixable. And then for the fixable ones, for, is this almost a loop, for each bug, write a markdown file with a prompt. And then for each markdown file that is a prompt, start of a cloud set. So natively, cloud code has this concept of subagents. And this is basically a subagent, but you're not using the subagent's functionality. I'm not using the subagent's functionality.

16:39And the reason I'm not is because I'm firing that off as a cloud code remote task. That's kind of nice because then it can just fire it off. I can go to my next meeting and in cloud code remote, now the work's happening. Yeah, you see, like, you're already starting to use the cloud over your local machine. And I think this is one of those things where, like, well, shouldn't just everything just be cloud first, right? This is such a good group. I'm like solely about this. I have so many thoughts about that. Okay. So I generally believe that Silicon Valley overall is undervaluing the local computer.

17:08And my default argument for that is always, how come we're all using Macbooks and not like an iPad or a Chromebook? There's like still value in having a local machine. And now when I think about Claude, it's this entity that is supposed to be very useful to you. Like it's tremendously useful to you. I think that entity needs to have access to all the same tools you have access to. Otherwise, it's going to be hamstrung in all these complex ways. And there's sort of two approaches we could take. We could say, okay, we're going to one by one chip away at everything that is at your computer and move it into the cloud.

17:41That's one way to do it. And I think other products have taken that path. I personally, this is a very personal opinion, but I personally, for the amount of tools that I use, just don't have the patience to give another tool like permissions to every single thing and keep those permissions up to date. The second thing that I'm still grappling with, and I don't have a good answer for anyone just yet, but the second thing I'm still grappling with is what does it look like for someone to slurp up your entire work and put that in the cloud? Like if I just, as an example, like if you would click a button and I just clone your entire computer into the cloud, is that something that you would want?

18:19I'm not totally convinced yet that everyone will. And that is sort of like upstream of all the technical issues we're going to have. Because in general, I think the world is not ready for this kind of stuff. I'll give you one quick example that would probably be very easy for us. So as a desktop app, we, in theory, with your permission, can do a lot of things on your computer, including reading your Chrome cookies, if we really want to do it. We could take your Chrome cookies, you wouldn't have to decrypt them for us, But we could put those on the cloud if we really felt like it. Pretty easy solution.

18:50That would be super cool. We could just be like, oh, we can do all your tasks in the cloud now. A lot of websites, banks included, if they see the same authentication from like two different locations, we'll just lock down your account. And now you have to go to the branch and be like, okay, I'm here with my passport. You actually know that. Wow. You know, as tired as we all are of the term agent for the agentic future, I think there's a lot of stuff that sort of slowly needs to catch up. and until that's the case the way I as someone who's working on Cloud can make Cloud most effective is to like put it where you're working Anything else with our mental model?

19:22So like basically like part of me also just want like the more I understand how it works the more I can use it to its full potential, right? Yeah And so what I'm hearing from you is you told me to delete the planning thing you're not doing anything special that's only exclusive to Cloud Cowork We have some tricks but they're sort of like change week over week Like we eval Cowork maybe against different use cases than you would eval ClockCode, right? How do you think about it this way? Okay. So like ClockCode is... I'd eval ClockCode. So ClockCode is like quite optimized for coding tasks and we mostly evaluate whether or not we're getting better or worse depending on how good it is at like a typical sweet job.

19:58And ClockCode, on the other hand, we evaluate more against typical knowledge work, the kind of stuff he would find in finance or in like maybe like a legal office. My personal use case is always like managing my... things like managing my personal mortgage or something like that, right? Or like wealth planning for me and my family. Those are the kinds of use cases we eval CloudCodeWork on. And what you might be picking up on is like the subtle changes we make to the system prompt, what we put in the system prompt, how we steer Cloud with the tools we give it. So like either it'd be better in one or the other direction, whether there's a trade-off, trade-offs exist a lot, CloudCode will be better for code and CloudCodeWork will be better for non-coding tasks.

20:38Will those gaps still exist in the next few generations of models? It's like a little unclear to me though. Yeah. Because right now, these like hyper optimizations we make, I'm not sure for how long they're still going to be relevant. I think what I was referring to was also, it just, it qualitatively felt different when I, probably it's just out-prompting and I'm reading too much into it. But like the fact that it comes out with like a nine-step plan, I can edit the plan and give feedback and see it execute the plan. Yeah, it felt more long range than in Cloud Code, but maybe that already existed in Cloud Code and then you just built a nicer UI for it.

21:14It's kind of both. Like if the Cloud Code people who build the planning functionalities with Cydia, they would say, yes, we have all of those things in Cloud Code. And they do. I think people tend to give co-work tasks that are maybe of a longer time horizon. It's so long. Yeah. That's like one thing, right? You're just like the chunk of work tends to be maybe a little bigger. And then the second thing is that because the work, when it gets longer, it gets a little bit more ambiguous. We do tell co-work to make heavy use of the planning tool or to make heavy use of the ask user question tool, right?

21:46We do want it to come up with like different scenarios of, okay, tease out what the user actually wants. Don't go off to work for like four hours and then come back with the wrong thing. And you're probably picking up on that. Yeah. I wish I could tell you I like built this magical thing and it's like there's some secret sauce. Oh, no, no, no. I mean, it's just clarity is good. engineers just want to know so they can plan around it. And I think also for me, I'm realizing I have to switch to my other machine because this is a new machine and doesn't have my session. But yeah, the planning is really important for me to approve or to see whether it's right.

22:19The ask user question is so beautifully presented. I mean, it's also available in Cursor and Cloud Code. But I think it's so nice to see that it's kind of for me like to understand that it gets me, it gets what I want to do. Yeah, yeah. It drives very hard. Just on the topic of evals, when you say eval, I think people are very vague about what it means. Is it just like vibe testing or do you have like automated programmatic evals of Cloud Cowork? When we say eval, what we really mean is that we essentially take the entire transcript, including all the tools that cloud has available ultimately to it, and we then measure what are the outputs depending on what we tweak.

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23:02So we do run that a lot. We use that in training. We use that in like, if you sort of separate out post training from like the scaffolding around it, cowork sort of exists in the scaffolding space, but obviously we also train on it a little bit. So when we say eval, we mean given the certain transcript, what do the outputs look like, including the file outputs, as well as the actual token outputs, like the ones that you see in the TAT window.

23:24Felix Rieseberg:I'm curious how much of the failure modes are the model intelligence versus like the usage of the end tool to put the intelligence in? Like the world planning is like a good example, right? It's like one thing is to come up with a plan. The other thing is like make a nice spreadsheet that kind of runs you through the plan. Like how have you seen that evolve? The thing that I grapple with a lot is that whatever scaffolding you come up with, I think we still have a bit of sort of like model overhang where the model is dramatically more capable than users I'm using it for. And I think part of that is that we're just not getting the model, all the tools to do all the things that's theory capable of, right?

24:02That's like one thing. However, whenever you do build the scaffolding, I'm sort of wondering at what point will that scaffolding go away? And like how much you invest in figuring out what the right scaffolding is, it's kind of up to, it's a little bit of a bet, right? And one thing that I as an engineer quite enjoy is that like working in Anthropic and working at a frontier lab, I maybe have a little bit more insight into what's coming down the chute in terms of like, what's the next model? What is the model capable of? What is good at? What is it bad at? And I'm increasingly wondering, is the right thing for us to like really invest too much in sort of these like scaffolding corrections where the model might otherwise not misbehave, but just not do the thing that you want?

24:40Yeah. Or is it to just give it as many capabilities as possible, try to make those safe so that the worst case scenario is not as bad as it might be otherwise, and then just simply wait a second for the next model drop? I'm personally currently more leaning into the latter. I think we're going to see a lot of applications and companies that do very impressive things with AI that in the short term might seem very effective because they're very specialized to individual use cases. but I think once models get better at generalization and get better at like those specific use cases without being super guided on those I'm not sure how long that's going to stick around and you can kind of already see this in like skills and MCP servers, right?

25:19We've already seen sort of this like slow shift from MCP servers to skills and like maybe a good example is Barry who made skills he was initially hacking on something that honestly looked a lot looked a lot like what Cowork does today he was sort of thinking about what if Cowork but for like people who don't want to build code. And he too did that as a prototype inside the desktop app. One of the first use cases we thought of were, okay, what are like coding like use cases that could really benefit from graphical interfaces and like from being a little separated from the actual underlying code.

25:53And everyone comes up with the same answers, data analysis. Right. Or it's like, how many users do we have today? How many? Like it's always data analysis. this. And I think the thing that ultimately led to skills is that we want to connect this little prototype to our data warehouse. And the team very quickly discovered that like, instead of building a custom tool for the thing to talk to our data warehouse, they just like made a markdown file like, dear Claude, if you want to get data, here's the endpoint, here's what the API looks like, you figure it out. And then they hand over control. Yeah.

26:25Yeah. Also just like maybe go one step up in the layer of abstractions. Right? Just like, instead of telling the thing, here's a CLI, please call the CLI or here's an MCP, please call this interface shape. Just like, this is the end point. If you want to know something, if you post here, maybe you can do post SQL. It's going to be okay. And that ended up being so effective that they started trying the same pattern of like just giving the model a markdown file that describes whatever it needs to do that the whole thing eventually became skills. And we're like, we should package this up. This is a good idea.

26:57Yeah, we've had Barry Mahesh on our conference, and he's definitely got a good idea there. Yeah. I wanted to show you how I've been using Cloud Cowork. So this was my favorite part. This is so this is like me. This is how we run the Discord. We literally at first, I didn't trust Cloud Core. This is my very first usage. Okay. Right. So then I was like, okay, I will just try to manually download from Zoom all my recordings and upload it to YouTube because this is a very laborious process. I got to click, click, click. YouTube isn't super user-friendly. And it just did it. And then I was like, actually, you know, even the download from Zoom part, I should also put into Cloud Cowork.

27:39And then I did it, right? Here's a bunch of, and it starts compacting here. And it starts to even be able to do things like look through the individual frames of the video to name the video so that I can upload it automatically. And this replaces my job as a YouTuber. We will forever appreciate your creative. Yes. And so that's great. But then, by the way, it compacts and makes like a new thing, right? So I don't have the initial thing. But then I asked it to make its own skill so that something that's repetitive and one-off and human-guided becomes more automated and I can use the skills independently and reuse them.

28:15And it obviously can write skills. And that goes into context and skills at the bottom here, which is so nice. So I have all these skills that I now sort of do on a weekly basis. I know you've released scheduled co-works, which I haven't done yet. But of course, you should try them. I think this is like so wonderful and fun for me to see, because I think one thing that is very fun for me about skills in particular is that they're so easy to make. Like anyone can make a skill, like a text message could be a skill. And they can be so hyper-personalized to you. And this is like sort of this objection layer, right?

28:47Like, I'm just guessing, but I assume you're very good your job you've already given this thing some guidance about how to do it right i i just said wrap everything up into into a skill right yeah and then and then i was like actually sometimes i might need to break uh things apart because some parts fail or some parts might be needed individually so i told it to split one skill into three skills so it's like a skill splitting thing and then there's like a parent skill that just orchestrates all of them if i want to use that you know like um i think that's that's like really good uh and uh there's there's one more part which is the Google Chrome thing that I told you about, where I'm like, okay, you know what's better than uploading using Cloud Coworks to YouTube?

29:25Like actually looking at the docs to like programmatically upload to YouTube and then putting that in a skill. And I've never done that before. I don't want to deal with Google Cloud. So Cloud Cowork does it for me. So I just, I don't care. I just like, let it do its thing. It doesn't really matter. That is really cool. And then you, I assume, paired the skill just with the script that it's built? Yeah. And then I just update the skill. Oh, that is beautiful. Yeah, that's wonderful. It's kind of like a skill. Basically, I think like the way that people ease into Cloud Cowork is like take a knowledge work task that you would normally be clicking around for and then try to turn that and then you do the, okay, well, what if you went further?

30:03Okay, and then what if you went further? And you sort of expand the scope of Cowork as you gain trust with it and also teach it how to replace you. Yeah, it's like a little bit like playing Factorio, but for your own life. Like you say, you start really small. You start automating something really tiny. And like once it clicks, you keep adding onto this like automation empire, just like make your life easier and easier. My favorite skill has been every single morning, Koberk starts looking at my calendar and make sure that there's a conflict because people tend to schedule a lot of meetings, sometimes last minute or sometimes miss it.

30:37It's often painful. And a lot of products have existed like that a lot. I've written in the custom prompt there. I haven't made it a skill. Honestly, I should. But I've given it pretty clear instructions about, okay, here are some people, if they book over other meetings, I'm probably going to go to their meeting. Like if Dario schedules a meeting.

30:55Felix Rieseberg:Right. Not try to reschedule Dario, right? And I think there's some other rules in there about what kind of meetings I care more about, what kind of meetings I care less about, what is okay to maybe punt when I want to be working, when I don't want to be working. And it's those really small things that I think kind of click with people. right when we launched Cowork, I think one of the user cases that went most viral on Twitter X was clean up your desktop, which is of course silly. That's such a thing, right? Like you don't need to model to clean up your desktop. Not really. Like this? Like clean up my desktop?

31:29Yeah, exactly. Yeah. I need to choose my desktop, right? I guess. Give it access to my desktop. Yeah. Okay. Okay.

31:37Felix Rieseberg:This is very scary. We'll do it. I did it with my downloads folder. It was like, you have so many term sheets and there's like eight copies of your rental lease for your office. I was like, all right, like, don't yell at me. It's such a small task. And I would never go out there normally otherwise and tell people, I've built a product that can organize your folder for you. Because it feels small. But I think to your point, like... Here's the ask user questions. Yeah. Beautiful, right? Elite obvious junk. You probably shouldn't click that. No. It's not just reversible. I don't make a plan. Yeah.

32:13Yeah. No, I have a typical, everything is super messy folder. So yes, I think this is super helpful. So this is a pretty simple task, but I've, okay, here it is, right? Here's the progress. I don't see this in this. I'm like, this gotta be something different than, than cloud code because I'm like, we do. Yeah. That's, we do system prompt. We're like, all right, we want you to think about like this task. Yeah. And then I can do little suggestions for these things. It's beautiful. Look at this. I can say, oh, don't do that. Don't do this. It's amazing. I'm so happy you like it. I mean, the other way around, we're part of the Cloud Code team.

32:51If you would like this in Cloud Code. Yeah. Damn. So, yeah. I mean, this is really good. Obviously, I'm kind of raving about it. I have other things like sign up for PG &E. So if you can do phone calls for me, that'd be great. I do. People have done that. Obviously, you can't do that natively, but people have done that with various other providers. Yeah. And then this is signing up for the Figma MCP. I really am trying to do everything in data analysis as well. I do think, oh, design to code, very, very good. So here's a Figma file, take it. And then this is where a lot of other tasks is like knowledge work, like replace my manual clicking.

33:33But this is, no, I would normally use Cloud Code for this, but But because I perceive that you have better Chrome integration, I think you can actually do a better job of this. And this is one shot at my conference website. That's pretty cool. Like at some point I would love to like hear how you feel about code in the desktop app. I never use it. Which is the same team. Same team. So I use the cloud coding terminal, which I perceive to be the default way of cloud coding. So one thing this has, sorry, I'm just like, I'm not here to wrap all these products. So can I talk about other stuff? I'm not sure if people out there want to like hear me advertise my stuff for like an hour.

34:10Please do that. This thing is like a built-in browser, which is a thing a lot of products have. He said, yeah, it's a built-in browser. And I think giving cloud eyes into like what you're actually working on makes it so much more effective. And that's probably what you've seen in co-work because it can see Chrome. It can like debug the DOM. It can like see things. That does make it more powerful. Yeah. So I think my mental model is kind of broken because I only use this co-work because I thought it had a browser thing in it. But I understand that the Cloud Code app or the app version of Cloud Code does have a built-in browser.

34:42I've seen this preview thing. Yeah. I've never used it. But in the end, you sort of get like... Habits by heart. Yeah, you basically get the same thing, right? Like the additional skill that you're describing is a lot is better if it can see what it's working on, right? That's sort of like the summary here. And like whether it's using your Chrome or it's just like making up its own little like browser, doesn't really make a bit difference because either way, it's going to see what it's working on and that just makes it much better. And then you don't have to run QA for your cloud. Why doesn't it pick up my existing cloud code sessions?

35:13Because I mean, obviously, I've used cloud code, but... Excellent question. Don't have a good answer other than like, we're honest. I just haven't, yeah. This is what the OpenAI team does. Cool. I don't have other, like, I just, I do want to expand people's minds and also maybe show people if they haven't really done it. But like, I think it's very interesting how I sometimes use this more than I use, I mean, I use Dia, right? Yeah. And I've used all the other agentic browsers, and Enthropic didn't have to build an agentic browser because you just had cloud cowork, and that's enough. Yeah. I also think maybe integrating with a number of excellent browsers out there is currently on my personal priority list a little higher than trying to rebuild a browser from scratch.

35:56Yeah. I'll never say never, but I think going back to this idea of, Like we want to plug this into an entire existing workflow. I think our goal is actually to not replace any of the applications you have on your computer. But instead of like work really well with a new workflow. Make the new one. Yeah.

36:11Felix Rieseberg:Yeah. It seems that nowadays, especially in the browser, most of the innovation is like user ergonomics. It's not really like the underlying browser engine. So I feel like to call it, it doesn't really matter if it's like VIA or Chrome or Alice, whatever. Yeah. We want to meet you wherever you are, which is like, Like, obviously I would say that, but it's also just genuinely true because I don't want to restrict my potential user base artificially by saying, okay, like I'm going to start building for the people who are willing to switch browsers. Right. That's such a, like, you know, like many lawsuits have been filed over who gets to every other browser.

36:48And like a lot of money has switched hands over the question of like which browser is default and which search engine is default within the browser. I just want to build for, yeah, I want to build for Swix, essentially. I want to build for people who have a number of annoying tasks that they feel like maybe Clark could do it for them.

37:08Felix Rieseberg:Yeah. What do you think about skills portability? I think there's been one thing. I use another thing called Zo, which is kind of like a cloud computer plus agent. And I have a skill to add visitors to the office. Yeah. So whenever somebody has to come in after hours, they need to check in downstairs. But I want to like text the thing so it doesn't really work in in co-work. But now that skill is in the zone harness and it's not in my co-work thing. And then if I make a change, I got to sync them. How do you see that going? Like I see memory as like cloud personal kind of like I don't necessarily want my memories to be crossing.

37:45Felix Rieseberg:Yeah. But I do want my skills to be cross agent that I use. I think with MCPs, people do the same thing. It's like, oh, MCP gateway, MCP registry. I don't really know if that's like a business. So I'm curious, like, if you've had any thoughts in the area. I think for me, this is sort of where I go back to the really basic primitives. For us, skills are file-based instead of like this complicated thing that exists inside a place somewhere that is like super proprietary. I'm really leaning into the idea of like, it's all just files and folders. And that makes it very portable on its own, right? We do have skills as part of this container format, which was just called plugins.

38:21And plugins are available both for Cloud Code and Cloud Code work. the same format and you can install plugins this works in co-op today you can basically say i'm going to add a whole like just a github repo as a skills marketplace or like a plugin marketplace and that's how we're doing potability i think we have a lot of room left to grow in how do we make it easy for people to know that they can write skills how do we make it easy for them to just like share a skill with you because obviously all the words i just said right like i'm losing most of the knowledge worker base out there right start for saying oh you can connect to github repo it's not exactly how most people will end up working in like a general knowledge worker space um but i think there's something there and another thing that's there that i think has not really been properly explored is the the the combination of which part of the skill is very portable and then which part of the skill is like very personal to you right and i think that's something we haven't really solved yet in the industry it's like which time you want to introduce more structure to the skill or have always have like public skill, private skill, you know, pairs?

39:26Yeah, yeah, kind of. I think that's like, like the easiest way to do this, which is we do like use string interpolation or something, right? Right. Yeah. Insert username here, insert like phone number, insert like known folder locations, that kind of stuff. That's probably clunky. That's why we haven't built it. But I do think someone is going to come up with like an interesting way to keep everything we like about skills. The portability is just a file. It's just Markdown. It's just text, honestly. Write like a text file words. The complete lack of structure, which means you don't need any kind of tutorial to write a skill.

40:00Just like explain it to Claude the way you would explain it to me and Claude will probably get it before I work in, right? You're just like, for booking a flight, tell Claude how to book a flight the same way we're telling somewhere I just started working here today. But combine that with a very like personal thing. Maybe we'll stick with the booking of flight example. I don't actually think AI should be booking flights. I think the tools we have is yes. Yeah, finally, somebody says it. It's the default demo that everyone was making. I'm like, I ain't against like booking demos. It was not a good showcase.

40:32Yeah, I'm like, I just want to book my flight myself. But I think there's a lot of things that have a personal and a non-personal component. And that's maybe why people reach for flight booking, because some things are very universal. cheaper flight is usually better, right? Like few people try to book the most expensive flight. And then some things are quite personal about like what times you prefer, which seat you prefer, which airports you prefer. Combining that and like a skill format that is actually portable, compatible, easy to understand for people. I think that would be very exciting.

41:02We just haven't figured it out yet.

41:03Felix Rieseberg:Yeah, I think the techs part, I think everybody by now has some sort of like cloud file thing, either Dropbox, Google Drive, whatever. So it feels like in a way it should basically like Simlink my skills into all my agent harnesses. Yeah. Just keep those in sync. Like we have internally this like valuable tokens repo, which is like all the commands, sub agents. It's good. And then I built like a TUI where you can start and be like, you know, install this command and this three sub agents into this agent in this folder and just copy paste this. It doesn't do anything. It literally CP the file into that.

41:36Felix Rieseberg:But I feel like there should be something similar where like whenever I go into a new thing, it's like, hey, here's like the link to exactly the cloud folder. and just bring down these skills into this. Like today, it doesn't quite work like that. Like if I install a new agent, I cannot, I have to like copy paste all the skills and I don't even know where they are. That's like the big problem. It's like, where do I find them? So I'm curious, like in the future, like that almost feels like my personal productivity thing will be my skills. It's not really the product that I use because everybody has access to the same product.

42:08Felix Rieseberg:But today that just looks like copy pasting MBA files. I think so many things. I really like thinking about agents and LLM just as like another coworker. So many attempts have been made to build documentation companies that are like, oh, we're going to solve all your documentation problems. I myself like spend a little bit of time working in Notion, right? I'm like deeply familiar with the concept of let's get everyone on the same page. What you're basically saying here is you want all your agents to be on the same page about your preferences about the skills about the way they ought to work and like how they ought to execute i'm not sure what the right thing is going to be if it's going to be some some company that can say all right we're as an independent body we're not trying to like push into any particular product it's our job to be like the skill authority and we provide i don't know we're going to be the dropbox of skills and we can just sim link us into all the products they want to use i'm not sure that's going to be viable business but as as an idea it would be cool right yeah yeah i think so many things are just going away as businesses.

43:08It's like, how am I supposed to do it?

43:10Felix Rieseberg:I'm not even asking somebody to make a product about it. Like, I want to personally know. And there's things, like you said, it's like, you almost want a skill and then interpolate it between personal and work. So if I'm booking a flight for work, it's different than I'm booking a flight personally in some ways. But like a lot of the scaffolding is the same, you know? I mean, as an engineer, I will tell you like, you know, technical person, technical person, I will just be like SimLinks. Well, that's what that's what I do with Cloud.md and Agents.md. It's just the same as how SimLinks. And so it's like that works, but it feels like, yeah, I don't know.

43:44Maybe you could always go one level up. You can always talk coworker problem and then coworker will solve it for you. Just make the SimLinks. That's like one way to do it.

43:51Felix Rieseberg:That's true. That's true. All right. Everything is called cowork. Potentially spicy question for both of you. Which of these industries will go away? Okay. So what Felix was saying before is interesting. There's basically like the short-term pressure of like, we need to turn these tokens into valuable things, which is I should build the last mile product that harness the model. And then there's the question of like long-term, which ones are going to still be valuable? And I think you're kind of seeing this today with like, you know, the coding space in a way. It's kind of like everybody's moving up and up in stack because you need more than just turning tokens into code.

44:29Felix Rieseberg:I think search, like enterprise search is kind of seeing the same thing, like with Glean and like all these different companies. It's like at the end of the day, if cowork is the one doing all the work, the search itself is like such a small part that like, I don't know if I'm really going to pay that much money just to do search. It's almost like everything is like a cowork vertical. So like how much can cowork first party support and how much can it not? I think for a lot of these things, the planning thing that you were showing, the planning, the planning. Okay, yeah. Yeah. Like, that's one thing where, like, most of the value that these agents provide is, like, they're better at planning for specific tasks and have better tools for it.

45:10Yeah.

45:10Felix Rieseberg:But I think the models are now moving in that direction. And they have the right harnesses and they're on your computer. So, for me, it's almost like if the end customer trusts your startup to be the provider of that task result, then I think that works. This is something that, this is a spike that we're working on. Yeah. I think, look, I'll tell you this. I don't think I'm the best person to actually estimate which industry is going to hit the hardest. But I do think that at Anthropik, as a group of people, we're deeply worried about the impact that the tools are going to have on the labor market, especially for like junior employees.

45:55Because I think it's only honest to say that when we talk about automating away a lot of the work that we personally find annoying, that we maybe think it's not the best use of our time. In a lot of industries, that kind of work would have been given to a junior entry-level employee, right? And I think it's only right to be really worried about that and worry what that's going to do, in particular to people like enter the shop market.

46:20Felix Rieseberg:I have a solution for that, which you make them, you create stimulative jobs for them. Okay. So this is like half joke, half true. So if you think about software engineering, when you're like a junior engineer, you work like one, two, three years. And in those three years, there's like maybe like an end-fold moment where like you really learn something. And then a bunch of other days where like, you're not really progressing. Yeah. I think now we can use AI and these models to actually like shortcut these careers and almost like simulate the early years of your work and like just make them like super dense in like these learnings.

46:56Felix Rieseberg:It's like, hey, we're working on this feature, which is like a distributed system and you need to learn this thing. That might take three months at a company. And so you take three months. Here is like, we're just simulating the whole thing. It's actually not a real thing. And in one week, we kind of speed run through the whole thing. And you kind of learn your lesson from there. And we kind of repeat that. And like one year, you basically get like three years worth of like projects and experience. I think it's harder for like things like sales or for things like, you know, marketing, because you don't really have a way to get the feedback loop.

47:28Felix Rieseberg:But I think a lot of it, it sounds kind of silly. It's like you're making them do a fake job, but it's almost like you go to college, right? People pay to learn how to do it. And this might feel similar where it's like, hey, we have the Jane Street simulator. It's like, you want to come work at Jane Street? we'll just put you in the simulator over like three months and you'll come out of it. It's like, you know, I'm ready. So there is an aspect here. I'm not an expert enough to like actually know what is going to happen to marketing or legal or finance, right? Like I don't work in those jobs and I don't think I should talk about them, but I am an engineer and I think I have a pretty good idea of what engineering is like.

48:03And I think one thing we're sort of seeing is that as a company and also as the public, we're like deeply worried about entry level, but we're also seeing more senior engineers accelerate it. If you like, they're more productive, they actually increase the value they provide. And the thing that I'm thinking about a lot is the fact that even before all of this happened, I've always had a lot of respect for the University of Waterloo. And the new grads that have joined my teams as from coming from the University of Waterloo, always felt like more ready than new grads who literally spent their entire time at the university, regardless of how good, but never actually had to work inside an environment where you have to ship things that eventually will be used by users.

48:44And I'm German. I initially went to German university. And I think the information systems programs there tend to be very theoretical, right? I often give people the example of trying to become a doctor, but you first have to do four years of biology. And as a result, when you get a new grad, you sort of have to teach them what it's like to actually build products and to work in a company and work with other people. and like some people will have a different opinion and like how do you do all of those things and the university of wadalu it seems like they just spend half of their time i don't know if it's true but i think it's a year right they spend so much time part of your job or curriculum to do spend a year in internships yeah they just like go from company to company they show up on your team as like a junior engineer who's been to like 20 companies not really but like it seems like a lot of my new grads have also briefly worked at apple google tesla yes and uh there's a common meme where they like collect all these logos like infinity stones but and they always put it on linkedin it's very unclear that they were an intern like yeah yeah exactly but it does actually make them so much better compared to other new grads and i wonder if that's a useful model maybe for the future when we also have to like crunch down the amount of time you have as a junior employee because the value you have the junior employees going to like be impacted my sort of pro young people take is that you're more, you have higher neuroplasticity.

50:04You can learn more, you have less pre-existing biases. And what I assume is true for you, what OpenAI often says is that actually it's the younger, like first grad engineers that use codecs or they're coding stuff more innovatively than the experienced engineers who have a set and preferred way of doing things. Yeah, as I talk to people, I have some of the experience. Yeah, so maybe you're more AI native and therefore you get cut. But I think the problem is you don't need that many of them. I mean, Anthropic is on the record as saying we do believe that the impact on the market is going to be sizable.

50:41And we do not think that people overall are ready, right? And we do actually think we should probably talk about it as a society much more. I'm not sure that I'm like the individual that can add anything useful there. But I think as societies with economists and governments that need to wrestle those questions in a way that is probably more meaningful than me wrestling with them, we're probably not doing that enough. Yeah, well, we'll try to educate. And then I think also just releasing frequently as you guys do, or probably maybe too frequently, is helping people to adjust over time. Rather than one big bang thing, there's like sort of this gradual takeoff that people are living through that we're waking people up.

51:21Right? Yeah. And I, but I think a lot of us like wondering at what point do we actually have full takeoff? Right? Like at what point is there, we're all sort of expecting this like big bang moment where things will accelerate so quickly that it becomes a self-reinforcing loop. And at that point it's sort of like off to the races and there will be no more like slowly catching up. You know, just have Cloud being so good at everything. Yeah. It's when co-workers training models. It's when it's looking at TensorBoard and weights and bias and training things. And like, we can all debate like how many years it's away, right?

51:52Like some people make a bet around like maybe it's 10 years away, maybe it's a year away. I'm not entirely sure where I come on this line, but I'm not entirely sure that ultimately it matters all that much whether or not it happens in four or five years. If we have a decent one, certainly that's going to happen. It's probably something we should wrestle with. I wanted to talk, so by the way, the scheduled task complete, the clean my desktop task complete, and it did. It organized by file type, which, okay, but you know, I was trying to get it to do more sort of thematic, like read the file, understand what it's about, group by the topic rather than the file type.

52:23I mean, you can just follow up and have it do that. Oh, yeah, fair. Like it is proposing this, right? Yeah, so it's got some like topical things, but yeah, I could probably do better. Like, yeah, so like I probably need to give it a skill to read video files so that it understands that here's how I like to... Honestly, though, like I see that you're using Opus 4.6, right? Like my recommendation for people is increasingly don't worry about it anymore. just like tell it what you want it to do yeah and it's probably going to figure out a way to do it okay it might not be the way that you like necessarily or the way that you've gone about it

52:55Felix Rieseberg:videos deeper but we're outsourcing organizing all of this so that's fine okay yeah yeah i'm honestly like so curious what cloud is going to come up with i'll kick that off i wanted to also just talk about the overall uh you know you talk about data analysis you talk about like uh your your personal finances you also said uh which by the way for us is very timely tax season, right? Like, you use Cloud Core for tax season, it is not responsible for any mistakes, but might as well, right? Like, it's free knowledge work for you. So I just, like, I think Cloud for finance is a big deal. And this is definitely, like, in that mix.

53:28I wonder, is it, like, is it a separate team? Do you talk to them? How important is it, right? Like, you can also natively output Excel files now. Yeah. Just talk about the finance effort. Yeah, we care about the verticals quite a bit. So we do have a dedicated verticals team. We also have a dedicated enterprise team and there was this is engineering not sales it's engineering yeah yeah it's engineering so we do have people who sort of come to work every single day and they they ask themselves how do we make co-work extremely effective for people in those specific industries how do we make it easier for them to understand how do we make it easier for them to plug into this and like sort of get the same value out of it that software engineers get i think it's no real surprise that software engineers ended up being sort of at the forefront of the entire ai moment because so much of it is this like Rube Goldberg machine-esque, where like we're already used to automating things, right?

54:13Like it's part of our job. Yeah. So we care about it quite a bit. I think it also like really matches what we see Cloud being very good at as a model. I think it provides tremendous amount of value to those customers in particular, because we can do so much with the amount of data they have. Those are like data-heavy industries. Their industries were correctness matters quite a bit. For us, if I've used it to analyze my business, I just can't show it. That's two cents. I had a similar question about taxes. I did tweet about the fact, I did tweet about, oh, COVID is doing my taxes. This is honestly incredible.

54:47And it's like annoying because this is so cool, but I'm not going to... Twitter is maybe not the audience that needs to see my tax return. Yeah, here it is. It's reading on the videos. So it's getting more. Yeah. How did it actually do it? I'm actually curious. Oh, usually it just takes a screenshot and then it reads the screenshot by vision. so this is what i do for my my zoom upload thing right because i i have paper club sessions that i need to upload to zoom and i wanted to automatically uh title them and do show notes and everything so it just takes screenshots and try to try its best yeah it would probably benefit from transcribing which it's doing by it's operating my pure vision now but it's good enough yeah and then i i do have to call uh out to nano banana to do images so unless you guys do images for me i have to call other people with images.

55:35We're aware. It's just like so fun for me because like this is the thing that I'm increasingly doing, like increasingly curious about Claude's creativity and like figuring out what is great. Claude's approach is like certain problems. Yeah, vision for everything is like the superpower, right? Like, you know, and computer use, you guys were the first to do computer use, right? And when it was launched, I was very unimpressed. I was like, it's slow, it's unreliable. It's bad. It was one year ago. Yeah, I know. So, like, it was barely usable. Yeah, I remember it was barely usable, but isn't it wild how much better things have gone over like one year?

56:10We went to the Anthropic office because for the launch event for computer use, like, there was like this hackathon. Yeah, and like nobody hacked on computer use. But I did see, I don't know if you were okay with me saying that, but I did see briefly that you do have like a, like an automate macOS MCB server installed, right? Have you used that ever? Sorry, which one? Where? If you go to your settings. Oh, settings, okay. Sorry, this one? Yeah. Yeah. I noticed that in your connectors. I probably set it up one time, but I don't use it actively. Oh, okay. A MaxWise automator. Yeah, yeah. So, yeah, this one, I really wanted to just automate everything in my thing.

56:46I didn't find it super reliable. Okay. Why? No, no. That's not true at all. Cloud is much better at writing AppleScript and executing its own AppleScript than relying on these third-party tools. Yeah. So I've increased, I initially installed IMCP and like all these other MCPs that people built and, but now I don't use any of them anymore. Like just, just let claw write its own thing. Yeah. It's going to be more custom made. We keep going up the stack. But I think computer use is like a fairly interesting area to me. And it's like also interesting in the sense that I don't think we're far away from, I don't think we're far away from claw being very effective at like using your computer and not just a theoretical computer.

57:28Felix Rieseberg:What's the relationship between the user and the computer? Like there were some tweets about how huge some of the VMs that Cloud Cowork creates are. It's like 12, 15 gigabytes and people complain. But at some point it's like, if you're using the computer, you're taking action, is this just your computer? And I'm just looking at it. You know, it's like, I think that's why people like the idea of like the Mac mini and the open claw or whatever on it, because it's like, it got its own home, you know, it's doing its thing, I'm doing my thing. I think there's some kind of like not like race condition but it's like okay if I kickstart this task now I can't really use the computer you know because cloud coworker is doing things on it and it's kind of awkward like yeah I'm not sure I do think it's a super interesting area because I can maybe tell you like some of the things I thought about that I think actually bad idea so when when we initially started working on coworker I did have some dreams about what would it look like for cloud of its own cursor could be cool right like it's a computer we can write code, we can touch everything.

58:27Who says that computers need to have one cursor? We could do a second cursor. But that actually breaks down quite a bit, even if you go and present cool dreams to both Apple and Microsoft. You're like, wouldn't it be cool if? It breaks down quite a bit because so many of our models on a computer are built around this idea of there's only one thing working on it. There's a foreground app, a background app. Cloud and Chrome can work in the background, but that's within one application. But the operating system layer, that is a lot harder to implement. So I'm still grappling with what does it mean for Cloud to actually act on your computer?

59:00Is the right format for Cloud to have its own computer that you set up and maybe every now and then you like zoom in and you play with it? Or is the right format for Cloud to just like wait until you're stepping away for a little bit and take over while you're gone? Or is the right move for Cloud to just like have its own computer in the cloud and like whatever you want Cloud to do, you have to set up yourself? Right? There's like a number of different options. This is a thing I think about a lot, like what is the relationship between you and your computer and you and your data on the computer?

59:33Because how intimate that relationship is kind of depends on the tool and the thing that you're currently looking at, right? Like we're quite comfortable sharing some things, very uncomfortable sharing other things. And I think whatever product is going to be successful, we'll have to deal with those different things. but you probably, even if Cloud was capable making a determination, would you want Cloud to make that determination in the first place? It's tricky, Barry, because it's like, it's more than just privacy. It's like almost intimacy. And it's like tricky to reason about in a way that will make everyone comfortable.

1:00:08Felix Rieseberg:Yeah, I could see, you know, a virtual box, like actual virtual box app where like you run the VM and then you have like a screen within the screen, you know, you can put in the background, but then you can like jump in the screen. You know, that's not a good idea. You know, like, I mean, I used to, you know, people used to do it virtualizing like Kali Linux in a Windows machine. Yeah. And you just jump in and then you jump out. But it's like, it's not like a dual boot. It's like within the thing. The problem is that you need twice the amount of RAM, twice the amount of, you know, it's like, it's kind of taxing on the machine.

1:00:40Felix Rieseberg:But I think that would be cool. Kind of like see, you know, the little card window. I can see it's desktop, look how cute it is clicking around things. I was going to bring up, he's the original machine and the machine guy because he has the Windows 95 project. Where's the Windows 95 project at? There's probably someone on my GitHub. No, no, no. The first thing you see is this one. Nice. Exactly. That was honestly a very fun project though. Obviously, I didn't I should say this just so that no one gets the wrong impression. I did not write the actual obviously I didn't build Windows 95 because I was a child But also, I did not build the actual engine that is capable of simulating an x86 processor in JavaScript and Watham.

1:01:24That's a tool called V86, which is very cool and everyone should try. But this came out of a debate we had at work where people were like, they often are in the end of debating the merits of Electron and whether or not we should be building software in JavaScript, yes or no. And I still am very upset that I can run all of Windows 95 in JavaScript and launch Microsoft Excel inside the virtualized JavaScript Windows 95 machine and do things that I can do that entire chain faster than I can do a lot of other things in like traditional SaaS applications. This is sort of like a performance rampage that I went on.

1:01:59So I mostly built this as a joke for some of my colleagues at Slack. This took like one night. What? but then that I it was not hard to do it was all the hard work is in V86 like if you go to the repo it's going to say like 99 % of this work is done by by a guy who goes after the by the name Copy his name is Fabian yeah cool I think you're you're kind of back on the Windows grind because you're building out the Windows support I thought there were some really cool technical stories to tell and it gives people an appreciation of like well here's how hard it is and here's how important how you invested the sandbox.

1:02:38So maybe this is like a good opportunity to talk about some of the details. Oh yeah, the VM honestly is like so cool. There's a lot of things we dislike about the VM, right? Like there's a lot of things that are real trade-offs and you want to know why you're making those trade-offs. And you're right, like a lot of people write me like, hey, how come Cloud is taking up 10 gigabytes? I could say on that point, it's not actually taking up 10 gigabytes. It's just like a way that macOS displays bytes. It's like wrong. but the way we actually write it to disk is by we collapse the empty space in the image.

1:03:08So it's not actually taking up 10 gigs, but that's a technical differentiation. That's for Nocturne. To me, the outcome is it takes too long to start. Yeah. It's like 30 seconds sometimes. I don't know. Oh, it should be faster than that. Whatever. It's maybe 10, but it feels like 30. Yeah. Like even either way, like whatever it is, it's going to be, it's going to be slower than just running Clarko directly on your computer. Right. So the trade-offs are real. But what we're doing on Windows, we're using the Windows host compute system. It's the same thing that WSL2 runs on, like the Windows subsystem for Linux, that I think a lot of developers appreciate quite a bit.

1:03:41Yeah. And it's pretty cool because we sort of like have to separate out which system space this virtual machine runs and who gets to talk to that virtual machine because obviously you give this virtual machine a decent amount of power. How do we optimize not just the connection between the two systems, but also how do we make sure that random other application doesn't get to talk to Claude inside the VM. We do some pretty interesting things. Last week, we started writing a new networking service, a networking driver that optimizes how Claude talks to the internet. If your company is doing like weird internet things like patent inspection and like, taking your part as a cell inside your company.

1:04:19I think there was probably like a very small, easy version to build of Cowork that is much simpler, but also breaks on most users' computers. and this one is quite nice because it works on most users computers. And the default example I always go for is, I really want this to be highly effective on a machine that most people pick up and that machine will probably not have Python, it will not have Node.js. And even if I just take away those two things, Cloud is going to be so much less effective on your computer. So what do you do? You don't even, I mean, maybe require people to install Node in Python.

1:04:53Oh, you mean for like, what does the future look like without a VM? No, no, no. So like you said, right, let's say a target machine is whatever is a default spec windows laptop. We do this, which is quite cool. So on macOS, we use the Apple virtualization framework, which is pretty solidly optimized. Like it's good stuff. And it's a simple API call, right? It's like super simple. I saw the code recently. I'm like, that's it? What the fuck? Would you, once you start like shipping production code on it, you start adding like all of these edge cases, you know, it ends up being a little longer. But I think Apple really cooked with a virtualization framework and it's very, very good.

1:05:30It is very fast. It's very reliable. And same on Windows, the host compute system, I think WSL2 as well is maybe one of the diamonds within Windows. It's like one of the few things that developers universally rave about is very, very cool. And like hooking into the same subsystem makes it a lot easier for us to say, we don't really care how locked down your computer is. Maybe it's like your employer's computer and your employer has decided that you get to install nothing. Not trusted. But it's true in a lot of environments, right? Like even at Anthropic, our IT department controls what kind of stuff you install, which is like a pretty common experience for many companies.

1:06:06And this gives IT departments a decent amount of, like it makes their job so much easier because we can say you can separate out Cloud's computer from the user's computer. And then for Cloud's computer, what you probably care about is data loss. you care about like a potentially hostile actor, you care about maybe data being exfiltrated. And once you control the network and the file system layer, you don't really care necessarily anymore that Cloud might be writing super useful Python scripts. What worries you about the fact is that like, once you install Python, now anyone can do anything on a computer.

1:06:39But once you put that in a VM, that risk really goes down. Yeah. So that's why we jumped through all of these loops. Yeah, I think you had a different tweet about this, but it's almost like, people have also approved exhaustion. Like, it's like you can't approve every single command. Like, sometimes by default, some of the CLIs, I think even early cloud code, we have to approve every single command. Yeah. And like, so there's this sort of dichotomy between either approve every step or dangerous leads get permissions. Yeah. And actually sandboxing is like kind of like the middle ground. Yeah, I do think it's maybe on us as like the AAN history to come up with something better than, oh, this is super safe as long as it doesn't do anything.

1:07:21Right. If you want this to be useful, then you have to like approve every single step of the way. And like computer use is a good example. The only way to make computer use on your host like super safe, like really super safe is probably if you approve every single action, right? Like models, like I would like to type the word L. And you're like, okay, that seems fine. I know, I know which like cursor is focused. Yeah, it's not automation if you don't delegate. Yeah, exactly. You need to like probably delegate. you need to be able to like delegate and walk away and trust that this thing is not going to like mess automatically and i don't even think we need to build perfect systems i don't think we need to wait for like 100 model alignment we can rely on the same swiss cheese model we've used in the industry for a long time but i do think we need to like universally maybe eventually invest more and that's what we're doing we need to invest more in systems but we can say you do not need to approve everything speaking of swiss cheese modeling he just wrote a thing about this oh cool yeah Yeah, super cool.

1:08:17I mean, yeah, it's weird how like, I guess usually I think safety and security is kind of like a boring word to engineers. They're like, just give me unsafe, give me unsecure. But I think achieving the right thing, like you're going after a consumer slash prosumer. Yeah, kind of like both. I think I also want to capture people who would have no trouble using cloud code like yourself, right? Yeah, yeah. But still find them maybe just convenient, easier. and you're like, oh, cool, that's like the to-do list on the right. I can edit it. Those things are just easier to do if you have to. Yeah, but this is like clearly the knowledge work side.

1:08:51Cloud code will clearly capture the development workflow. But like, I do think like you have to sweat this like safety and security details in order for people to trust it. And like even cloud and Chrome, like having the whatever API uses to do the background thing. Yeah. That's the only reason I use it is because otherwise I would have to just get a separate machine. Yeah. And just run it. And that sounds super annoying. Yeah, I mean, I'm currently doing it, but... And I think also as developers, maybe we are more risk tolerant, but we're also just like accepting... We are more risk tolerant, but I think we also just have like, I don't want to say arrogance, but like sort of the trust that if like the really bad thing happens, we can probably fix it.

1:09:30I just tell Claude to like check with me before doing any irreversible action, like sending an email or doing it permanently. It's good enough. But like not even Claude, I mean like simple things such as NPM install. like we're all running npm install with full user permissions and if it wants to like read.ssh it will crazy that that is the default kind of what yeah i know i agree i agree at the fine like i'm obviously doing it every single day no right like uh and i think obviously npm and get up to have like done a pretty good job maybe over the last couple months to like clean house and come up with like more specific tokens but generally speaking i think as engineers we've always been a little bit more risk tolerant and if you do a little bit of introspection and you ask yourself is that how we should be doing things.

1:10:13You might not always come up with the right answer. And I think for models too, like my approach, like I'm not going to, the safest thing is to do nothing. We do want products that are quite capable, but to the extent possible, I don't want to ask you, are you okay with a script? Because I kind of believe that once it starts becoming a part of your workflow, you're probably not either, either you don't have the skill to understand whether or not this Python script is safe, or you're not going to read it anyway. Cool. I guess a couple parting questions. What's the future of Clockwork? I think we're still in such early days.

1:10:46We're going to keep shipping things that we're going to keep shipping things that we're going to keep iterating on this thing like pretty quickly, but which I mean you can sort of continue to expect that every single week there's going to be like a small new feature if not a big new feature. I'm going to continue probably to double down on your computer and like making you effective on your computer and making cloud effective on your computer. We're starting to grapple as we talked about today, grapple more with the question of like, what does it mean? What does your computer mean? Does it have to be the one in front of you?

1:11:12Or like a VM on your computer or like a computer somewhere else? And then the third thing that I'm quite excited about is we're continuing to go up this hill climbing on slowly taking users who are used to asking questions and getting an answer to slowly teaching them to like step more and more away and that claw take over like bigger and bigger tasks and work both in time as well as in like scope. And I think you can probably see most of our investments on our feature releases to like work on both of those things. Like the ability to do more on your computer and then the ability to do it more independently for longer.

1:11:48Does remote control work for Cloud Cowork yet? No, right? Excellent question. Coming soon. I mean, that's an obvious thing if you want to keep betting on your computer. But to me, like, you know, we talk about like people are not ready this year. Like there's no wall. it's accelerating to me like what will be we be doing differently at the end of this year that you know we may be not even thinking about this at the start of this year right like i'm just trying to look ahead as to like what's like a good use case that you're we sort of aim towards so for example for the machine learning scientists it's always okay well i want ai scientists that can automate machine learning but like for for knowledge work i mean i can already you know get it's a sign of a Google Cloud to me in SAGI.

1:12:33Because Google Cloud is smart. But like, what's beyond that? I don't know. I think it's basically the idea that like, you still had to tell her to build your script, right? You were still kind of involved. Yes. In maybe a way that felt kind of magical to you. But like maybe to me on the other side as the person building this product still feels kind of heavy handed. I see so much process that I'm like, oh, let me take that away from you. Okay. Like, how do I just go? I will continue to go or continue to go like further and further up the stack and make your life easier and easier. Oh, here's one, right?

1:13:03Yeah. Watch, you know, I don't care about my own privacy or whatever, or I trust Anthropic. So just watch everything I do on a normal day-to-day basis. At the end of the day, tell me what is called co-workable. Yeah. I don't know. I think the funny thing about a lot of these products is that, like, for good reason, I don't enjoy, I don't feel my entire career. I've never, like, teased too much what I'm working on because I think you should just, like, Yeah, to lose it. Yeah, build the place. release it and then talk about it. Like I'm not a big fan of like vague posting my own work ahead of time.

1:13:35But the thing that is like always so fascinating to me is like both of you all multiple times a day you've like mentioned things and like yeah that is obviously like very obvious that someone should be working on those things. And I think we're still in the space where if you look at co-work the things that we will be releasing will probably not be a big surprise to either of you. You're going to be like yeah obviously that's valuable. Obviously that we're working on those things. And obviously that's good and useful. And the more I hit those points, And the more our features fit into that category, I think the better it is for us because then we don't end up building things that are too hyper-specialized, too difficult on this style.

1:14:07Yeah, I think the hyper-specialized thing is very important. It keeps you, like, general purpose. It means you're not thinking too small, maybe. I don't know what the word is. Yeah, yeah, exactly. It's like the whole concept that, like, at no point if we release, you know, there's no cloud code for Node.js applications that use React and 10 stack and only those two things. And, like, if it's anything else. I know several startups like that. I think that's pretty, like, I'm not a VC. I'm not an investor. It's, like, hard for me to predict where the markets go. But in terms of the building blocks that I'm interested in, Electron is probably by far the most popular thing I ever built.

1:14:42And Electron itself is, like, very abstractable and generalizable, right? Like, so many apps are in it. And I think it would have been hard for me to predict how many apps actually end up using Electron. And what would have been even less useful for me to predict is what those apps do. I just really remember Bloom coming out of me. That is cool. Like your camera in a little circle in the corner. That is pretty smart. That's an extranet. Yeah. Or at least was, I'm not sure if it still is, if it was for a while. Or like 1Password has so many interesting things, right? It's a level of the stack that I'm quite comfortable with.

1:15:15And whenever I give other engineers advice, it's actually that layer that I think is most valuable to invest in. Because the tools of the layer are not that good, but that's where you get the most leverage. Yeah. The future in general. Just quick tangent on Electron, because I always wonder this. Have you looked at Tori? I have, yeah. What's your take? My view is most things should be Tori by default unless you really need the full power of Electron. Yeah, I can give my big take. Why do we ship an entire version of Chromium inside the thing? Why do we do that? And people ask me this question a lot because it's very counterintuitive.

1:15:51Wouldn't it be much easier to use the web views that are on the operating system? Wouldn't it be much easier not to have to do that? And the answer is yes. And like, obviously I did that. Once upon a time, I did that. It was a version of the Slack app that used just the operating system web views. Wait, did you start the Slack app? I would, well, team effort in it. Yeah, but I was there. We built the Slack app. Yeah, it was crazy. I mean, obviously you get the Electron guy to do it, but. Well, but this is an interesting point. Like by the time I joined Slack, they already had an app that was built with something at the time called MacGab.

1:16:24It was a little bit like the same app gap thing for mobile. It just used the operating system's web views. And that didn't work for so many reasons. And they were like, all right, maybe we need bigger guns. We need to take more control of the rendering stack. And there's a few things I always mention here. I think if you're building a small app, just going with the operating system's web view is perfectly fine. If you're building an app maybe that doesn't have too many users who will cry bloody murder if it doesn't work, that is fine. And the reason to go with your own embedded rendering engine is because, and this is still true in 2026, the operating system rendering engines are not that good.

1:17:01They're just not that good. Both Microsoft and Apple are trying to move away from that. They so far really haven't. The only way to upgrade those is to upgrade your operating system. So if you're say a Slack and you have a critical rendering bug in WK WebView and some of the other WebView options, your only recourse is to tell your customer, oh, sorry, you're too poor. You didn't buy the latest Macbook. Unacceptable. Unacceptable to the user, unacceptable to the user developer. So you sort of need to like go down the stack and like find the best rendering engine and then put it in your app. Why Chromium, even though it's very big, Chromium is by far the best thing.

1:17:36Like I often like to remind people the Unreal Engine, you want to render some text, they use Chromium. Like Chromium is part of the Unreal Engine for the same purposes. Chromium is very, very good. I think it's like one of the marvels of engineering. It's very hard from where in San Francisco right now is where we're recording. Most of the people in the city are web developers. It's hard for me to like overstate how magical it is. that you can run, like rendering a YouTube video, dynamically negotiating a bitrate, figuring out what to do about your extremely broken hardware driver. Actually, this is a fun thing.

1:18:13You can enter chrome, colon, whack, whack, GPU. Okay. And if you scroll down a little bit, these are all the enabled workarounds because something is going wrong on your computer. If you're doing this on a Windows computer with like a GPU that is not the most popular GPU, it will be much longer. And all of these are usually just there to make sure that if I say as a developer, I want a red pixel to appear here, that that actually happens. Chrome is such a marvel because it works on all the machines that a user might throw at you. And it's going to work fairly reliably. And if it doesn't, they will probably fix it within 24 hours.

1:18:51I see. So this is the super operating system, right? That works everywhere. Yeah. All right. Okay. Yeah. So a lot of the magic of Electron is honestly just that it makes it very easy for you to ship Chromium in a way that serves you exactly in your use cases exactly. Our next interview is with Mark Andreessen, who had the phrase like, desktop OSs are just poorly, poor implications of the actual OS, which is Chrome, which like actually works everywhere. And this is the platform where you ship apps. I think the wild thing is that I guess engineers, we so often sort of assume that the platform, like the layer below us is like super stable.

1:19:24and then he talked to those people and then I got, we were also just like guessing. And I had like a distinct moment at Slack where one of our customers at Slack was NVIDIA. And for a while, I really put GPU developers on this pedestal in my head. And I do think they're still probably much smarter than I am. But I was like hardware engineers who built the chips, who then like built the drivers. Their work must be so much harder than mine. They must be very good. And we had like one bug in Slack where like if you had a YouTube video in Slack, it wouldn't quite render why it would have these weird artifacts.

1:19:58And that ended up being a Chromium bug and I ended up on this giant thread. So I got to see a lot of the source code. And they also are just like common to do. We don't know why this is weird, but if you flip this bit, things work. This is just like happening every layer of the stack. Maybe the end of year AGI prediction is that Cloud can build Chromium. You see, you laugh now, but Yeah, you know, someday. It's starting to get pretty good. Like, it used to be completely useless, mostly just, like, overwhelmed both with how hyper-specialized tools are inside the Chromium repo. Like, for a long time, the Chrome method, like, sort of reinvent all the tools because none of them are capable of ending Chrome.

1:20:40I think the EGI moment I'm kind of waiting for is at what point are we going to say Electron is probably no longer necessary because you can just build fully native apps. In Swift-D? Yeah, like, not just in Swift, Because this is one thing, like, it's pretty easy. I think our current models are quite capable of taking an Electron app and replicating it Swift. Are they going to be capable of, like, building an app that is actually more performant, uses less memory, all of that stuff? Is going to go into the same hyper-optimization that developers have done for, like, a long time? We're not quite there yet where I can, like, point even our best models at a thing and say, just replicate this in native code.

1:21:17Make no mistakes, ultra-think, right? We're not quite there yet. Um, UltraThink is bad. Today, UltraThink is back. Yes. Okay. Or we'll get on UltraThink for like days. Just a pretty long time for Boral. But he worked on UltraThink for days? Yeah. Why? It's just, it's just a prompt. I'll let it a little bit. The war goes into it.

1:21:37Felix Rieseberg:Yeah. Okay. Another question I had is like co-works. So if I have my cloud co-work, like what's kind of like the multiplayer mode? I think sub-agents is like single players split up the context. Yeah. And the multiplayer coworker is like my colleague has some file on their machine that I want to know about, or I want to know how their task is going to then update my thing. Like, is that interesting? Is that something that makes sense for you to build or for like? It's like super interesting to me. It almost goes back to like some of the scaffolding where I'm like, okay, are we going to be end up, are we, will we end up building scaffolding that will just go away?

1:22:13And like a question I have here is at what point do we just assign these things? like their own Gmail account. We'll just give them their own like Slack handle and then they will just like use the same tools we humans use to interact with each other. You mentioned our finance people. They've been working pretty hard on very good office integrations and I think for a while we've been like we built so much tech around Claude leaving useful comments inside a Google Doc and now it just does it. Just like leaves a comment in your Google Doc and that's how you interact with it. Maybe like the similar thing where I still have open questions around what is the best interaction mode?

1:22:49Is it for us to build something super custom for co-work agents to talk to each other? Or is it, okay, let's just jump straight to the finish line and say, well, we're just going to give this thing, if you use Slack at work, we're just going to give this thing a Slack handle. And that's going to be the way it's like multiplayer capable.

1:23:04Felix Rieseberg:They communicate with each other. Yeah. Like, you know, as a fun project, I build this thing called PiQ, which basically takes any repo and the Pi agent, coding agent. it puts it in a VPS and then there's a public webhook where anybody can submit a coding task. Oh, and then there's a dashboard in which you review the task. And then there's PIQ. PI, P-I-Q.

1:23:31Felix Rieseberg:Yeah, you basically get all these like tasks. Anybody can submit a task. And to me, it's almost like in the organization of the future, it's like the sales people are talking to the engineering team that is talking to the marketing team to the product team and all these co-workers are going to like queue up decisions for other people to approve in a way yeah you know and i'm kind of curious what that looks like and like how do you how do i give my co-work the ability to both approve tasks without asking me yeah and how to decide which one i need to review you know because for some of these things it's like you know you want to change the color or something that's kind of like a branding decision or another one is like hey your thing is just broken it's like this is like how you fix it and claude can actually review whether or not that prompt matches what it's trying to do today everything is still very it's like multiplayer within the single player you know i can spin up many of them but like how do i get multiple people to hand off to each other things using their particular context yeah and for both of your co-works to like talk to each other right right yeah hey we got an episode today can you're like, have you, you know, or?

1:24:39Yeah, this is like, I know we're like running out of time here, but like we previously talked about sharing skills and I did have this question of like, what if your coworker would just like ask the other coworkers if they have a skill for this task? There's another thing you could do, right? Like, okay, so skill transfer. Yeah, like, and again, that's maybe a bit creepy. This maybe goes back into the territory of like building something very powerful and building something creepy often goes hand in hand because I could tell from the reaction that my fellow engineer said that this is probably not what we're going to do.

1:25:09But like, we have Bluetooth LE, right? Like I, this computer can figure out that it's sitting right next to this computer. So you're probably working on the same thing. Will you see that in co-work? Probably not. But there's like, I think really creative solutions to problems that we really haven't tried yet. Yeah, yeah, yeah. Excellent. I guess the last thing is Anthropic Labs. I always have this mental model of a model lab versus agent lab. And this is basically Anthropic's internal agent lab which Cloud Code is now under, right? It's part of the whole org. I mean, people are so fungible, right?

1:25:42Okay, this is just... I don't know how real this is. No, it's a real team. It's a very team. The last team is primarily working, though, on things that you don't see in public yet. They're trying, like, really wild out there ideas that seem quite improbable. The mad science thing. But are you officially under this thing? No, where is it? Cloud Code is... Now Cloud Code is, like, a fairly big group. where I actually know how many people we are. Like I remember yesterday coming into our weekly cohort meeting. I was like, whoa, this is a lot of people here. But we still have a Labs team. And we actually made the Labs team a lot bigger.

1:26:18Mike just joined the Labs team as an IC, which I think is very cool and very fun. But they're working on things that you have not seen yet that are extremely out there and probably half broken, right? Like the sort of the idea of a Labs team is that it should only work on things that make really no sense for anyone else to work on. Okay, well, looking for exciting things from there. But thank you so much. I know we're out of time, but I appreciate your joining us. I appreciate Cloud Cowork. Everyone go use it. It is the closest I've felt to AGI this year. That's so nice to say. Thank you very much.

1:26:48Thank you for your time.

From the publisher

Claude Cowork came out of an accident.

Felix and the Anthropic team noticed something interesting with Claude Code: many users were using it primarily for all kinds of messy knowledge work instead of coding. Even technical builders would use it for lots of non-technical work.

Even more shocking, Claude cowork wrote itself. With a team of humans simply orchestrating multiple claude code instances, the tool was ready after a brief week and a half.

This isn’t Felix’s first rodeo with impactful and playful desktop apps. He’s helped ship the Slack desktop app and is a core maintainer of Electron the open-source software framework used for building cross-platform desktop applications, even putting Windows 95 into an Electron app that runs on macOS, Windows, and Linux.

In this episode, Felix joins us to unpack why execution has suddenly become cheap enough that teams can “just build all the candidates” and why the real frontier in AI products is no longer better chat, but trusted task execution.

He also shares why Anthropic is betting on local-first agent workflows, why skills may matter more than most people realize, and how the hardest questions ahead are about autonomy, safety, portability, and the changing shape of knowledge work itself.

We discuss

* Felix’s path: Slack desktop app, Electron, Windows 95 in JavaScript, and now building Claude Cowork at Anthropic

* What Claude Cowork actually is: a more user-friendly, VM-based version of Claude Code designed to bring agentic workflows to non-terminal-native users

* Why “user-friendly” does not mean “less powerful”: Cowork as a superset product, much like how VS Code initially looked simpler than Visual Studio but became more hackable and extensible

* Anthropic’s prototype-first culture: why Cowork was built in 10 days using many pre-existing internal pieces, and how internal prototypes shaped the final product

* Why execution is getting cheap: the shift from long memos, specs, and debate toward rapidly building multiple candidates and choosing based on reality instead of theory

* The local debate: why Felix thinks Silicon Valley is undervaluing the local computer, and why putting Claude “where you work” is often more powerful

* Why Claude gets its own computer: the VM as both a safety boundary and a capability unlock, letting Claude install tools, run scripts, and work more independently without constant approval

* Safety through sandboxing: why “approve every command” is not a real long-term UX, and how virtual machines create a middle ground between uselessly safe and dangerously autonomous

* How Cowork differs from Claude Code: coding evals vs. knowledge-work evals, different system-prompt tradeoffs, longer planning horizons, and heavier use of planning and clarification tools

* Why skills matter: simple markdown-based instructions as a lightweight abstraction layer for reusable workflows, personalized automation, and portable agent behavior

* Skills vs. MCPs: why Felix is increasingly interested in file-based, text-native interfaces that tell the model what to do, rather than forcing everything through rigid tool schemas

* The portability problem: why personal skills should move across agent products, and the unresolved tension between public reusable workflows and private user-specific context

* Real use cases already happening today: uploading videos, organizing files, handling taxes, managing calendars, debugging internal crashes, analyzing finances, and automating repetitive browser workflows

* Why AI products should work with your existing stack: Anthropic’s bias toward integrating with Chrome, Office, and existing workflows instead of rebuilding every app from scratch

* Computer use one year later: how much better it has gotten, why vision plus browser context is such a superpower, and why letting Claude see the thing it is working on changes everything

* Why many “AI verticals” may get compressed: specialized wrappers may matter in the short term, but better general models and stronger primitives could absorb a lot of narrow use cases

* The future of junior work: Felix’s concerns about entry-level roles, labor-market disruption, and whether AI can compress early-career learning into denser simulated experience

* Why Waterloo grads stand out: internships, shipping experience, and learning how real teams build products versus purely theoretical academic preparation

* The agentic future of the desktop: what it means for Claude to have its own computer, whether AI should act on your machine or a remote one, and how intimacy with personal data changes the product design space

* Why Electron still mattered: shipping Chromium as a controlled rendering stack, the limits of OS-native webviews, and why browser engines remain one of the great software abstractions

* Anthropic’s Labs mentality: wild internal experiments, half-broken future-looking prototypes, and the broader effort to move users from asking questions to delegating increasingly long and valuable tasks

* Why the endgame is not just more capability, but more independence: teaching users to trust AI with bigger scopes of work, for longer durations, with fewer interventions

Felix Rieseberg

* X: https://x.com/felixrieseberg

* LinkedIn: https://www.linkedin.com/in/felixrieseberg

* Website: https://felixrieseberg.com/

Anthropic

* Website: http://anthropic.com

Full Video Pod

Timestamps

00:00 — Cheap execution and building all the candidates00:44 — Intro in the new Kernel studio02:47 — What Claude Cowork is04:18 — Why user-friendly can be more powerful05:33 — How Anthropic built Cowork07:09 — Prototype-first product development08:00 — Why local computers still matter09:20 — Skills, primitives, and platform leverage12:13 — Cowork’s architecture: VM + Chrome + system prompt15:38 — Felix’s own bug-fixing Cowork workflows17:38 — Local-first agents20:16 — Evals, planning, and knowledge-work optimization23:14 — What Anthropic means by evals24:21 — Scaffolding, tools, and why skills matter27:44 — Demo: YouTube uploads and self-generated skills31:03 — Calendar automation and cleaning your desktop34:47 — Browser context and why DOM access matters37:47 — Skills portability and plugins44:36 — Which AI categories survive?46:19 — Junior jobs, simulated work, and labor disruption52:00 — Gradual takeoff vs big-bang takeoff53:42 — Finance, taxes, and enterprise verticals56:24 — Vision and the improvement in computer use57:31 — Why Claude writes its own scripts58:06 — Should Claude have its own computer?1:01:26 — Windows 95 in JavaScript1:03:19 — VM tradeoffs and sandbox design1:07:23 — Approval fatigue and safe delegation1:11:18 — The future of Cowork1:12:27 — What comes next for agentic knowledge work1:15:13 — Electron, Chromium, and desktop software lessons1:22:16 — Multiplayer agents and coworker-to-coworker workflows1:26:05 — Anthropic Labs and closing thoughts

Transcript

Alessio: Hey everyone. Welcome to the Latent Space Podcast, our first one in the new studio. This is Alessio, founder of Kernel Labs, and I’m joined by swyx, editor of Latent Space.

swyx: Yeah, so nice to be here. Thanks to, uh, TJ, Alessio, Allen helping to set everything up. It looks beautiful. We even have the logo outside.

Yeah, kind.

Felix: It’s like really nice, right? When you walk in here as a guest, you’re like, ah, this is a serious production. You’re like, feel it immediately.

swyx: Yeah. Felix, you’ve been, you’re, you’re currently a product manager of Cowork or,

Felix: uh, really Technic

swyx: Eng. Yeah. The, the identities are kind of vague member technical staff.

Felix: I know member staff is like, the official title will carry around forever.

swyx: Yeah. I basically kind of wanted, like we’ve been. Kinda obsessed. I, I’ve been using it a lot, even for managing latent space. Like, uh, cowork helps me upload videos and like title things and like edit and everything. It’s, it’s like really amazing.

Alessio: Cool. He said multiple times Cowork has said gi in the group track.

swyx: Yeah, yeah, yeah. So, so we have a second, uh, we have a second channel, uh, for latent space tv. Uh, and I, uh, and uh, we basically, this is our Discord meetup. Um, and I I, we have like Claude Coworks, it might be a GI, I don’t know if we, we have, uh, uploaded it yet, but one of the sessions was like a, like a Claude cowork thing.

Felix: I, you have to see, I would love to see it. Like, I’m so curious, like one of the most fun parts of my job is like constantly see the weird things people use Cowork for because it’s obviously like very hard for us to actually design for specific use cases we do. But like every single person who’s like most amazed is usually amazed about a thing that I didn’t even expect cowork would be good at.

Um, we have a new designer and it’s one of the first small tasks. I was like, Hey, we need like a new emoji for cowork for our internal stock. It’s like a pretty small thing. I like, can you please do it? And he drew an SVG and just gave it to coworker was like, can you animate this emoji? And now it has like this beautiful loopy animation.

Um, and I mean, I think obviously this goes down to like, it turns out you can do more things with code than you expected, but it, it’s like that kind of stuff that is really fun to me. So, long story short, I would love to see like, the kind of things you’re doing.

swyx: I’ll pull it up. I’ll pull it up.

Felix: Yeah. Yeah.

swyx: Uh, but before we get into it, I, I think always wanna start with like a top level. What is Claude Cowork for people who haven’t heard of it? Haven’t tried it out.

Felix: Okay. Uh, real quick, Claude Cowork is a user friendly version of Claude Code. So the way it basically works is we have Claude Code and for us, fairly impressive agent harness that over December we noticed more and more people are using either, even though they’re not technical, they, they’re not at home in the terminal or they are at home in the terminal, but they started using Claude Code for non-coding workloads, right?

Like managing expenses or like filling out receipts or organizing a knowledge base. Like there was a big obsidian moment that a lot of people liked and we wanted to capitalize on that, but also bring, bring this capability to people who are not terminal native and who might not know how to like brew and store something.

So cowork is Claude Code running in original machine with a little bit of padding, a little bit more guardrails, making it a little safer and a little bit more convenient for people who don’t wanna first open up the terminal when they go to work.

swyx: It’s interesting, uh, that is kind of. Pitch that way as a more user friendly thing because I always feel like it, it, to me, I I treat it as like why I’m familiar with Claude Code.

Like we, we did a Claude Code episode Yeah. A year ago. But this one is like even more power user tools ‘cause it, uh, it kind of integrates much better with like clotting Chrome and, uh, in all the, all the other tooling. But like, maybe, maybe that’s like a perception thing, right? Like

Felix: No, honestly, I don’t think you’re wrong.

This is like a, a thing I’ve been thinking a lot about for like the last two weeks. So,

swyx: but when they say user friendly, it’s like, oh, it’s the dumb down version. But no, actually this is the superset.

Felix: Yeah. Like, I think a similar thing happened, A similar thing happened to me about 10 years ago, like maybe 12 years ago when I was at Microsoft and we started working on, on Electron and like browser-based technologies and cross-platform stuff.

And one of the first use cases was Visual Studio Code, which used to be a website. And the initial narrative was, or Visual Studio Code is, is like a more user-friendly version of Visual Studio. But in a similar vein, I think there was some voices saying, oh, this is. For serious developers, like, we’re not gonna use this.

Right? For like anything. And I think in the end what happened is people have different stories about why Visual Studio Code became such a big thing. But my personal, my personal belief is that the Hackability and the extendability has like played a pretty big role, right? You can hook in Visual Studio Code that like almost any workload, it’s so easy to hack on, so easy to put extensions for it.

And I think cowork might be hitting a similar thing where it’s very easy to extend and it’s very easy to bring into your workflows. Uh, so the convenience I think is a bit of a, it’s obviously the thing we strive for as developers, but I think the way people find value in it then is by probably mapping it onto whatever they actually have to do in their job.

Alessio: So end of last year, you see the spike of like non-technical usage and clock code. What’s the design process to say we should make clock code work? Because I mean, you built it in only 10 days. Um, I’m sure there was some discussion before on whether it’s easier to use mean. You know, like making, making like a desktop GUI is obviously one way to do it, but like there’s a lot of nuance in the product.

Like maybe talk people through what was like the trigger of like, we should build a separate thing. We should not build like a different plot code thing. And then maybe some of the more interesting design decisions that maybe you didn’t take.

Felix: Yeah, I think philanthropic, we’ve been thinking about ways to move people who are comfortable with using Claude to answer questions and bring more of the power of like this thing to now like, execute tasks for you.

I can like solve problems for you can like build things for you. How do we bring that capability to people who are currently mostly comfortable with like a like question answer paradigm within the chat. And we’ve had a lot of prototypes around that. Just going back as far as like easily a year and a half.

Like we had a lot of people working on that. Um, and internally philanthropic is a very prototype demo, first culture. We have a lot of like internal prototypes that don’t reach the public. What Cowork actually became is like we sort of picked the right pieces out of the many prototypes that we had.

Right. And that’s, that’s maybe also like, I think an important qualifier whenever people mention this like 10 day number. I do think it’s important to me to mention that within Double Scratch there was like a lot of stuff already happening, right? Like, and I think it’s important for people to remember that when you build a website, you use React, you use like a bunch of other things.

And this is like a similar scenario with like a lot of pieces we already had. Um, and in terms of decision path, I think we live in like an interesting new world where execution is actually quite cheap.

swyx: Mm-hmm.

Felix: So maybe, maybe what you would do That’s so crazy. The year. I know it’s wild.

swyx: You should be, ideas are cheap.

Execution is the hard part. I

Felix: know. And like the, we, we used to live in this world maybe where you would take a product manager and the product manager would go to a number of potential customers and in this like very low bandwidth way, would try to. Try to like tease out what are the problems they’re having, what are they willing to buy?

Um, and then maybe what can you build to like drive out that need and then you go back and you like draft a spec and you think about it and then like you make a design and you execute it. We internally philanthropic app, not pretty much closer to the point where we’re like, don’t even write a memo, just like build, like let’s build all the candidates very quickly.

Let’s just build all of them and then pick the best ones. I think the, the decision that is most impactful both for the product as well for the users right now is like the way we put value on your local computer. I think that’s a big decision point a lot of people have thought about. Should this thing, whatever it is, should it ultimately run into computer or should it run in the cloud?

‘cause they’re big trade offs, right?

Alessio: I guess like if we solve auth, it would be easy to do in the cloud. But I think like the fact that I can just download any file from anywhere and then put it and cowork there, it’s like a big unlock. Um, I mean it’s interesting you mentioned reusing certain pieces. I think this is something I’ve been thinking about even with Claude Code, right?

The price of like writing code is going to zero, blah, blah, blah. But it actually seems like the value of having some sort of platform substrate is like increasing because as you build these new things, you can kind of plug them together.

Felix: Yeah.

Alessio: So I almost feel like when people are saying, oh, the value of a lot of software is gonna zero because you can recreate it, to me it’s almost like the opposite.

It’s like having an existing platform to build on top of. It’s like even more valuable because you can kind of bolt things on.

Felix: Yeah.

Alessio: You have obviously mcps, you have skills, you have like obviously the models, which is a big part. All these things kind of come together. Do you feel like that’s a valid way to think about it, where people should invest even more in kind of like primitives.

To rebuild on or are you like recreating a lot of it each time because like things change and it’s easier to rewrite than reuse?

Felix: You know, I think, I think you’re right. I think you’re right that the holistic platform is really useful. And this is maybe a whole like a somewhat contrarian view to a lot of people in ai.

I actually don’t think that the future is going to be hyper personalized software down to the point where everyone is running their own version. Like, I actually think it’s going to be quite hard for all of us to have our own internal chat tool and like, if I wanna talk to you, like

swyx: how

Felix: is that gonna work, right?

In the, in the context of cowork and how we build it, I think it’s a bit of a combination. Like what the, the execution that gets cheap is not necessarily rebuilding all the primitives. I think our priori, there’s also not a lot of value in it. So for instance, my team did not think about rebuilding clock code.

We’re like very much started with the. The core thesis of this should be Claude Code.

Mm-hmm.

Felix: And then we’ll like build things on top of it. The part of the execution that gets a little cheaper is like, how do you take all of these Lego pieces and put them together in a way that makes sense for users?

It’s like actually valuable. You have so many different approaches now in terms of what kind of, what kind of things do you actually elevate to a primitive, do you strongly believe that all your products should be built by just combining primitive that the public also has available? Do you keep some things internal?

Um, and I think that’s still evolving, but I think what’s probably gonna go away is like, I’m not sure if it’s gonna fully go away, but I’m gonna say, I think for me personally, I will probably no longer try to come up with a really good product without testing up with people. This is not a new concept, but wherever you used to have to make costly decisions around, do we pick technology A or technology B, or do we like, um, build it this way, build it the other way.

I really strongly believe now you just build all of them and try them out with a small focus group and then whatever, whatever is better is what you go with. Right. And that, that is probably quite different even from how we maybe worked a year ago. Right. Like, I think, I think this happened very recently.

Alessio: Yeah. I started building something in on Electron since you’re here. Coincidence. Uh, but then Electron and like SQL Light are like, there’s like some issues that like between development and like, uh, building anyway. And I was like, let’s just rebuild the whole thing in Swift and just recreated the whole thing in Swift.

And it’s like, I. It’s done.

swyx: You know, I didn’t take any effort. I, I, I don’t even know Swift.

Alessio: Yeah, exactly. I was like, I’m the, I’m not reviewing it anyway, whatever. You can write in whatever language you pick, but the important stuff that I did was not write the electron bindings. Yeah. It was like the logic of what happens in the app, you know, and then the model is like, yeah, I can just recreate the same thing as with

swyx: Yeah.

I, I think you still want, especially for people who are doing like high performance software or like very complex software, uh, you still want like, some view of the architecture. Uh, but you can use markdown for that,

Felix: right? Yeah.

swyx: Uh, you don’t actually have to read the code again. I, I’m still like on a sort of like a definitional thing.

Um, can we build a good mental model of Claude Cowork? Um, this is what I have, right? Like you you said it’s like fundamentally cloud co. We don’t wanna touch it. There’s the cloud app, there’s clouding Chrome. I think you guys do something different in planning, but, uh, I’ve been talking with Tariq who is on the cloud co team, and you guys are, he’s like, no, we just exposed planning.

Maybe we can clarify like, what are the major pieces. That people should be aware. It goes into cowork, like,

Felix: okay, I think you basically have them. So really, um, you can, you can take planning more or less out. I think there’s a few things that are really valuable in cowork. Um, the virtual machine is probably the most powerful thing.

So we currently run like a, we currently run like a lightweight VM and we put clocked out into the vm and we do that for, for, um, a number of reasons. Safety and security is a big one, but even if you, even if you ignore for a second safety and security and you’re just like, okay, Yolo, I want this thing to do whatever.

It is quite powerful to give Claus on computer that is like generally a good idea. And in terms of architecture and UX and everything else that we’ve been working on, philanthropic, it often is quite useful for you to like anthropomorphize, um, clot aggressively and just be like, this is a person. What will you do if you give a, if you had a person, right?

Yeah. And the analogy I’ve given my dad this morning who is still like quite insistent on using chat even for like coding things, is if you were a developer and your employer told you that you don’t need a computer, they’re just gonna like, send you emails with a code and you send emails with code back like that, maybe work for Patrick Miles in the back, but that it’s not very effective.

Um, so what we can do with the VM is because it’s a, it’s a Linux system, Claude Code has more or less free reign to install whatever needs to install. It can install Python, it can install no js. We do have strict network ingress and egress controls. So you can still, as, as a user in like plain human language, make it clear to, to the entire system what you’re okay with and what you’re not okay with.

But at no point do we have to ask a real person, like a, like a person who might be in marketing or a lawyer. I’d have to go to a lawyer and be like, are you okay with me installing Homebrew?

Alessio: Yeah, yeah.

Felix: Right. Because the implications of the question and the answer are complex and nuanced and like, not, not easy to reason about.

This gives us a lot of distraction that makes Cloud very powerful. Now then around it, we, we do probably have a number of things that also keeps growing almost every single week that you’re probably noticing that make cowork maybe better for certain tasks than just cloud. Cloud on its own. Yeah. But most of those actually live in the system prompt.

They’re about like, what can we infer about the work that you do? What can we, what can we intru in the system prompt to make that more effective? It’s of course the like very tight integration with Cloud and Chrome. You’re noticing that a lot of people, especially as the models get better, a lot of people throw up their hands when it comes to MCP connectors in this area.

I’m not gonna, I’m not gonna go through like 25 M CCP connectors, click off everywhere and then like half of them don’t let me do the things anyway. So Cloud and Chrome is quite powerful because we can just talk to the cloud and Chrome sub agent and that will just do things for you.

swyx: Yeah, so, so one example right in MCPI, honestly, I think that the state of MCP is kind of, kind of.

Really hard to integrate. Um, I need to, I needed to add, uh, Figma MCP to the coding agent that I use.

Felix: Yeah.

swyx: Uh, and, but I didn’t wanna read the docs, so I just had caught to it. And it’s, it’s great at reading docs and the same, same way I had to set up like a Google Cloud, um, account for some project I was working on and get some API keys somewhere.

And Google Cloud is famously super hard to navigate, so I just didn’t wanna deal with any of it. I just used Claude Cowork

Felix: within the first week of developing on Core. This happened very, very quickly. Um, I caught myself by starting to use cowork for coding tasks, which is not ostensibly what we built it for, right?

We don’t need to. But I found myself, um, I found myself like on our internal, internal tool that we have for, to collect crashes and just like debugging information and I found myself sort like picking out the ones that I think we can easily fix versus the ones that might be like kernel corruption or something else on the operating system.

And I found myself sort of picking these out and then just telling Clark, go fix this bug. I was like, what am I doing here? Go one level up, tell a cowork, I want you to go to all these crash tools. I want you to find all the bugs that you think are fixable and not like an operating system crash. And then I want you to tell another cloud to like fix all of that.

Um, and that’s, that’s, that’s sort of another cloud,

swyx: just so it can spin up another instance or,

Felix: uh, it, currently what I do is, um, and this is a bit of a hack, but I tell it to use clockwork remote to which website itself? Yeah, that’s interesting. So you basically take, if you, if you imagine like a dashboard with like 20 bucks, you, this is remote control or clock or remote, or, sorry, I just wanted to confirm what, the way I’m using it is.

I have cowork running and I’m telling cowork, here’s where I normally go every morning to find the latest bugs. Go read the entire bug list, separate out which ones are fixable, which ones are, are fixable, and then for the fixable ones, four is this almost loop. For each bug, write a markdown file with a prompt.

And then for each markdown v, that is a prompt. Start of a cloud set. So natively Claude Code has

swyx: this concept of subagents. Mm-hmm. And this is basically a subagent, but you’re not using the subagent functionality.

Felix: I’m not using the subagent functionality. And the reason I’m not is because I’m firing that off as a Claude Code remote

swyx: task.

Felix: Yes. That’s kind of nice. ‘cause then I can just fire it off. I can go to my next meeting and in Claude Code remote. Now the work is happening.

swyx: Mm-hmm. Yeah. You, you see like you’re already starting to use the cloud over your local machine. And I think this is one of those things where like. Shouldn’t just everything just be cloud first, right?

Felix: Ah, this is such a good group. I’m like solely bad about this. I have so many thoughts about that. Okay. So I generally believe that Silicon Valley overall is undervaluing the local computer. And my default argument for that is always how come we’re all using MacBooks and not like an iPad or a Chromebook?

Um, that there is like still value in, in having a local machine. And now when I think about Clot, it’s this entity that is supposed to be very useful to you, like it tremendously useful to you. I think that entity needs to have access to all the same tools you have access to. Otherwise it’s gonna be hamstrung in like all these complex ways.

And there’s, there’s sort of two approaches we could take. We could say, okay, we’re gonna like one by one chip away at everything that is at your computer and move it into the cloud. That’s, that’s one way to do it. Um, and I think other products have taken that path. I personally, this is a very personal opinion, but I personally, for the amount of tools that I use.

Just don’t have the patience to give another tool like permissions to every single thing and keep those permissions up to date. The second thing that I’m still grappling with, and I don’t have a good answer for anyone just yet, but the second thing I’m still grappling with is what does it look like for someone to slurp up your entire work and put that in the cloud?

Like if I, just as an example, like if you could click a button and it just clone your entire computer into the cloud, is that something that you would want? I’m not totally convinced yet that all everyone will. Mm-hmm. And that is sort of like upstream of all the technical issues we’re gonna have. ‘cause like in general, I think the world is not ready for this kind of stuff.

Like, I’ll give you one quick example that would probably be very easy for us. So as a desktop app, we in theory with your permission, can do a lot of things on your computer, including reading your Chrome cookies. If we really want to do right, we could take your Chrome cookies, you would have to decrypt them for us.

We could put those on the cloud if we really felt like it. Pretty easy solution. That would be super cool. We could just be like, oh, we can do all your tasks in the cloud now. Um, a lot of websites, thanks, include it. If, if they see the same authentication from like two different locations, we’ll just lock down your account and now you have to go to the branch and be like, okay, I, I’m here with my passport.

You actually know that. Wow. Yeah. As tired as well are of the term agent for the age agent future, I think there’s a lot of stuff that sort of slowly needs to catch up and until that’s the case, the way I, as someone’s working on clock and make Cloud most effective is to like put it where you are working.

swyx: Anything else? I thought with our mental model, so like, basically like, uh, part of me also just want, like the more I understand how it works, the more I can use it to its full potential. Right?

Felix: Yeah.

swyx: And so what I’m get hearing from you is you told me to delete the planning thing. You’re not doing anything special on, on the, that’s only exclusive to Qua cowork.

Felix: We have some tricks for this sort of like change week over week. We eval cowork maybe against different use cases than he would evil clock code, right? If you think about it this way. Okay, so like clock code is our eval clock cowork. Yeah. So clock code is like quite optimized for coding tasks and we mostly value it whether or not we’re getting better or worse depending on how good it is at like a typical suite job.

And Clark Cowork on the other hand, we evaluate more against typical knowledge work, the kind of stuff he would find in finance or in like maybe a, like in like a legal office. Um, my personal use case is always like managing my things, like managing my personal mortgage or something like that, right? Or like wealth planning for me and my family.

Those are the kinds of use cases we eval, clock cowork on. And what you might be picking up on is like the subtle changes we make to the system. Prompt what we put in the system, prompt how we steer, clot with the tools we give it. Um, like either it’d be better in one or the other direction and whether there’s a trade off, try us exist a lot.

CLO code will be better of a code and Claude Cowork will be better. For non-coding tasks, will those gaps still exist in the next three generations of models? It’s like a little unclear to me though.

swyx: Yeah,

Felix: because right now these like hyper optimizations we make, I’m not sure for how long they’re still be relevant.

swyx: I think what I was referring to was also, it, it just, uh, it qualitatively felt different when I probably, it’s just all prompting and I’m reading too much into it, but like the, the fact that it comes out with like a nine step plan, I can edit the plan and give feedback and, and, and see it execute the plan.

Yeah. It felt more long range than in Claude Code, but maybe that already existed in Claude Code and you just build a nicer UI for it.

Felix: It’s kind of both. Um, like if the Clark Code people who build the planning functionalities would city, they probably say yes, we have all of those things in Clark code and they do.

Um, I think people tend to give cowork. Tasks that are maybe of longer time horizon, I thought is

swyx: so long. Yeah.

Felix: That’s like one thing, right? It’s just like that the, the chunk of work tends to be maybe a little bigger. And then the second thing is that because the work, when it gets longer, it gets a little bit more ambiguous.

We do tell co-work to make heavy use of the planning tool or to make heavy use of the ask user question tool, right? We do want it to come up with like. Different scenarios of, okay, tease out what the user actually wants. Don’t go off to work for like four hours and then come back with the wrong thing.

And you’re probably picking up on that.

swyx: Yeah.

Felix: Um, I wish I could tell you I like built this magical thing and it’s like, there’s some secret sauce,

swyx: but No, no, no. I mean, it’s, it’s just clarity is good that, you know, engineers just want to know. Yeah. They can, they can plan around it. And then I think also for me, um, I am realizing I have to switch to my, my other machine because this is a new machine that doesn’t have my session.

But, uh, yeah, the, the, the planning is really important for, for me to like approve or like to see whether it’s like, it’s right. The ask is, the question is so beautifully presented. I mean, it also, it also available in like cursor and, and in Claude Code. But like, I, I think like it’s so nice to see that it, like it’s kind of for me like to understand that it gets me, it gets what I want to do.

Felix: Yeah.

swyx: Yeah.

Felix: It probably very hard

swyx: just on the topical evals. Mm-hmm. When you say eval, I think people are very vague about what it means. Is it just like vibe testing or do you have like automated programmatic evals of Claude Cowork?

Felix: When we say eval, uh, what we really mean is that we essentially take the entire transcript, including all the tools that clot has available ultimately to it, and we then measure what are the outputs, depending on what we tweak, right?

So we do run that a lot. We use that in training. Um, we use that in, in like, if you sort of separate out post training from like the scaffolding around it. Cowork sort of exists in the scaffolding space, but obviously we also train on it a little bit. Um, so when we say eval, we mean given the certain transcript, what do the outputs look like?

Including the file outputs as well as like the actual token outputs, like the ones that you see in the chat window.

Alessio: I’m curious, um, how much of the failure modes are the model intelligence versus like the usage of the end tool to put the intelligence in? Like the well planning is like a good example, right?

It’s like one thing is to come up with a plan. The other thing is like make a nice spreadsheet. Yeah. That kind of runs you through the plan. Like how have you seen that? Well,

Felix: the thing that I grapple with a lot is that whatever scaffolding you come up with, I think we still have a bit of sort of like model overhang where the model is dramatically more capable than right.

Users end up using it for. And I think part of that is that we’re just not getting the model all the tools to do all the things that’s theory capable of, right? There’s like one thing, um, however, whenever you do build the scaffolding, I’m sort of wondering at what point, at what point will that scaffolding go away and like how much you invest in figuring out what the right scaffolding is.

It’s kind of up to, it’s a little bit of a bet. And one thing that I as an NJ quite enjoy is that like working in philanthropic and working at a frontier lab, I maybe have a little bit more insight into what’s coming, coming down the chute in terms of like, what’s the next model, what is the model capable of?

What is good at, what is it bad at? And I’m, I’m increasingly wondering, is the right thing for us to like really invest too much in sort of these like scaffolding corrections where the model might otherwise not misbehave, but just not do the thing that you want?

Alessio: Yeah.

Felix: Or is it to just like give it as many capabilities as possible, try to make those safe so there’s the worst case scenarios, likeno status might be otherwise.

And then just simply wait a second for the next model drop. I’m personally, currently more leaning into the ladder. I think we’re gonna see a lot of like applications and companies that do very impressive things with ai that in the short term might seem very effective ‘cause they’re very specialized to individual use cases.

But I think once models get better generalization and get better at like those specific use cases without being super guided on those, I’m not sure how long that’s gonna stick around. And you can kind of, kind of already see this in like skills and NCP servers, right? Mm-hmm. We’ve, we’ve already seen sort of this like slow shift from MCP service to skills.

And like, maybe a good example is Barry who made skills. He was initially hacking on something that honestly looked a lot, looked, looked a lot like what Cowork does today. It was sort of thinking about what if cowork, but for like people who don’t wanna build code. Mm-hmm. And, um, he too did that as a prototype inside the desktop app.

One of the first use cases we thought of were, okay, what, what are like coding like use cases that could really benefit from graphical interfaces and like from being a little separated from the actual underlying code. And everyone comes with the same answers. Data analysis,

Alessio: right?

Felix: Yeah. Or saying how many users do we have today?

How many, like, it’s always data analysis. And I think the thing that ultimately led to skills is that we wanted to connect this little prototype to our data warehouse and. The team very quickly discovered that like instead of building a custom tool for the thing to talk our data warehouse, they just like meet and embarked on follow like mm-hmm.

Dear Claude, if you want to get data, here’s the end point. Here’s what the API looks like. You’ll figure it out.

swyx: Ah.

Felix: And then it be hand over control. Yeah, yeah. Also just like maybe go one step up in the layer of abstractions, right. Just, yeah. Instead of, instead of telling the thing, here’s ACL I, please call the CLI, or here’s an MCP.

Please call this ECT shape. Just like this is the end point. If you wanna know something, if you post here, maybe you can do post sql. It’s gonna be okay. And that ended up being so effective that they started trying the same pattern of like just giving the model a markdown file that describes whatever it needs to do.

That the whole thing eventually became skills and we’re like. We should package this up. This is a good idea.

swyx: Yeah. Um, we’ve had Barry Mahesh, uh, on, on our conference and uh, he’s uh, definitely got a good idea there.

Felix: Yeah.

swyx: I wanted to show you the, how I’ve been using Claude Cowork.

Felix: Uh, this is was my favorite part.

swyx: This is this. So this is like me, uh, this is how we run the Discord. Uh, we literally, uh, at first I didn’t trust Cloud Core. This was my very first usage.

Felix: Okay.

swyx: Right. So then I was like, okay, I will just try to manually download from Zoom all my recordings and upload it to YouTube. Yeah. Because this is a very laborious process.

I got a click, click, click YouTube, um, isn’t super user friendly. Uh, and it just did it. And then I was like, actually, you know, even the download from Zoom part, I should also. Put into Claude Cowork, and then I did it right. Here’s a bunch of, and it starts compacting here, and it, and it, it starts to even be able to do things like look through the individual frames of the video to name the video so I can upload it auto automatically.

Oh, that is, and this replaces my job as a YouTuber. We will forever appreciate your creative Yes. You know, and so that’s great. Uh, but then by the way, it compacts and makes, makes like a new thing, right? So I, I don’t, I don’t have the initial, initial thing, but then I asked it to make its own skills so that it, so that something that’s repetitive and one-off and human guided becomes more automated and I can use the skills independently and reuse them.

Uh, and it obviously you can write skills and that goes into context and skills at the bottom here, which is, which is so nice. Um, so I have all these skills that, that I now sort of do on a weekly basis. Uh, I know you’ve released scheduled Coworks, which I haven’t done yet, but

Felix: course I should try them. I, I think this is like so wonderful and fun for me to see because.

One thing that is very fun for me about skills in particular is that they’re so easy to make. Like anyone can make a skill, like a text message, could be a skill, and they can be so hyper personalized to you. And this is like sort of the subtraction layer, right? Like, um, I, I’m just guessing, but I assume, heck, you are very good at your job.

You’re probably given this thing some guidance about how to do it, right? I,

swyx: I just said, wrap everything up into, into a skill, right?

Felix: Yeah.

swyx: And then, uh, and then I was like, actually, sometimes I might need to break, uh, things apart because some parts fail or some parts might be needed in individually. So I told it to split one skill into three skills.

So it’s like a skill splitting thing, and then there’s like a parent skill that just orchestrates all of them if I want to use that. You know, like, um, I think that’s, that’s like really good. Uh, and, and, uh, there’s, there’s one more part, which is the, uh, Google Chrome thing that I told you about.

Felix: Yeah.

swyx: Where I’m like, okay, you know, what’s better than uploading, using Claude Coworks to YouTube?

Like actually. Looking at the docs to like programmatically upload to YouTube and then putting that in a skill. And I’ve never done that before. I don’t want to deal with Google Cloud. Yeah. So Claude Cowork does it for me.

Felix: That is really cool.

swyx: So, so I, I just, I don’t care. I just, like, I do a thing. I don’t, it doesn’t really matter.

Felix: That is really cool. And then you’ve, I assume paired the skill just with the script that it’s built.

swyx: Yeah, no, I just update, update the skills.

Felix: Oh, that is beautiful. Yeah. That’s wonderful.

swyx: It’s kind of like a skill, like, uh, uh, basically I think like the way that people ease into Claude Cowork is like take a knowledge work task that you would normally be clicking around for and then, uh, try to turn, turn that, and then you do the, okay, well what if you went further?

Okay. And then when, if you went further, when, if you, and it sort of expand the scope of cowork as you gain trust with it and, and also teach it how to replace you.

Felix: Yeah. It’s like a little bit like playing factorial, but for your own life. Uh, like you say, you start really small.

swyx: Yeah.

Felix: You start automating something really tiny and like.

Once it clicks, you keep adding onto this like automation empire. Just like make your life easier and easier. My favorite skill has been, um, every single morning Kohlberg starts looking at my calendar and make sure that there’s conflicts because people tend to schedule a lot of meetings, sometimes last minute, sometimes miss it soft and painful.

And a lot of products have existed like that A lot. I’ve written in the custom prompt there. I haven’t made it a skill, um, honestly should.

swyx: Yeah.

Felix: But I’ve given it like pretty clear instructions about okay, here are some people, if they book over other meetings, I’m probably gonna go to their meeting. Like if Dario schedules a meeting.

swyx: Right.

Felix: Not try to reschedule down. Right. Um, and I think there’s some other rules in there about like what kind of meetings I care more about what kind of meetings I care less about. What is okay to like, maybe pun like when I want to be, when I want to be working, when I don’t want to be working. And it’s those really small things that I can think kind of click with people.

Right. When we launch co-work, I think one of the US races that went most viral on Twitter. X was clean up your desktop, which is stuff, because silly, that’s such a smart thing, right? Like you don’t need to model to clean up your desktop. Not really. Um,

swyx: like this, like clean up my desktop.

Felix: Yeah, exactly. Yeah.

swyx: I need to, I need to choose my desktop, right? I guess give it access to my desktop.

Felix: Yeah.

swyx: Okay. Uh, okay. This is very scary. Oh, we’ll do it.

Alessio: I did, I did it with my downloads folder. It was like, you have so many term sheets and there’s like eight copies of your rental lease for your office. I was like, all right.

Like, don’t yell at me.

Felix: It’s like, it’s not such a small task. And then like, I, I would never go out there and normally otherwise and tell people I’ve pulled a product. It can organize your folder. Right. Um, because it feels small. But I think to your point like,

swyx: oh, here’s, here’s the, here’s the ask user questions.

Felix: Yeah.

swyx: Uh,

Felix: beautiful. Right. Elite obvious junk. You probably shouldn’t click that.

Alessio: No.

Felix: If he’s not done right.

swyx: As long as it’s reversible, I don’t

Alessio: make up blend to,

swyx: yeah. Uh, yeah. No, I, I have a, I have a typical, everything is super messy folder. So, yes. I think this, this is super helpful. So this is a pretty simple task.

Mm-hmm. But I’ve, okay, here it is. Right. Here’s the progress. I don’t see this in, that’s why I’m like, this gotta be something different than, uh, than Claude Code, because I’m like, we

Felix: do. Yeah. That’s, we do system prompt that. We’re like, all right. We want you to think about like, this task Yeah. Methodology.

Yeah.

swyx: And then I can, I can, I can do like little suggestions for, for, for these things. It’s beautiful. Look at this. I, I can, I can like say like, oh, don’t do that. Don’t do this. It’s amazing.

Felix: I’m so happy. You like it. Um, I mean, the other way around, like we’re part of the Clark core team, if you would like this in Clark COVID.

swyx: Yeah. Yeah. Yeah. Uh, so, so yeah, I mean, uh, this is really good. Obviously I, I’m like kind of raving about it. Uh, you know, I have other things like sign up for pg e so if you can do phone calls for me, that’d be great. Um, I, I do, people

Felix: have done that. Obviously you can’t do that natively, but people have done that with like, various other providers.

swyx: Yeah. Uh, and then this is like signing up for the Figma MCP. Um, I, I really am trying to do like everything, um, data analysis as well. I do think, um, oh, design to code, uh, very, very good. Right? So like, here’s a Figma file, take it. And then this is where like a lot of other tasks is like knowledge work, like replace my manual clicking, but this is no, I would normally use Claude Code or uh, Claude Code for this, but because I perceive that you have better Chrome integration

Felix: mm-hmm.

swyx: I, I think you can actually do a better job of this. And I, this, this is one shot at my, uh, conference website.

Felix: That’s pretty cool. Like at some point I would love to like, hear how you feel about code. In the desktop apps, which is like I never use, which is the, the same team. Same team.

swyx: So I use the call code in terminal, which I, I perceive to be the default way of cloud coding.

Felix: So one thing this has,

swyx: sorry, I’m just like, I’m not

Felix: here, I’m not here. All products. Can I talk about other stuff? Like I, I’m not sure if people out there wanna like hear me advertise my stuff for like an hour. Please do that. Um, this thing is like a builtin browser, which is a thing a lot of products have said.

Yeah, it’s a builtin browser. And I think giving cloud eyes into like what you’re actually working on makes it so much more effective. And that’s probably what you’ve seen in cohort because it can see Chrome, it can like debug the dom, it can like see things. Um, that does make it more powerful.

swyx: Yeah. So, so I think, uh, my mental model was kind broken.

‘cause I only use this cowork because I thought it had a, a browser thing in it. But I understand that the Claude Code app. The app version of Claude Code does have a built-in browser. I’ve seen, I’ve seen this preview thing.

Felix: Yeah.

swyx: I just, I’ve never used it.

Felix: But in the end, in the end, you sort of have it by hard.

Yeah. You basically get the same thing. Right? Like the, the, the additional skill that you’re describing is chart is better if we can see what it’s working on. Right. That’s, that’s sort of like the summary here and like whether it’s using your Chrome

swyx: Yeah.

Felix: Or it’s just like making up its own little like browser.

It doesn’t really make a big difference because either way it’s gonna see what it’s working on and that just makes it much better. And then you don’t have to run QA for your cloud.

swyx: Why doesn’t it pick up my existing Claude Code sessions? ‘cause I, I mean, obviously I’ve used Claude Code, but Excellent question.

Um, don’t have a good answer other than like, we’re honest. Just haven’t Yeah. This is what the Open AI team does. Okay. Uh, cool. I I I don’t have other, like, I, I just, I, I do wanna expand people’s minds and also maybe show people if they haven’t really done it, but like, I, I think it’s very interesting how I sometimes use this more than I use, I mean, I use dia, right?

Yeah. Um, I, and I use, uh, I’ve used like all the other agentic browsers and philanthropic didn’t have to build an agentic browser because you just had Claude Cowork and that’s enough.

Felix: Yeah. I also think like maybe integrating with number of excellent browsers out there, it’s like currently on my personal priority list, a little higher than like trying to rebuild a browser from scratch.

Yeah. You know, never say never, but I think going back to this idea of like, we wanna plug this into an entire existing workflow, I think our goal is actually to not replace any of the applications we have in your computer. But instead of like, work really well within a new workflow,

Alessio: make the new one. Yeah.

Are, it seems that nowadays, especially on the browser, most of the innovation is like user ergonomics. It’s not really like the underlying browser engine. So I feel like to call it, it doesn’t really matter if it’s like the, uh, or Chrome or Alice, whatever.

Felix: Yeah. We wanna, we wanna meet you wherever you are.

Which is like, like obviously I would say that, but it’s also just generally true because I don’t wanna shrink my potential user base artificially by saying, okay, like, I’m gonna start building for the people who are willing to switch browsers.

Alessio: Right.

Felix: That’s such a, like, you know, like many lawsuits have been filed over who gets to review the browser and like a lot of money has switched hands over the question of like, which browser is default and which search engine is default within the browser.

Um, I just wanna build for, yeah, I wanna build for swyx essentially. Like, I wanna, I wanna, I wanna build for people who have a number of annoying tasks that they feel like. Maybe clock could do it. Could do it for them.

Alessio: Yeah. What do you think about skills portability? I think there’s been one thing, I use another thing called zo, which is kinda like a cloud computer plus agent.

And I have a skill to add visitors to the office. Yeah. So whenever somebody has to come in after hours, they need to check in downstairs. Um, but I wanna like text the thing, so it doesn’t really work in, in cowork, but now that skill is in the zone harness and it’s not in my cowork thing. And then if I make a change, it’s gotta, I gotta sync them.

How do you see that going? Like I see memory as like. Cloud personal, kinda like, I don’t necessarily want my memories to be cross thing.

Felix: Yeah.

Alessio: But I do want my skills to be cross agent that I use. I think with MTPs, people do the same thing. It’s like, oh, Mt. P Gateway. Mt P registry. I don’t really know if that’s like a business.

So I’m curious like if you’ve had any thoughts in the area.

Felix: I think for me, this is sort of where I go back to the really basic primitives for our skills are file-based instead of like this complicated thing that exists inside a place somewhere that is like super proprietary. I’m really leaning into the idea of like, it’s all just files and vultures, and that makes it very portable on its own.

Right. We do have skills as part of this container format, which was just called plugins.

Alessio: Mm-hmm.

Felix: And plugins are available both for Claude Code and Claude Code work the same format, and you can install plugins. This works in cowork today. You can basically say, I’m gonna add a whole, like just a GitHub repo as a.

Skills marketplace or like a plugin marketplace. And that’s how we’re doing portability. I think we have a lot of room left to grow in. How do we make it easy for people to know that they can write skills? How do we make it easy for them to just like, share a skill with you? Because obviously all the words I just said, right?

Like I’m losing most of the knowledge worker base out there, right. And start by saying, oh, you can connect to GitHub repo. It’s not exactly how most people will end up working in like a general knowledge worker space. Um, but I think there’s something there. And another thing that’s there that I think has not really been properly explored is the, the, the combination of which part of the skill is very portable and then which part of the skill is like very personal to you.

Right. And I think that’s something we haven’t really solved as an industry. Hmm.

swyx: It’s like, which, how you wanna introduce more structure to the skill or have always have like. Public skill, private skill, you know, pair. Yeah, yeah. Kind of. I think there’s

Felix: like a, like the easiest way to do this, which is we do like use string interpolation or something.

Right, right. Yeah, yeah. Insert username here, insert like phone number, insert, like known folder, locations, that kind of stuff. Um, that’s probably clunky. That’s why we haven’t built it. Um, but I do think someone is going to come up with like an interesting way to keep everything we like about skills. The portability is just a file, it’s just marked down.

It’s just text, honestly. Right. Like a text file words. The complete lack of structure, which means you don’t need any kind of tutorial to write a skill. Just like explain it to Claude the way he would explain it to me and Claude will probably get it before I work. Mm-hmm. Right? You’re just like, for booking a flight, tell Claude how to book a flight the same way we tell him somewhere.

I just started working here today. But combine that with a very like, personal thing. Um, maybe we’ll stick with a booking a flight example. I don’t actually think. AI should be booking flights. I think the tools we have is yes.

swyx: Yeah. Finally, somebody says it. It’s the default demo that everyone’s making.

Felix: I’m

swyx: like, I even against like booking demos, it is not a good showcase.

Felix: Yeah. I’m like, I just wanna book my flight myself. But, um, I think there’s a lot of things that have a personal and a non-personal component and that’s maybe why people reach for flight booking because some things are very universal. Yeah. Super flight is usually better, right? Like few people try to book the most expensive flight.

And then some things are quite personal about like what times you prefer, which seat you prefer, which airports you prefer. Combining that and like a skill format that is actually portable, compatible, easy to understand for people. I think that would be very exciting. We just haven’t figured it out yet.

Alessio: Yeah, I think the text part every, I think everybody by now has some sort of like cloud file thing. Either Dropbox, Google Drive, whatever. So it feels like in a way it should basically like sim link. My skills into all my agent harnesses. Yeah. Just keep those ing like we have internally this like valuable tokens repo, which is like all the commands sub agents.

It’s good. Uh, and then I build like a TUI where you can start it and be like, you know, install this command and this three sub agents into this agent in this folder and just copy paste this. It doesn’t do anything. It literally cp the file into that. But I feel like there should be something similar where like whenever I go into a new thing, it’s like, hey, here’s like the link to exactly the cloud folder and just bring down these skills into this.

Yeah. Like today it doesn’t quite work like that. Like if I install a new agent, I cannot, I have to like copy paste all the skills and I don’t even know where they are.

Felix: Yeah.

Alessio: That’s like the big problem. It’s like where do I find them?

Felix: Yeah.

Alessio: Um, so I’m curious like in the future like that, that almost feels like my personal productivity thing will be my skills.

Felix: Yeah.

Alessio: Is not really the product that I use. Everybody has access to the same product. But today there’s, that just looks like copy pasting ME files, I

Felix: think so many things I, I really like thinking about agents and LLMs just as like another coworker. So many attempts have made to build documentation companies that are like, oh, we’re gonna solve oil documentation problems.

Um, I myself, like spend a little bit of time working in notion, right? I’m like deeply familiar with the concept of let’s get everyone on the same page. Mm-hmm. Right? And what you’re basically saying here is you want all your agents to be on the same page about your preferences, about the skills, about the way they ought to work and like how they ought to execute.

And I’m not sure what the right thing is going to be if it’s going to be some, some company that can say, all right, we’re as an independent body, we’re not trying to like, push into any particular product. It’s our job to be like the skill authority, and we provide, I don’t know, we’re gonna be the Dropbox of skills and we can just sim link us into all the products we want to use.

I’m not sure that’s gonna be viable business, but as, as an idea, it would be cool.

Alessio: Yeah. Yeah. I think so many things are just going away as businesses. It’s like, how am I supposed to do it? I’m not even asking somebody to make a product about it. Like yeah. I wanna personally know. And there’s things like you said, it’s like you almost wanna skill and then interpolate it between personal and work.

So if I’m booking a fly for work, it’s different than I’m booking a flight personally.

Felix: Yeah.

Alessio: In some ways, yeah. But like a lot of the scaffolding is the same, you know? Cool.

Felix: I mean, as an engineer I will tell you like, you know, technic a person to technic a person. I will just be like siblings.

Alessio: Well that’s what, that’s what I do.

We call that MD and agents that MD’s just the same how sim length. And so it is like, that works, but it feels like, yeah, I don’t know. Maybe

Felix: you can always go one, you can always tell cowork problem and then cowork will solve it for you. Just make the siblings. That’s like one way to do it.

Alessio: That’s true.

That’s true. All right. Everything is called cowork.

Felix: Uh, potentially spicy. Question for both of you.

swyx: Uh, which of these industries will go away?

Alessio: Okay, so what Felix was saying before is interesting. There’s busy like. The short term pressure of like, we need to turn these tokens into valuable things, which is I should build the last mile product that harness the model.

And then there’s the question of like, long term, which ones are gonna still be valuable? And I think you’re kind of seeing this today with like, uh, you know, the coding space in a way is kind of like everybody’s moving up and up in stack because you need more than just turning tokens into code. I think search, like enterprise search is kind of saying the same thing.

Like with G Clean and like all these different companies is like, at the end of the day, if Cowork is the one doing all the work, the search itself is like such a small part that like, I don’t know if I’m really gonna pay that much money just to do search. It’s almost like everything is like a cowork vertical.

So like how much can cowork first party support?

swyx: Mm-hmm.

Alessio: And how much can it not? I think for a lot of these things, the planning thing that you were showing do Which one? The planning. The planning.

swyx: Okay. Yeah. Yeah.

Alessio: That’s one thing where like most of the value that these agents provide is like they’re better at planning for specific tasks.

Yeah. And have better tools for it.

swyx: Yeah.

Alessio: But I think the models are now moving in that direction and they have the right harnesses and they’re on your computer. So for me it’s almost like if for the end customer trusts your startup to be the provider of that task result, then I think that works. This is, uh, something that, this is a short

swyx: spike that we’re, we’re working on.

Uh, yeah.

Felix: I think, look, I’ll, I’ll, I’ll tell you this, like I don’t think I’m the best person to like actually estimate which industry is going to be hit the hardest. But I do think that at philanthropic as a group of people, we’re deeply worried about the impact. That the tools are going to have on the labor market, especially for like junior employees that, because I think, I think it’s only honest to say that when we talk about automating a lot away, a lot of the work that we personally find annoying that we maybe think’s not the best use of our time.

In a lot of industries, that kind of work would’ve been given to a junior entry level employee. Yeah. Right. And I think it’s, it’s only, it’s only right to be really worried about that and like worry what that’s going to do in particular to people like enter the shop market.

Alessio: Mm-hmm. I have a solution for that.

Which you make them, you create simulative jobs for them.

Felix: Okay.

Alessio: So this is, this is like half joke, half true. So if you think about software engineering, when you’re like a junior engineer, you work like 1, 2, 3 years. And in those three years there’s like maybe like a handful of moments where like you really learn something.

And then a bunch of other days where like you’re not really progressing.

Felix: Yeah.

Alessio: I think now we can use AI and these models to actually like shortcut these careers and almost like simulate the early years of your work and like just make them like super dense and like these learnings, it’s like, hey, we’re working on this feature, which is like a distributed system and you need to learn this thing that might take three months at a company.

And so you take three months here, it’s like we’re just simulating the whole thing. It’s actually not a real thing. And in one week we kind of speed run through the whole thing and you kind of learn your lesson from there. And we kind of repeat that in like one year. You basically get like three years worth of like projects and experience.

Yeah. I think it’s harder for like things like sales or for things like, you know, marketing because you don’t really have a way to get the feedback loop. But I think a lot of it, it sounds kind of silly, it’s like you’re making the new effect job, but it’s almost like you go to college, right? People pay to learn how to do it, and this might feel similar where it’s like, hey, we have the.

Jane Street Simulator is like, you wanna come work at Jane Street? We’ll just put you in the simulator for like three months.

Felix: Wow.

Alessio: And you’ll come out of it. It’s like, you know, I’m ready.

Felix: So there, there is an aspect here. I’m not an expert enough to like actually know what, what is going to happen to marketing or legal or finance, right?

Like, I don’t work in those jobs and I, I don’t think I should talk about them, but I am an engineer and I think I have a pretty good idea of what engineering is like. And I think one thing we’re sort of seeing is that as a company and also as, as the public, we’re like deeply worried about entry level, but we’re also seeing more senior engineers accelerate it.

If like they’re more productive. They, they actually increase the value they provide. And the thing that I’m thinking about a lot is the fact that even before all of this happened, um, I’ve always had a lot of respect for the University of Waterloo and the, the new grads that have joined my teams as from coming from the University of Waterloo always felt like.

More ready than new grads will like literally spend their entire time at the university regardless of how good, but never actually had to work inside an environment where you have to ship things that eventually will be used by users. And I’m, I’m, I’m German. I like initially went to German University and I think the, the, the like information systems programs, there tend to be very theoretical, right?

Like I often give people the example of like trying to become a doctor, but you first have to do four years of biology and as a result when you get a new grad, you sort of have to teach them what it’s like to actually build products and to work in a company and like work with other people. And like some people will have different opinion and like, how do you do all of those things?

And the University of Ulu, it seems like they just. Spend half of their time. I dunno if it’s true, but I think it’s, it’s a year, right? They spend so much time,

swyx: part of your job, uh, a cu a curriculum to do spend a year in internships.

Felix: Yeah. They just like go from company to company. They show up on your team as like a junior engineer who spend like 20 companies.

Not really, but like, it seems like a lot of my new grads have also briefly worked at Apple, Google, Tesla. Yes. And uh, there’s a common meme where they like collect all these logos, like infinity stones, but, and they always put it on LinkedIn and it is very unclear that they’re an intern. Like Yeah, yeah, exactly.

But it does actually make them so much better compared to other new grads. And I wonder if that’s a useful model maybe for the future when we also have to like, crunch down the amount of time you have as a junior employee. ‘cause the value you have as a junior employee is going to like, be impacted.

swyx: My sort of pro young people take is that they’re, you’re more, uh, you have higher neuroplasticity, you can learn more, you have less preexisting biases.

And, uh, what I is assuming is true for you, what OpenAI often says is that. Actually it’s the, the younger, like fresh grad engineers that use Codex or their coding stuff, uh, more innovatively than the, uh, experienced engineers who have a set and preferred way of doing things.

Felix: Yeah. As I talk to people, I, I someone experience.

swyx: Yeah. So maybe you’re more AI native. Yeah. And therefore you’re, you, you get cut. But like, I think the problem is you don’t need that many of them.

Felix: I mean, philanthropic is on the record as saying we do believe that the impact on the market is going to be sizable and we do not think that people overall are ready.

Right. And we do actually think we should probably talk about it as a society much more. Yeah. I’m not sure that I’m like the individual that can add like anything useful there. But I think as societies with economists and, and governments that need to wrestle those questions in a way that is probably more meaningful than me wrestling with them, we’re probably not doing good enough.

swyx: Well, we, we’ll try to educate and then I think also just releasing frequently as, as, as you guys do, or probably maybe too frequently

Felix: Yeah.

swyx: Uh, is helping people to adjust over time. Right. Rather than one big bang thing. There’s like sort of this gradual takeoff that people are living through that we

Felix: Yeah.

swyx: Waking people up. Right.

Felix: Yeah. And I, but I think a lot of us like wondering at what point do we actually have full takeoff, right? Like at what point is there, we’re all sort of expecting this like big bang moment where things will accelerate so quickly that it becomes a self-reinforcing loop.

swyx: Mm-hmm.

Felix: And at that point, it’s sort of like off to the races and there will be no more like slowly catching up.

You notice just have cloud being so good at everything.

swyx: Yeah. It’s when cowork is training models, it’s when it’s looking at tensor board and Exactly. Weight and biases and training things.

Felix: I like we can all debate like how many years it’s away, right? Like some people make a better route, like maybe it’s 10 years away, maybe it’s a year away.

Um, I’m not entirely sure where, where I come on this time, but I’m not totally sure that ultimately it matters all that much, whether or not it happens in four or five years. If we have a decent one, certainly that’s going to happen. It’s probably something we should wrestle with.

swyx: I wanted to talk, so by the way, the, the scheduled task complete, uh, the, the, there’s the clean my desktop task complete and it did it organized by file type, which, okay.

But, you know, I was trying to get it to do more sort of thematic, like read the file, understand what it’s about, group by, uh, the, the topic rather than the file type. But

Felix: I mean, you can just follow up and have it do that. Oh yeah. Here, like it did, it is proposing That’s right.

swyx: Yeah. So it’s, it’s got some like topical things, but uh, yeah, I could probably do better.

Like, yeah, so like I probably need to give it a skill to read video files so that it understands here’s how I like to,

Felix: honestly though, like, um, I see that you’re using Opus 4.6, right? Like my recommendation for people is increasingly don’t worry about it anymore. Just like tell it what you want it to do.

swyx: Yeah.

Felix: And it’s probably gonna figure out a way to do it. It might not be the way that you like necessarily or the way that you’ve gone about it.

swyx: Videos, deeper,

Alessio: lower outsourcing, organizing all of this. So let’s fight. Yeah. Yeah.

Felix: I’m honestly like, so curious what cloud is gonna come up with.

swyx: I’ll kick that off.

I wanted to also just talk about the, the overall, uh, you know, you talk about data analysis, you talk about like, uh, your, your personal finances. You also said, uh, which by the way for us is very timely tax season, right? Like Yeah. Use cloud core for tax season. It is not responsible for any mistakes, but might as well, right?

Like it’s, it’s free knowledge work for you. Yeah. Uh, so I just like, I think cloud for finance is a big deal. Um, and this is definitely like in that mix. I wonder, is it like, do you, is it a separate team? Do you talk to them? How important is it? Right. Like, because you can also natively output Excel files now.

Felix: Yeah.

swyx: Just

Felix: talk about the

swyx: finance effort

Felix: grow. Yeah. We care about the verticals quite a bit. So we do have a dedicated verticals team. We have a dedicated enterprise team,

swyx: and those is business engineering, not sales.

Felix: It’s engineering. Yeah, yeah, yeah. It’s engineering. So we do have people who sort of come to work every single day and they, they ask themselves, how do we make co-work extremely effective for people in those specific industries?

How do we make it easier for them to understand, how do we make it easier for them to plug into this and like sort of get the same value out of it that software engineers get? I think it’s no real surprise that software engineers ended up being sort of at the forefront of the entire AI moment because so much of it is this like Rub Goldberg machine nest where like we’re already used to automating things, right?

Like it’s part of our job. Yeah. So we care about it quite a bit. I think it also like really matches what we see. Cloud being very good and as a model, I think it provides tremendous amount of value to those customers in particular because. We can do so much with the amount of data they have. Those are like data heavy industries.

Their industries for correctness matters quite a bit.

swyx: So for us of, I’ve used it to analyze my business, I just can’t show it. So

Felix: it’s two sense. I had a similar question about, about taxes. Like, I did tweet, I did tweet about the fact, I did tweet about, oh, COVID is doing my taxes. This is honestly incredible.

And, um, it’s like annoying. He is like, this is so cool, but I’m not gonna, Twitter is maybe not the audience that needs to like see my tax return.

swyx: Yeah. That way. Here, here it is. It’s it’s reading on the videos, so it’s like Yeah, it’s getting more, yeah.

Felix: How did it actually do it? I’m actually curious.

swyx: Oh, usually it just like, takes a screenshot and then it reads the screenshot vi by vision.

So this is what I do for my, my Zoom upload thing, right? Because I, I have paper club sessions that I need to upload to Zoom and I want it to automatically. Uh, title them and do show notes and everything. So it just take screenshots and try to try its best. Yeah. It wouldn’t probably benefit from transcribing, which it’s doing by, it’s operating by Pure Vision now, but it’s good enough.

Felix: Yeah.

swyx: And then I, uh, I do have to call, uh, out to Nano Banana to do images. So unless you guys do images for me, uh, I have to call other people your images.

Felix: We’re aware. We’re aware. It’s, it’s just like so fun for me because like, this is the thing that I’m increasingly doing, like increasingly curious about cloud’s, creativity and like figuring out what is great Claude’s approach is like some problem.

swyx: Yeah. Vision for everything is, is like the, the superpower, right? Like, you know, and computer use, you guys were the first to do computer use, right. And when it was launched, I was very unimpressed. I was like, it’s slow, it’s unreliable, it’s wild. How much better? ‘cause it is one year ago.

Felix: Yeah, I know. Like it was barely usable.

Yeah. I, I remember it was very usable, but is it wild how much better things have gotten? Yeah.

swyx: Yeah.

Felix: Over that one year

swyx: we went to the anthropic office because you, uh, for the launch event for computer use. Like there was like this hackathon. Yeah. And like nobody hack on computer use.

Felix: But I did see, I, I I don’t know if you’re okay with me saying that, but I did see briefly that you do have like a, like an automate Mac, SMCB server installed.

Right. Uhhuh, you use that ever.

swyx: What? Sorry? Which one? Where?

Felix: Um, if you go to your settings.

swyx: Oh, settings. Okay. Uh, where, sorry, this one?

Felix: Yeah.

swyx: Yeah.

Felix: Um, I noticed that in your connectors,

swyx: Uhhuh. Uh, I probably said it at one time, but I don’t use it actively.

Felix: Oh, okay. The

swyx: a max automated. Yeah. Yeah. So, so I, yeah, this one I really wanted to like, just automate everything in my thing.

I didn’t find, I didn’t find it super reliable.

Felix: Okay.

swyx: Why?

Felix: No, no, no question at all.

swyx: Cloud is much better writing Apple Script and executing its own Apple Script than relying on these, uh, third party tools.

Felix: Yeah.

swyx: Uh, so I’ve increased, I, I initially installed Im CP and like all these other fcps that people built, and, but now I don’t use any of them anymore.

Like just, just let cloud write its own thing.

Felix: Yeah. It’s

swyx: gonna be more custom made. We keep going up the stack,

Felix: but if using computer uses like a fairly interesting area to me, and it’s like also interesting in the sense that I don’t think we’re far away from, I don’t think we’re far away from clapping, very effective, but like using your computer and not just it’s theoretical computer.

Alessio: Mm-hmm. What’s the relationship between the user and the computer? Like, uh, there, there were some tweets about how huge some of the VMs, the Claude Cowork creates ours, like 12, 15 gigabytes and people complain. Yeah. But at some point it’s like, if you’re using the computer, you’re taking action on, it’s, it’s just your computer.

And I’m just looking at it, you know, it’s like, I, I think that’s why people like the idea of like the Mac mini and the open claw or whatever on it because it’s like, it got its own home. You know? It is doing its thing, I’m doing my thing. I think there’s some kind of like, not like risk condition, but it’s like, okay, if I kickstart this task now I can’t really use the computer.

Felix: Yeah.

Alessio: You know, because car coworkers doing things on it and it’s kind of awkward, like, yeah. I’m not sure.

Felix: I, I do think it’s a super interesting area because I, I can maybe tell you like some of the things I thought about that I think are actually a bad idea. So when, when we initially started working on cowork, I, I did have some dreams about, well, would it look like for cloud of its own cursor?

Could be cool, right? Like it’s a computer, we can write code, we can touch everything. Like who says that computers need to have one cursor? We could do a second cursor, but that actually breaks down quite a bit. Even if you go and like present cool dreams to both Apple and Microsoft, you’re like, wouldn’t it be cool if, um, it breaks down quite a bit?

‘cause so many of our models on a computer are built around this idea of like, there’s only one thing working on it. Yeah, there’s like a foreground app, a background app, cloud and Chrome can work in the background, but that’s like within one application. But the operating system layer, that is a lot harder to implement.

So I’m, I’m still grappling with what, what does it mean for cloud to actually act on your computer. It’s the right format for cloud to have its own computer that you set up. And maybe every now and then you like zoom in and you play with it. Or is the right format for Claude to just like, wait until you are.

Stepping away for a little bit and take over while you’re gone. Or it’s the right move for cloud. Just like if it’s on computer in the cloud, and like whatever you want cloud to do, you have to set up yourself. Right. There’s like a, there’s like a number of different options. Um, this is the thing I think about a lot, like what is the relationship between you and your computer and you and your data on their computer?

Because how intimate that relationship is kind of depends on the tool and Right. The thing that you’re current looking at, right? Like we’re quite comfortable sharing some things, very uncomfortable, sharing other things. And I think whatever product is gonna be successful, we’ll have to deal with those, like, with those different things.

But you probably, even if Claude was capable of making a determination, would you want Claude to make that determination in the first place? It’s tricky, Barry, because it’s like, it’s more than just privacy. It’s like almost intimacy and it’s like tricky to reason about in a way that will make everyone comfortable.

Alessio: Yeah, I could see. You know, a virtual box, like actual virtual box app where like you run the VM and then you have like a screen within the screen, you know, you can put it in the background, but then you can like jump in the screen and like you,

Felix: that’s not a bad idea. Yeah.

Alessio: You know, like, I mean I used it, you know, people used to do it virtualizing like C Linux in a Windows machine.

Felix: Yeah.

Alessio: And like you would just jump in and then you would jump out. But it’s like, it’s not like a dual boot. It’s like within the thing. The problem is that you need twice the amount of ram, twice the amount of, you know, it’s like, it’s kind of taxing on the machine. But I think that would be cool. Kinda like see, you know, the little quad window.

I can see desktop look cute. It is clicking around things

swyx: I was gonna bring up. He’s the original machine and the machine guy, because he has the uh, windows. Windows 95 project. Where’s, where’s the Windows 85 project at?

Felix: It’s probably somewhere in my GI guitar,

swyx: right? No, no, no, no, no. It is like the first thing you see is this one.

Nice. Yeah,

Felix: yeah,

swyx: exactly.

Felix: That was honestly a very fun project though. Like, obviously I didn’t, I, I should say this, just so that No, it’s the wrong impression. I did not write the actual, the actual, obviously I didn’t build Windows only five because I was a child, but also I did not build the actual engine that is capable of like simulating an X 86 processor and JavaScript and m um, that’s a tool called V 86, which is very cool and everyone should try.

But this came out of a, this came out of like a debate we had at work where people were like, they often are in the into debating the merits of electron and whether or not we should be building software in JavaScript, yes or no. And I still am very upset that I can run all of Windows 95 in JavaScript.

And launch Microsoft Excel inside the virtualized JavaScript Windows only five machine, and do things that pro, I can do that entire chain faster than I can do a lot of other things in like traditional SaaS applications. Mm-hmm. Uh, this is sort of like a, like a performance rampage that I went on. So I’m mostly built this as a joke for some of my colleagues at Slack.

This took, took like one night. Um, what, but then that I, it was, it was not hard to do. It was all the hard work is in V 86. Yeah. Like if, go to the repo, it’s gonna say like, 99% of his work is done by, by um, a guy who goes after the, by the name. Copy. His name is Fabian.

swyx: Yeah.

Felix: Um,

swyx: cool. I think you’re, you’re kind of back on the Windows grind ‘cause you’re building out the Windows support.

Uh, I thought there was some really cool technical stories to tell. Uh, and it gives people an appreciation of like, well here’s how hard it is and here’s how important here, how, how you invested the sandbox. So maybe this is like a good opportunity to talk about something in the details.

Felix: Oh yeah, the, the VM honestly is like so cool.

There’s a lot of things we dislike about the vm, right? Like there, there’s a lot of things that are real trade offs and you want to know why you making those trade offs. Um, and you’re right, like a lot of people write me like, Hey, how, how come cloud is taking up 10 gigabytes? I could say on the point, it’s not actually taking up 10 gigabytes.

It’s just like a way that macros displays bites is like wrong, but the way we actually ride it to disc is by we collapse the empty space and the image, so it’s not actually taking up 10 gigs. But that’s a technical differentiation. That’s probably not gonna matter to, like,

swyx: to me, the the, the outcome is it takes too long to start.

Yeah. It’s like 30 seconds sometimes. So I don’t know. Oh, it should be faster than that. Whatever it be te about this feels like 30.

Felix: Yeah. Like even either way, like whatever it is, it’s going to be, it’s going to be slower than just running Log Ultra on your computer. Right. So the trade offs are real, but what we’re doing on Windows, we’re using the Windows, windows, uh, host compute system.

It’s the same thing that WSL two runs on, like the Windows subsystem for Linux that I think a lot of developers appreciate quite a bit. Yeah. Um, and it’s, it’s pretty cool because we sort of like have to separate out which system space the virtual machine runs in, in who gets to talk the virtual machine because obviously you give this virtual machine a decent amount of power.

How do we optimize not just the connection between the two systems, but also how do we make sure that random other application doesn’t get to talk to Clot inside the vm?

swyx: Hmm.

Felix: We do some pretty interesting things. Um, last week we started writing a new networking service. A networking driver. That optimizes how Claw talks to the internet.

If your company’s doing like weird internet things like pack inspection and like, like, you know, taking your part as a cell and inside your company, I think there was probably like a very small, easy version to build of cowork that is much simpler but also breaks on most com most users, computers. And this one is quite nice because it works on most users computers.

Um, and the default example I always go for is I, I really want this to be highly effective on like a, on like a machine that most people pick up. And that machine will probably not have Python, it will not have no j And even if I just take away those two things, cloud is going to be so much less effective from

swyx: your computer.

So what do you do? You don’t even, I mean, may maybe require people to install Node in Python.

Felix: Oh, like, you mean for like a, what does the feature look like without a vm?

swyx: No, no, no. So, so like, like you said, right? Let’s say a target machine is whatever’s a default spec, windows laptop.

Felix: We do this, which is quite cool.

So on, on, uh, mes, we use the, um, apple virtualization framework, which is pretty solid, optimized, like it’s good stuff, and instead simple a p call, right?

swyx: It’s

Felix: like super simple.

swyx: I, I saw the code recently and I’m like, that’s it. What the f**k

Felix: would you, once you start like shipping production code on it, you start adding like all of these edge cases, your new

swyx: Oh

Felix: yeah, it ends up being a little longer, but, um, I think Apple really cooked with a virtualization framework and it’s very, very good.

It is very fast, it’s very reliable. And same on Windows. The, the host compute system. I think WSL two as well is maybe one of the diamonds within Windows. It’s like one of the few things that developers universally rave about is very, very cool. And like hooking into the same subsystem makes a lot easier for us to say We don’t really care how locked down your computer is.

Maybe it’s like your employer’s computer and your employer has decided that you get to install nothing.

Alessio: Mm-hmm.

Felix: Not trusted, but it’s true in a lot of environments, right? Like even at Anthropic, um, our IT department controls what kinda stuff you install, just like a pretty common experience for many companies.

Um, and this gives it departments a decent amount of, like, it makes their job so much easier because we can say you can separate out cloud’s computer from the user’s computer. And then for cloud’s computer, where you probably care about its data loss, you care about like a potentially hostile actor, you care about maybe data being exfiltrated.

And once you control the network and the file system layer, you don’t really care necessarily anymore. That cloud might be writing super useful Python scripts. What worries you about the fact is that like once you install Python, now anyone can do anything on a computer. Once you put that in the vm, that risk really goes down.

swyx: Yeah.

Felix: So that’s why we jumped through all of these hoops.

swyx: Yeah. I think you, you had a different, uh, tweet about this. Um, but it, it’s, it’s almost like people have also approved exhaustion. Like, it’s like you can’t approve every single commands. Like sometimes by, by default, some of the theis, I think even early called code, uh, we have to approve every single command.

Yeah. And, and like it’s so, so there’s this sort of dichotomy between either approve every step or dangerously get permissions.

Felix: Yeah.

swyx: And actually sandboxing is like, kind of like the middle ground.

Felix: Yeah. I do think, I do think it, it’s maybe on us as like the AI industry to come up something better than, oh, this is super safe as long as it doesn’t do anything right.

Right. But if you want this to be useful, then you have to like approve every single step of the way. And like, computer use is a good example. The only way to make computer use on your host, like super safe, like really super safe is probably if you approve every single action, right. Like models, like, I would like to type the word.

You’re like, okay, that seems fine. I know, I know. Which, like cursor is focused. Yeah. It’s not

swyx: automation if you don’t delegate.

Felix: Yeah, exactly. You need to like properly delegate. You need to be able to like delegate and walk away and trust that this thing is not gonna like mess dramatically. And I don’t even think we need to build perfect systems.

I don’t think we need to wait for like a hundred percent model alignment. We can rely on the same Swiss cheese model we’ve used in the industry for a long time. But I do think we need to like universally maybe eventually invest more. And that’s what we’re doing. We need to invest more in systems where we can say, you do not need to approve everything.

swyx: Speaking of Swiss cheese model, he just wrote a thing about this.

Felix: Oh cool.

swyx: Yeah. Uh, yeah. Um, yeah. Super cool. I mean, yeah, it’s, it’s weird how like, I guess usually I think safety and security is kind of like a boring word to, to engineers. They’re like, just gimme be unsafe, gimme unsecure. But, um, I think.

Achieving the right thing. Like you are going after a consumer slash prosumer.

Felix: Yeah. Yeah. Talking both kind of like both. I think I, I also want to capture people who would’ve no trouble using clock code like yourself, right?

swyx: Yeah. Yeah.

Felix: But still find it maybe just convenient, easier. You’re like, oh cool.

That’s like the list on the right. I can edit it. Those things are just easier to do if you have

swyx: to. But this is like clearly the knowledge work side. Yeah. Claude Code will clearly capture the development workflow. But like I, I, I do think like you have to sweat this like safety and security details in order for people to trust it.

And like the even Claude and Chrome, like having the whatever API uses to do the background thing.

Felix: Yeah.

swyx: Um, that’s the only reason I use it is because otherwise I would have to just get a separate machine.

Felix: Yeah.

swyx: And just run it, run to the, and that sounds like

Felix: super annoying.

swyx: Yeah. I mean, like currently doing it, but,

Felix: and I think, I think also as developers, um, maybe we’re, we are more risk tolerant, but we’re also just like accepting we are more risk tolerant, but I think we also just have.

I don’t wanna say arrogance, but like sort of the trust that if like the really bad thing happens, we can probably fix it.

swyx: I just tell Claude to like, check with me before doing any irreversible action. Like sending an email or doing permanently. Yeah, it’s good enough.

Felix: But like, not even Claude, I mean like simple things such as NPM install, right?

Like we’re all running NPM install with full user permissions and if it wants to like read SSH, it well crazy that that is the default kind of why. Yeah, I know. I agree. I agree. Fine. Like I’m obviously doing it every single day. No, right. Like, uh, and I think obviously NPM and GitHub too have like done a pretty good job maybe over the last couple months to like clean house and come up with like more specific tokens.

But generally speaking, I think as engineers we’ve always been a little bit more risk tolerant. And if you do a little bit of introspection and you ask yourself, is that how we should be doing things, you might not always come up with the right answer. And I think for models too, like my approach, like I’m not gonna, the the safest thing is to do nothing.

We do want products that are quite capable, but to the extent possible, I don’t wanna ask you, are you okay with the script? Because I kind of believe that once it starts becoming a part of your workflow, you’re probably not either, either you don’t have the skill to understand whether or not the python, the script is safe or you’re not gonna read it anyway.

swyx: Cool. I guess a, a couple partying questions. Uh, what’s the future of clockwork?

Felix: I think we’re still, we’re still such early days. We’re gonna keep shipping things that we’re gonna keep shipping, things that, um, we’re gonna keep iterating on this thing like pretty quickly, but, which I mean, you can sort of continue to expect that every single week there’s gonna be like a small new feature, if not a big new feature.

Um, I’m going to continue probably to double down on your computer and like making you effective in your computer and making cloud effective in your computer. Um, we’re starting to grapple, as we talked about today, grapple more with a question of like, what does it mean? What does your computer mean? Does it have to be the one in front of you or like a VM on your computer or like a computer somewhere else?

And then the third thing that I’m quite excited about is. We’re continuing to go off this hill climbing on slowly taking users who are used to asking questions and getting an answer to slowly teaching them to like step more and more away. And that claw take over like bigger and bigger tasks and work both in time as well as in like scope.

And I think you can probably see most of the, our investments on our feature releases to like work on both of those things, like the ability to do more on your computer and then the ability to do more independently for longer.

swyx: Does remote control work for Claude Cowork yet? No. Right.

Felix: Excellent question.

swyx: Coming soon. I mean, that’s an obvious thing if you want to keep betting on the, on your computer, but I, to me like. You know, we, we talk about like, people are not ready this year. Like the, there’s, there’s no wall. It’s, it’s accelerating to me like what will be we be doing differently at the end of this year that, you know, we are maybe not even thinking about this, uh, at the start of this year.

Right. Like, I’m just trying to look ahead as to like, what, what’s like a good use case that you’re, that we sort of aim towards? So for, for example, for the machine learning scientists, it’s always, okay, well I want AI scientists, I can automate, automate machine learning, but like for, for knowledge work, I mean, I can already, you know, get it to sign up for Google Cloud to mean as a GI.

Felix: Yeah. ‘

swyx: cause Google cuts are, but like, what, what is, what’s beyond that? I don’t know.

Felix: I think it’s basically the idea that like you still had to tell her to build your script, right? He was still kind of involved.

swyx: Yes.

Felix: In maybe a way that felt kind of magical to you, but like, maybe to me on the other side is the person building this product still feels kind of heavy handed.

I see so much process that I’m like, oh, lemme take that away from you. Okay. But like, how do I just go, I will continues to go or continue to go like further and further up the stack. Make your life easier and easier.

swyx: Oh, here’s one. Right?

Felix: Yeah.

swyx: Watch, uh, I, you know, I don’t care about my own privacy or whatever, or I trust cloud, I trust philanthropic.

So just watch everything I do on a normal day-to-day basis. At the end of the day, tell me what you is called co workable.

Felix: Yeah. I

swyx: dunno.

Felix: I think the funny thing about a lot of these products is that like, for good reason, I don’t enjoy, I, I don’t, throughout my entire career, I’ve never like teased too much what I’m working on because I think you should just like, yeah.

Release it. Yeah. Build the base and release it, and then talk about it. Like I’m, I’m not a big fan of the like vague posting my own work ahead of time.

swyx: Yeah.

Felix: But the thing that is like always so fascinating to me is like, both of you all multiple times a day, you’ve like mentioned things and I’m like, yeah, that is obviously like very obvious

swyx: Okay.

Felix: That someone should be working on those things. Um, and I think we’re still in the space where if you look at cowork. The things that we will be releasing will probably not be a big surprise to either of you. You’re gonna be like, yeah, obviously that’s valuable obviously that we’re working on those things.

swyx: Yeah.

Yeah.

Felix: And obviously that’s good and useful. And the more I hit those points, the more our features fit into that category, I think the better it is for us because then we don’t end up building things that are too hyper specialized to difficult harness style.

swyx: Yeah. I think the hyper specialized thing is very important.

It keeps you like general purpose. It, it means you’re not thinking too small. Maybe I don’t, I don’t know what the, the word is.

Felix: Yeah, yeah, exactly. It’s like the whole concept that like at no point if we release, you know, there’s no Claude Code for no jazz applications that use React and 10 Stack. I know any of those two things.

And like if it’s anything else, I know several startups like that. I think that’s pretty, like, I’m not a vc, I’m not an investor. It’s like hard for me to predict where the markets go. But in terms of the building box that I’m interested in, the electron is probably by far the most popular thing I ever built.

And, um, electron itself is like. Very abstractable and generalizable. Right? Like so many apps run in it. And I think it would’ve been hard for me to predict how many apps actually end up using Electron.

swyx: Yeah.

Felix: Um, and what would’ve been even less useful for me to predict this in what those apps do. I distinctly remember a bloom coming out of being like, that is cool.

Like you are a camera in a little circle in the corner. That is pretty smart.

swyx: That’s an app. Yeah. Yeah.

Felix: Or at least was, I’m not sure if it still is. It was for a while. Or like one password has so many interesting things. Right. It, it’s, it’s, it’s a level of the stack that I’m quite comfortable with. And whenever I give other engineers, advisors actually that layer that I think is most valuable to invest in because the tools of that layer are not that good.

But that’s where you get the most leverage

swyx: for like,

Felix: the future in general.

swyx: Just quick tangent on Electron. ‘cause I always wonder this, uh, have you looked at Tori?

Felix: I have, yeah.

swyx: What’s your take? Uh, you know, look, my, my my, my view is like most things should be Tori by default, unless you really need the full power of electron, but.

Felix: Yeah, I can give like my take on, I can give my big take. Why do we ship an entire version of chromium inside the thing, right? Like why do we do that? And, um, people ask me this question a lot because it’s like very counterintuitive. Wouldn’t it be much easier to use the web use that are on the operating system?

Wouldn’t it be much easier not to have to do that? And the answer is yes. And like obviously I did that once upon a time. I did that there was a version of the Slack app that used just the operating system that use Wait, did you, did you start the Slack app? I would, well, team effort and

swyx: Yeah, but I was, I was there.

We built the Slack app.

Felix: Yeah. It’s crazy. Um, I mean obviously you get the electron guy to do it, but, well, but this is an interesting point. Like, by the time, by the time I joined Slack, they already had an app that was built with something at the time called Met Gap. It was a little bit like the same app gap thing for mobile.

It just used the operating systems. Web views. Um, and that didn’t work for like so many reasons. Um, and they were like, all right, maybe we need like bigger guns. We need to like take more control of the rendering stack. And there’s, there’s a few things I always mention here. Um, I think if you’re building a small app, just going with the operating systems web view is perfectly fine.

If you’re building an app, maybe that doesn’t have too many users who will like cry bloody murder. If it doesn’t work, that is fine. The reason to go with your own embedded rendering engine is because, and this is still true in 2026, the operating system render engines are not that good. They’re just not that good.

Both Microsoft and Apple are trying to move away from that. They so far really haven’t, the only way to upgrade those is to upgrade your operating system. So if you are, say Slack and you have critical rendering bug in WK WebU and some of the other WebU options, your only recourse is to tell your customer, oh, sorry, you’re too poor.

You didn’t bother the, its MacBook. Unacceptable.

swyx: Mm-hmm.

Felix: Unacceptable to user, unacceptable to user developer. So you sort of need to like go down the stack and like find the best rendering engine, then put it in your app. Why chromium, even though it’s very big chromium is by far the best thing. Like I, I often like to remind people the unreal engine, you wanna render some text.

They use chromium. Like chromium is part of the unreal engine for same purposes. Chromium is very, very good. I think it’s like one of the marvels of engineering. It’s very hard for, we’re in San Francisco right now where we’re recording. Most of the people in the city are web developers. It’s hard for me to like overstate how magical it is.

They run seat like rendering a YouTube video dynamically. Negotiating a bit rate, figuring out what to do about your extremely broken hardware driver. Actually, this is a fun thing. Um, okay, you can enter Chrome call on Wack Wack GPU. Okay? And if you scroll down a little bit, these are all the enabled workarounds because something is going wrong on your computer.

If you’re doing this on a Windows computer with like A GPU, that is not the most popular GPO, it will be much longer. And all of these are usually just there to make sure that if I say as a developer, I want a red pixel to appear here, that that actually happens. Chrome is such a marvel because of works on all the machines that user might throw you and it’s gonna work fairly reliably.

And if it doesn’t, they will probably fix it within 24 hours.

swyx: I see. So this is the super operating system, right? That that works everywhere.

Felix: Yeah.

swyx: Right. Okay. Yeah.

Felix: So a lot of the magic of Electron is honestly just that it makes it very easy for you to ch chromium in a way that serves you exactly in your use cases.

Elect, uh, exactly.

swyx: Our next interview is with Morgan Dreesen.

Felix: Yeah.

swyx: Who had the phrase like, desktop OSS are just poorly deep, uh, poor implications of the, the actual os, which is Chrome, which like actually works everywhere. And this is this, this is the platform where you ship apps.

Felix: I, I think the wild thing is that like as engineers, we so often sort of assume that the platform, like the layer below us is like super stable.

Mm-hmm. And then you talk to those people and they’re like, ah, we are also just like guessing. Um, uh, and I had like a distinct moment at Slack where one of our customers at Slack was Nvidia, and for a while I really put GPU developers on this pedestal in my head. And I do think they’re still probably much smarter than I am.

But I was like hardware engineers who built the chips, who then like built the drivers. Their work must be so much harder than mine. They must be very good. And we had like one bug in Slack where like if you had a YouTube video in Slack, it wouldn’t quite render why. Like it would have these weird artifacts.

And, um, that ended up being a chromium bug. And I ended up on this like giant thread. So I got to see a lot of the source code. And they also are just like common to do. We don’t know why this is weird, but if you flip this bit, things work. You know, this is just like happening with every layer of the stack.

Maybe the, uh, you know, the,

swyx: the end of year a GI prediction is that clock can build chromium. You see, you see you, you laugh now. But yeah, like, you know, someday

Felix: it’s, it’s sounding, it could get pretty good. Like it used to be completely useless. Um, mostly just like overwhelmed, both with how hyper specialized tools are inside the chromium repo.

Like for, for a long time. Chrome has like sort of reinvent all the tools because none of them are capable of ending Chrome. I think the EGI moment I am kind of waiting for is at what point are we gonna say Electron is probably no longer necessary because you can just build fully native apps. The Swifty?

Yeah. Like not just in Swift because this is one thing, like it’s pretty easy if you, I think our current models are quite capable of taking an electron app and replicating it Swift, are they gonna be capable of like building an app that is actually more performant, which is less memory? All of that stuff, um, is gonna go into the same hyper optimization that developers have done for like a long time.

We’re not quite there yet. Work and like point even our best models at a thing and say, just replicate this, a native code. Make no mistakes. Ultra think. Right? We’re not quite there yet. Um, ultra

swyx: think is bad

Felix: today. Think is back. Yes. Okay.

swyx: Or we’ll get an ultra think for like days,

Felix: just a pretty long time before,

swyx: but he worked on Ultra think for days.

Yeah. Why he just, it’s just. Front,

Alessio: I’ll let it, the

Felix: more goes into

swyx: it. Yeah. Okay.

Alessio: Another question I had is like coworks. So if I have my Claude Cowork, like what’s kinda like the multiplayer mode? I think sub agents is like single player Split up the context.

Felix: Yeah.

Alessio: And the multiplayer cowork is like, my colleague is some file on their machine that I wanna know about or I wanna know how their task is going to then update my thing.

Like is that interesting? Is that something that makes sense for you to build or for like

Felix: It’s like super interesting to me it, it almost goes back to like some of the scaffolding room. Like okay, are we gonna be end up, are we, will we end up building scaffolding that will just go away? And like a question I have here is at what point do we just assign these things, like their own Gmail account?

We just give them their like Slack handle and then they will just like use the same tools we humans use to interact with each other. You mentioned our finance people, they’ve been working pretty hard on very good office integrations. And I think for a while we’ve been like, we built so much tech around cloud, leaving useful comments inside a Google Doc, and now it just does, it just like leaves a comment in your Google Doc and that’s how you interact with it.

Maybe like the similar thing where I still have open questions around what is the best interaction mode? Is it for us to build something super custom for cowork agents to talk to each other? Or is it okay, let’s just jump straight to the finish line and say, well, we’re just gonna give this thing, if you use Slack at work, we’re just gonna give this thing a Slack handle.

And that’s going to be the way, it’s like multiplayer capable.

Alessio: They communicate with each other. Yeah. Yeah. Like, you know, as a, as a fun project, I build this thing called piq, which basically takes any repo and the PI agent, uh, coding agent, it puts it in a VPS, and then there’s a public web hook where anybody can submit a coding task.

Oh. And then there’s a dashboard in which you review the task and then piq pi, pi, uh, queue.

Yeah. You basically get all these like tasks, anybody can submit a task.

Felix: Mm-hmm.

Alessio: And to me it’s almost like in the organization of the future, it’s like the sales people are talking to the engineering team that is talking to the marketing team, to the product team, and all these coworker are going to like queue up decisions for other people to approve in a way.

Felix: Yeah.

Alessio: You know, and I’m kind of curious what that looks like and like how do you, how do I give my cowork the ability to build a proof task without asking me

Felix: Yeah.

Alessio: And how to decide which one I need to review. Yeah. You know, because for some of these things it’s like, you know, you wanna change the color of something that’s kinda like a branding decision.

Or another one is like, hey, your thing is just broken. It’s like, this is like how you fix it. Yeah. And Claude can actually review whether or not that prompt matches what he’s trying to do today. Everything is still very, it’s like multiplayer within the single player, you know? Yeah. I guess spin up many of them, but like, how do I get multiple people to hand off to each other things using their particular context?

Felix: Yeah. And for both of your coworkers to like talk to each other. Right,

Alessio: right. Yeah. Hey, we got an episode today. Can you like, have you, you know, or

Felix: Yeah. This is like a, uh, I know we’re like running out of time here, but like we, we previously talked about sharing skills and I did have this question of like, what if your cowork would just like ask the other coworks if they have a skill for this task?

Doesn’t matter. These could do.

swyx: Right. Like, okay, so skill transfer.

Felix: Yeah, like,

swyx: um, and again, that’s, maybe

Felix: this maybe goes back into the territory of like building something very powerful and building something creepy often goes hand in hand. Um, because I could tell from the reaction that my fellow engineers said that this is probably not what we’re gonna do, but like.

We have Bluetooth le right? Like I, this computer can figure out that it’s sitting right next to this computer. So you’re probably working on the same thing. Um, well, you see that in cowork, probably not. But, um, there’s like, I think really creative solutions to problems that we really haven’t tried yet.

Yeah,

Alessio: yeah, yeah. Yeah.

swyx: Excellent. I guess the, the last thing is, uh, philanthropic labs. Uh, I always have this mental model of a model lab versus, uh, agent lab. And this is basically Anthropics internal agent lab, which co Claude Code, uh, is now under, right? It’s part of the whole org.

Felix: I mean, people are so fungible, right?

Like,

swyx: okay, this is just, I, I don’t know how, I don’t know real. This is, I don’t know.

Felix: No, it’s a real team. It’s a very, um, the, the last team is primarily working though on things that you don’t see in public yet. Um, they’re trying like really wild out there, ideas that seem quite improbable. Um, the mad science

swyx: thing.

But you, you’re, are you officially under this thing or

Felix: No? We’re, where is the Claude Code is, but now Claude Code is like a fairly big group where. I actually know many people we are like, like I remember yesterday coming into our weekly COVID meeting. I was like, woo,

Alessio: this is hot.

Felix: There’s a lot of people here.

Um, but we still have a labs team and we actually made the labs team a lot bigger. Mike just joined the labs team as a, as an ic, which I think is very cool and very fun. But they’re, they’re working on things that you have not seen yet that are extremely out there and probably half broken. Right? Like the sort of the idea of a lab team is that it should only work on things that make really no sense for anyone else to work on.

swyx: Okay. Well, looking for exciting things from there, but thank you so much. I know we’re out of time, but uh, appreciate your joining us. I appreciate co cowork, everyone go use it. Uh, it is the closest I’ve felt to a I this year. That’s so nice you to say. Thank you very much. Yeah. Thank you for your time. Yeah.



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