265 | $300B vanished in 48 hours in a SaaSpocalypse triggered by Anthropic Opus 4.5 and ChatGPT Codex 5.3+Frontier. Agent swarms + Skill + MCP + Computer use, the gloves are off between Anthropic and OpenAI and more critical AI news ending February 6, 202

26:33Our most important principle for ads says that we don't do exactly this. We would obviously never run ads in the way Anthropic depicts them. We are not stupid and we know our users would reject that. So to be fair, OpenAI said multiple times that the ads are going to be separate from the regular chat answers and that it's not going to impact the answers, which is exactly what the ads are suggesting. And I'm continuing to what Sam wrote. I guess it's on brand to Anthropic to double speak, to critique theoretical deceptive ads that aren't real, but a Super Bowl ad is not where I would expect it.

27:08More importantly, we believe everyone deserves to use AI and are committed to free access because we believe access creates agency. More Texans use Chachapiti for free than total people use Claude in the US. So we have a differently shaped problem than they do. So basically what he's saying is saying they have a significantly larger free user base that they want to maintain as free. And hence, they need a mechanism to be able to pay for the tokens and the compute to allow this free usage. I 100 % agree with that. Obviously, Sam did not have to step on Anthropic in order to say that. But since they're giving a jab through the ads, he's just fighting back.

27:47Then he said Anthropic serves an expensive product to reach people. Now, to be fair, that is not accurate as well, because just like ChatGPT has multiple tiers, Anthropic has the same thing. So ChatGPT, you can get it for free,$8,$20, and$200. And you can get Anthropic for free,$17,$100, and$200. So a very similar approach exists with Claude as well. So I think that's, again, not a fair statement by Sam. But in war, like in war, you can do anything you want. And then Sam goes on in order to state what he's thinking about Anthropic. And I'm quoting again, maybe even more importantly, Anthropic wants to control what people do with AI.

28:26They block companies they don't like from using their coding product, including us. They want to write the rules themselves for what people can and can't use AI for. And now they also want to tell other companies what their business model can be. So again, to be fair, I think the fact that Anthropic is blocking their competitors from using their tools in order to write code makes perfect sense to me. And I don't really understand how Sam can use that against them. I think this makes perfect sense. Why would you use your tools to allow your competitors to close the gap against you? I'm fully aligned on the logic behind what Anthropic has done by blocking X and OpenAI from using cloud code.

29:04But then finally, in the end, Sam went to the positive side, and I'm skipping a part of the tweet. And he said, we are enjoying watching so many people switch to Codex. There have now been 500 ,000 app downloads since the launch on Monday, and we think builders are really going to love what's coming in the next few weeks. I believe Codex is going to win. So what does this whole thing tell us? Gloves are off. As much as there's been a fierce competition between these two companies before, this is a very serious escalation of this, both in going to ads that just joke about the other company, as well as the level of responses from Sam on X, this is going to be a very dramatic year for the competition between these two companies.

29:47But this is a very good segue to talk about their release of the new coding platform from OpenAI. Let's do a little timeline analysis. Both companies apparently were planning to launch their new products. So Anthropic Opus 4.6 and GPT 5.3 Codex, The plan was to release them at 10 a.m. Pacific time. However, Anthropic jumped the gun and moved first and made the announcement at 9.47, so 13 minutes before the queue, and OpenAI followed at 9.52. So five minutes after Anthropic made their big reveal, OpenAI did the same thing with their product that is the direct competition for the Anthropic product.

30:29So GPT 5.3 codex is reportedly 25 % faster than codex 5.2. The model topped both SWBenchPro and TerminalBench2 benchmarks. And OpenAI describes it as the advancements that transforms codex from a tool that can, and I'm quoting, write and view code into a capable platform that can perform, and I'm quoting again, almost anything developers and professionals do on a computer. So again, you can see the shift from developing a tool just for computer developers to a tool for any professional, very similar to what Claude did with Cowork a couple of weeks ago. Now, an interesting point here is the five-minute gap between the two announcements, which tells you very clearly that both these companies know exactly what's happening in the other companies.

31:17So the level of competitive intelligence that is happening here is absolutely crazy. and I don't know if it's people just drinking beer in the same places or real business espionage, but one way or another, releasing two competitive products within five minutes apart tells you that they're knowing exactly what's happening behind the scenes, each in the other company. Now Codex is available to all ChatGPT paid plans, and you can use it on the standalone Codex app, and in the command line interface, and in your favorite IDE, and on the web interface, and the API access is coming very soon. Now, very similar to the announcements from Anthropic, Codex also has the ability to schedule recurring tasks.

31:55So you can tell Codex what you want it to do. You can develop skills for it, very similar to what you can do with Cowork. And then you can set up and define a specific schedule. When a task gets completed, the results get placed in a review queue for the developer and or the professional user to review the output. And the system runs on worked trees, basically defining the work for the different repositories in order to prevent conflicts when the code and or the other tasks gets executed and generated. Now, while right now it runs on the developer's computer, OpenAI is planning a server side aspect of this that will allow these parallel tasks that are pre-scheduled or that are created in real time by the other agents to run on the web while the developer's computers are off.

32:44So a continuous, never-ending development cycle, very similar to what we heard from Anthropic and from other companies as well. So the biggest shift from a mindset perspective is that these kind of back-end, long-lasting, self-fulfilling automations are a complete shift from how these models are used right now. So rather than asking the AI to complete a specific task at this moment, developers can define recurring workflows, entire workflows, and delegate it, such as maintenance work through databases and so on, can happen on their own in the background, running by multiple agents, just by providing humans feedback on what is the status, but executing autonomously.

33:26But that's not the final thing that OpenAI introduced, or if you want from the late night infomercials, but wait, there's more. So OpenAI also launched Frontier, which is an enterprise platform for building, deploying, and managing AI agents, not just their own AI agents, but the idea is to create an infrastructure that can allow you to run and manage multiple agents from multiple sources, including from their competitors, such as Google, Microsoft Ananthropic, or any homegrown other third party agents that were developed by any enterprise can all be managed on this one environment. One of the key features of the Frontier platform is what OpenAI calls semantic layer for the enterprise, which basically allows to take silo data from whatever warehouses, such as CRM system, ticketing tools, or any internal applications, and create a unified context environment that all the agents can access and reason over that data, basically breaking one of the biggest problems that companies have right now with data, which is siloed, firewalled data that exists in different places that the AI agents cannot connect to all of it together.

34:32Well, it solves that problem. Now, it also introduces the concept of co-workers. The name, again, very interesting after Claude launched Cowork. And the idea is that agents can be managed similar to how you manage human employees, complete with onboarding process and feedback loops and improvement cycles over time. so the agents build memories and learn from the performance of other agents, and they keep on improving the quality of the output by monitoring themselves, creating dashboards for humans to monitor them and give them feedback, and so on. Now, early adopters of this platform include companies like Intuit and State Farm, Uber, HP, Oracle, BBVA, Cisco, and T-Mobile, and some companies are reported getting 90 % more time back for their client-facing team by using this new architecture.

35:19Now, to make all of this more accessible to users, OpenAI also launched Codex desktop app for Mac OS. Again, sounds familiar? The same exact thing that Claude did with Cowork just a couple of weeks ago. So OpenAI released the Codex app on February 2nd. The desktop app supports multi-agents parallelization, where the coding agents can run multiple threads at the same time. Again, the same exact thing we've seen from Anthropic and from Kimi2 and from Cursor. Now, individual agents can run for more than 30 minutes independently before returning and completing the code review with other agents. There's a centralized plan mode that provides review for the state of all the developers so humans and other agents can inspect what is actually happening and the full process can be tracked and managed in a more effective way.

36:08As I mentioned, it also allows you to schedule tasks that can run in the background for more or less anything that you want. I haven't tested the new codex yet, but it sounds very much like similar capabilities to Cloud Cowork that, as I mentioned multiple times in the past few weeks, I'm completely obsessed with. And it also allows connecting skills and connecting apps and connecting MCPs and building really powerful agentic solutions through that. So I haven't tested it yet, but I'm definitely planning to test it out and compare it to Cloud Cowork. And I will report my findings once I have a clear understanding of the pros and cons of each and every one of these platforms.

36:43Another interesting thing that they did is that they have cross-tool continuity, meaning you can continue in the desktop app sessions that you started either at your development platform or IDE or even in the terminal. So all of these allow you to continue the work that you started in one and continue in another. Now to show you how fast this is evolving, over 1 million developers use codecs in this past month. Usage has nearly doubled since GPT 5.2 Codex came out in mid-December, so less than a month and a half ago. And it has grown 20x since the launch in August of 2020. So in just a few weeks, we went from several tools who are great in coding, but that require a lot of hands-on from the developer and a lot of direct guidance and can more or less write only code to autonomous multi-agents orchestrated tools that can run 24-7 while running scheduled tasks in parallel and going way beyond coding into more or less any knowledge work.

37:46We're not just accelerating, the acceleration itself is accelerating. Now, from a personal perspective, I can tell you that I can feel, literally feel, what they mean by reaching the singularity. Meaning, I feel that the rate of change is getting very close or closer to a vertical line going straight up. Again, a few weeks ago, we didn't have many of these capabilities that are now all maturing and connecting to extremely powerful capabilities. As I mentioned multiple times in this podcast, we are not ready for this from any perspective, from an economical perspective, social perspective, psychological perspective.

38:25In other words, the human race, all of us, are not ready for such a rate of change, such a rate of improvement, which means because we're not ready, we will need to deal with a lot of unknowns and really serious bumps on the road in real time versus planning for them in advance. And this will become the norm because the speed of change is so fast and we cannot keep up with it, which from a global society scale, I believe is a really bad thing. Now, in addition to all these things, OpenAI also announced a broader support for MCP apps inside everything OpenAI. So they had support for MCP since March of 2025, just a few months after Anthropic announced it in late 2024.

39:08But now they have full read and write actions built into the MCP capability inside of OpenAI, which is similar again to what Anthropic already has, which provides developers in the OpenAI universe a lot more flexibility with what they can do with MCP connectors. And together with that announcement, they also announced a lot of new MCP connector partners in the OpenAI environment, including Amptitude, Fireflies, Versal, Monday.com, Stripe, Hex, Ignite, Alpaca, BioRender, SEMrush, and many others, including Atlassian, which brings in tools like Jira and Compass and Confluence, which you can now communicate with through a regular ChatGPT conversation.

39:46And we'll allow you to understand what's happening in each and every one of these platforms, but also make changes to these platforms so you can update your Jira just by having a chat with ChatGPT. And the same thing for Monday.com. If you're not a developer and you're just working on tasks in a regular knowledge work environment. Now, if you think I'm the only one that feels that this is moving a little too fast and requires some more guardrails, I mentioned to you a few weeks ago that OpenAI had an open position for a head of preparedness, somebody that will basically manage and oversee the deployment of new systems and the level of risk that they represent.

40:19OpenAI found that person. They just hired Dylan Scandinaro, which used to work at Anthropic at a very similar role. Altman framed the hire in the context of these accelerating capabilities, stating that things, and I'm quoting, are about to move quite fast. And he stated that OpenAI will be, and I'm quoting, working with extremely powerful models soon. In a recent interview with Forbes, Altman hinted that OpenAI has, and I'm quoting, basically built AGI or something very close to it. In another interview this week at the Cisco summit, where he was interviewed by Cisco's chief product officer, G2 Patel, Sam mentioned that 2026 is going to see a significant jump in the capabilities of models.

41:01And when he was asked whether the users are going to feel a 5X, a 10X, or a 50X improvement, he said that he believes that it will be about a 10X improvement by the end of this year. Now, from my personal perspective, I can tell you that as somebody who's been using these models every single day, and they're all extremely powerful right now, I cannot understand what a 10x improvement can look like because the models are already extremely capable right now. And he's talking about all of this happening in 2026, which means in the lab, they already have these models running. When these guys make predictions for the next few months, they're not making predictions.

41:35They're basically telling us what they have working in the lab right now that they haven't released yet. And Sam, by the way, confirmed what I'm feeling in the past few weeks, that the convergence of all these things together is what makes it unique. And he noted, and I'm quoting, code is really powerful, but code plus generalized computer use is even much more powerful, which is exactly what I'm experiencing. I don't really care that it's writing code in the background. I care about what it enables me to do by connecting the dots across more or less everything a business needs to do from a knowledge work perspective.

42:07And this is what these platforms enable right now. And if they're going to be 10x better by the end of the year, this is insanely powerful. And as I mentioned, nobody is ready for it, especially not companies. And Sam himself in this interview is saying that the most important thing for companies to do right now is to dramatically accelerate their understanding on how to use AI systems. And he's saying that companies who will fail to do that, who will be unprepared for integrating AI into everything that they're doing, will face a significant competitive disadvantage in the very near term. And I can tell you that working with multiple businesses, myself as a consultant and as an educator with these companies and showing them what's possible, I can tell you that the companies who are adapting and making these changes are gaining huge, significant competitive advantages over their competitors.

42:58And again, I'm saying that from the positive side, but it obviously means that the companies who are not doing this are going to suffer in a very big way in a relatively short amount of time. By the way, if you are in a company, in a leadership position, and you're looking for assistance in that, please reach out to me either through the link in the show notes. There's a way to book time with me or just reach out to me on LinkedIn. I'm there every single day and I will gladly come and provide you advice on how to proceed and what's the best way forward. Now to establish the fact that things are moving faster, Meter, which is a company that we talked about many times in the past in this podcast, is a company that has developed a benchmark to measure how fast AI is accelerating.

43:38And the way they're measuring it, just as a quick reminder, is by seeing how long AI can work in a single session in order to complete a specific task 50 % successfully. And the 50 % success rate doesn't really matter because they just keep on comparing a 50 % success rate over time. So the fact that it's a 50 % success rate is obviously not acceptable from a business perspective. That's not what they're trying to measure. They're trying to measure from one model to the next, how much longer can it work and still complete tasks in 50 % of the time? Well, they got to the limit of their previous benchmark because the AI was able to complete the task successfully almost every single time relatively quickly.

44:14So they developed a new benchmark that they're calling TH1.1 versus TH1 that happened before. But even with this new benchmark, what they found is now that now the models are doubling the time they can work on a specific task every 131 days versus 165 days, which was the assumption previously. So if previously models could double the amount of time they work on a task every 165 days. Now they're doing it every 131 days, which tells you, again, that the improvement is accelerating between the different versions of them. So what I am feeling, and if you are in this universe on a regular basis, you're feeling it as well, is not a subjective feeling.

44:57It is actually what's happening right now. And now to a lot of quick and interesting rapid fire items. Apple just released Xcode 26.3, which is integrating coding tools from both Anthropic and OpenAI, so the two main things we just talked about, into the Apple development environment, which means you can now use Anthropic agents and OpenAI agents in order to do development for anything in the Apple ecosystem. So you can develop iOS, macOS, watchOS, tvOS, and visionOS applications using these very powerful tools. Cursor, who is probably the most known name out of the AI development platforms out there, and definitely the one that is used the most by developers, not just by Vibecoders, just released an interesting blog post detailing their findings on how to run multiple AI coding agents simultaneously on a single code base and introducing multiple interesting concepts.

45:53And you can see this aligns perfectly with the latest releases from Kimi and OpenAI and Anthropic on running multiple agents on a single task that are running in parallel. It's a very technical and yet very interesting paper. And we'll put the link in the show notes. But the bottom line is the world of parallel agents is already here. And it is going to change every single thing that we know as far as how work can be done in a very dramatic way in a relatively near future. And basically what they're saying, that they've resolved all the issues on how to resolve conflicts between all these agents.

46:30And they've actually resolved it in a very interesting way where they actually allow the agents to make mistakes. So in their initial attempts, they were trying to get the agents to do everything perfectly on two different levels, both the individual piece of code that the agent is generating, but also preventing overlap and issues with the code. And they basically learned that a small error factor in both the code and conflict issues actually generates better results because these get resolved by other agents afterwards, providing an overall faster and more efficient and yet accurate system at the end product.

47:00And what they're saying right now is at scale, the limitation right now is not the agents or their coordination, but the ability to read and write from the hardware you're reading and writing to. So the disk IO that is being used in order to write the data or retrieve the data that is required by these agents, the actual hardware limitation becomes the limitation of how big or fast the system can work because hundreds of agents that are running in parallel can generate gigabytes of new code every single second. This is obviously a very profound situation that we're in, that the limiting factor for the amount of code you can generate is how fast the disk can write the new information that gets generated and not how many agents can run in parallel.

47:46Now, something from two weeks ago that I did not report on, but now that we're reporting on a lot of interesting releases that I feel that I have to report about, is Google DeepMind released Project Genie, which is the next version of the prototype that previously was released only for preview of specific companies and organizations. And it's a tool that is using several different capabilities that Google has developed in order to create 3D worlds in real time. So we talked about world models on this podcast several times in the past. Genie 3 is one of the most advanced of these. And the way it works is the user defines the world they are trying to create and the character they are trying to create.

48:22And then Genie creates it in real time. And it's currently allowing a 60 second free navigation through this new world with whatever character you invented. And it is doing this at a relatively decent quality of 720p with 24 frames per second. So think about coming up with an idea for a new world and allowing you to navigate that world with whatever kind of agent representing you in that universe, whether a bird, a person, a submarine, literally whatever you can come up with can be the entity that is navigating. And it can be a third party view or a first person view from that thing, allowing you to navigate that universe.

49:02This is just another step in the intensifying race in the world models environment where Fei Li has launched World Labs, which is developing something very similar with a product called Marble. Runway has launched their own world model. And we also talked on the podcast on Yal-Nekun, previously the chief scientist of Meta, leaving and starting his own company that is going to focus on developing world models, which has incredible, interesting implications. One of them might be just like there was just the SaaS apocalypse. We can see the gaming apocalypse happening because if anybody can create any game on the fly just with a prompt and then share it on an app store or a gaming platform, then why do you need large companies to create new games if they can just be created on the fly?

49:46Again, I don't think it will replace all games. I think it will replace all the less sophisticated games and you will do this very quickly. And I think it will have a profound implication on the gaming world. But to me, and I talked about this in the past when we talked about these models, I see a very scary future addiction. Because if you can experience anything in any world, whether a realistic world or imaginary world, and you combine that with virtual reality headsets that will get more and more advanced, and with haptic devices that will make you feel and touch anything in that world, we are going to end up in a Black Mirror episode where people will prefer spending time in these virtual universes versus realistic universes.

50:28And I sadly see stuff like that happening, not in the too far future. Sticking to the visual world and sticking to interesting releases this week, Kling AI just released Kling Video 3, which is now one of the most advanced video and image generation platforms. What's interesting about it is they created one unified multi-modal AI generation engine that integrates text and image and video and audio into one single training framework, which provides it extremely powerful capabilities. The video generation time jumped from 10 seconds to 15 seconds, and you can control the exact duration when you set up the preset options of the run.

51:08I added a really interesting feature that generates a multi-shot generation that allows you to generate up to six distinct camera cuts with a single video, which enables you a lot more control from a storytelling perspective. They also now have native audio generation, so now it allows you to create both the speech of the characters, sound effects, and music in the background, all while generating the first run of the video, similar to what we know from VO3. Now, from a quality perspective, the model outputs native 4K resolution at 60 frames per second. It can speak Chinese. It has multi-language support for Chinese, English, Japanese, Korean, Spanish, and other different specific dialects.

51:51And it has very strong consistency of subject and environment across multiple generations, which enables you to generate really long videos and combine them together seamlessly because the environment and the person stay consistently between all these generations. Staying on video generation, Meta just announced that they are launching Vibes, which is a standalone AI video creation app that lets users generate videos from scratch or remix existing content. You can then add visuals, add music, adjust different styles, and then post directly to the Vibes feed on both Instagram and Facebook. So this is a very similar concept to the Sora app from OpenAI, which tells you that we're going to see a lot more AI-generated content in our feeds.

52:40The more interesting announcement from Meta is something that we discussed shortly last week, which is Mark Zuckerberg basically saying that this year, Meta is planning to release a complete AI-controlled, autonomously generated advertisements on their platform. So you as the user will submit a product image or a URL in a specific budget, and the AI will autonomously complete everything. Images, video, text, determine the optimal targeting, will select the best platform, and will basically run the ads for you. This is the collapse, if you want, of an entire industry of marketing and ad agencies that has been doing this since the launch of e-commerce about 25 years ago.

53:22And I'm going to end with a funny, interesting, and yet scary thing that happened. And it actually happened several months ago, but I just caught it right now because apparently the phenomena has been growing. So an AI-generated travel article on the Tasmania Tours website, fabricated, basically hallucinated, a non-existing tourist attraction called the Weldeboro Hot Springs. And it included a detailed description of how beautiful the springs are and also vivid AI-generated images of steaming pools in the lush rainforest. Now, actual real tourists are driving hours through Tasmania's countryside to reach the destination to find out it doesn't actually exist.

54:06Now, a local pub owner said, and I'm quoting, it was only a couple of calls to start with, but then people began turning up in droves. I was receiving probably five phone calls a day and at least two to three people arriving at the hotel looking for the springs. Now, one of the reasons it was so successful in confusing people is that this article that, again, was AI generated also included well-known attractions like the Hestings Caves and other known attractions in Tasmania. So it made the made-up locations a lot more believable because a lot of people knew a lot of the other attractions. And by the way, that's what I see with most hallucinations on the day-to-day.

54:45They don't just show up as a standalone clear thing. They are well blended into a great output that most of it is real and some of it is made up. And that's what makes it very, very tricky to find hallucinations. But now I want to combine some of the dots from this episode together. I want you to combine this with how we started this article. So think about this particular article is a one article that was created by a person using AI and then posted without checking all the information. But we're talking about a very near future where completely autonomous work cycles are completed with multiple agents running in parallel 24-7, generating whatever output they're generating.

55:24could be code, but could be new business protocols, could be new products and services, could be new content or articles on behalf of your company, all while potentially hallucinating in the process. Now, while I'm telling everyone, including myself, to check every output the AI gives you because it might be hallucinating, the reality is we're getting very close to the point that it is impossible to verify the amount of work that AI is going to generate. Now, whether it is possible or not, it is very easy to stop doing this. And I told you in the beginning that when you use these agents, they ask you for approval to take different steps.

55:59It's the same in Cloud Code. It is the same in Cloud Cowork. And I very quickly went from looking at every single step and approving it to just giving it a blank check to do whatever it wants every time it asks for access to a specific platform, just because it is so tempting. I do not want to allow it to do everything it needs to do. I just want the output and I want it fast and I want it to be efficient. And I don't want me to be the showstopper or the blocker for the effort. So I'm just allowing it to do the work. Now combine that with systems that are 10x faster, that are deploying these kind of agents at a global scale, and you understand why this can go terribly wrong.

56:37I'm not saying this to scare you. I'm just telling you what's coming. And sadly, I don't have any good solutions or even suggestions on how we handle this reality where independent agents are working at scales we cannot monitor and they're generating content which may or may not be real that is going to be used across literally everything that we do. And this is without even talking about the option that there's actually bad actors that will do this on purpose, that will create such things at scale with swarms of agents to convince millions or potentially billions of people of whatever they want to convince us with.

57:14So on this positive note, I will end today's episode. And I will mention that all I can do at this point is keep you updated and keep you as much aware of what is happening and what I think is going to happen and how it is going to impact our world. And I really hope that the fact that more of us have that knowledge somehow allows us to be better prepared and reduces the overall risk. If you are finding this podcast helpful, even if scary at times, I would appreciate it if you rank it on your favorite podcasting platform, if you write us a review, and if you share it with other people who can benefit from it, it will take you seconds to do.

57:51Literally click the share button and then share it with a few people who can benefit from it as well. Keep on testing AI yourself. Keep sharing with the world what you find. This is our way to be better prepared for what is around the corner. That's it for this week. And until the next episode, have an amazing rest of your weekend.