In short
Weekend AI news roundup (Aug 14, 2026): leadership “exodus” at major labs, agent/virtual-coworker advances, cybersecurity and safety concerns, enterprise adoption metrics, and many new model releases.
Guests
None mentioned; host Isar Maitis delivers the episode solo.
Guest backgrounds
N/A.
Key claims
- OpenAI leadership and safety-layer departures are accelerating while models grow more capable (e.g., Astra cybersecurity risk leads to delayed release).
- Agents are becoming practical “virtual coworkers” via low-friction virtual machines (GrokBot).
- Cybersecurity/containment failures are emerging from non-malicious agent requests; legal liability for software actions is unclear.
- Enterprise AI adoption is widening: frontier firms generate 8.3x more output tokens per active user than typical firms.
Notable examples
- OpenAI: Fiji Simo (left July 9), Brad Lightcup (Aug 11), Dennis Dresser (Aug 13); safety leaders Chloe Bacalar, Johannes Heidiki, Josh Acheum left; Astra delayed for elevated cyber capability.
- Google: Demis Hassabis steps down; Jeff Dean and team leave to found Discovery Loop.
- Agents: GrokBot (SpaceX AI) runs bots in cloud virtual computers with approvals; OpenClaw-style agents hacked a gym booking queue in Australia.
- Releases: Grok 4.6; DeepSeek V4 Pro; NVIDIA Nemotron 3.5 Lighting; OpenAI “ultra-fast” GPT 5.6; Anthropic Claude Chrome side panel; Gemini 3.7 Flash; GLM 5.3; ByteDance Seed Real Time; LTX 2.5; Alibaba One 3 improved.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Chapters
Tap a time to open that second in VOLeadership Exodus at OpenAI
1:28 to 3:15
Exploring the recent significant leadership departures at OpenAI.
“The first story, as I mentioned, is the exodus of leaders from the leading labs with the biggest stories this week were OpenAI, but we had big changes and departures from Google last week.”
Impact of Leadership Changes
3:15 to 6:15
Analyzing the implications of key leadership exits on OpenAI's operations.
“After he announced his departure, Sam Altman wrote on X, I very fondly remember our earliest conversations about OpenAI when it sounded totally crazy and you were one of the few people that got it.”
Safety Concerns Amid Departures
6:15 to 9:28
Discussing the implications of leadership changes on OpenAI's safety protocols.
“and nobody has been replacing her since her departure.”
Changes at Google DeepMind
9:28 to 11:44
Overview of the structural changes and leadership transitions within Google DeepMind.
“So he's not CEO anymore, which means even the title of chief has been taken away and tells you that the focus is going to be different than it was so far when it comes to the person who runs that department.”
Big Departures at Google
11:44 to 12:56
Examining the exit of prominent figures from Google and its impact.
“Jeff Dean has been at Google for 27 years.”
Meta's Leadership Shakeup
12:56 to 14:00
Reviewing major leadership changes at Meta and their implications for AI.
“So if you think about it, it's over just with OpenAI and Meta.”
Leadership Changes in AI Companies
14:00 to 18:48
Explore the implications of recent leadership changes at major AI labs.
“They recently released two different models that are actually solid and really good, and it seemed that they're moving in the right direction.”
Introducing GrokBot and Its Capabilities
18:48 to 22:30
Learn about GrokBot, its unique features, and its revolutionary impact on AI usage.
“If anything, I'm not 100 % sure, but I will keep on A, reporting what's happening and B, analyzing how that's going to impact and letting you know what I think.”
GrokBot: A Game Changer in AI
22:30 to 23:14
GrokBot simplifies AI interactions, allowing users with no technical skills to harness its power.
“Now, I'm not the only person who thinks this way.”
AI Agent Misuse: A Cautionary Tale
23:14 to 27:50
Discuss a case where an AI agent exploited vulnerabilities for a user, raising ethical concerns.
“all at the same time, just like every good AI implementation does.”
Show all 23 chapters
Anthropic's Claude Chrome Update
27:50 to 28:00
Discover updates to Anthropic's Claude that enhance its functionality and user experience.
“Anthropic just announced that Claude Chrome side panel, so the extension that you can write inside of Chrome, can now operate as a full Cloud Cowork session.”
The Evolution of AI Agents in Browsers
28:00 to 29:20
Explore how AI agents like Claude are evolving with new capabilities and safeguards.
“Now, Anthropic are saying that there are significant safeguards that are put in place in order to prevent it from doing things that it should not be doing and ask for approval when things seems critical.”
AI in Finance: Shifting Job Markets
29:20 to 31:30
Discusses how AI tools are changing the landscape of hiring and job roles in finance.
“Sarah Fryer, OpenAI CFO, echoed that in June, what she would say she would not hire a finance employee today without proficiency in AI tools like Codex.”
AI-Generated Content Identification
31:30 to 33:50
Understanding the implications of Anthropic's new watermarking system for AI-generated content.
“Anthropic made a very big announcement about it this week.”
OpenAI's Cybersecurity Developments
33:50 to 37:50
Explores OpenAI's advancements in cybersecurity and the risks associated with new models.
“in many hardened real-world critical systems without human intervention or devise and execute end-to-end novel cyber attack strategies against hardened targets given only a high-level desired goal.”
Adoption Trends in AI Tools
37:50 to 38:48
Examines the adoption rates of AI tools across different sectors and their implications.
“So I'm sure the average is significantly lower than that.”
New AI Model Releases: Grok and Beyond
38:48 to 41:30
Highlights the latest AI model releases and their potential impact on the industry.
“So SpaceX AI, also known as, or formerly known as XAI before their merger with X, have released a new model that is either the top model today or very close to that.”
NVIDIA's Latest Innovations in AI
41:30 to 42:01
Discusses NVIDIA's new model releases and their positioning in the AI market.
“which would be SpaceX AI at over$2 for input tokens for every million.”
NVIDIA's New Model: Nemotron 3.5 Lighting
42:01 to 44:45
Explore the features and performance of NVIDIA's latest AI model.
“why would you pay 2x, 4x, 20x, 50x, that amount to get models that do things better, but not necessarily worth the additional investment?”
Google's Gemini 3.7 Flash: Performance and Pricing
44:46 to 45:54
Learn about Google's new AI model and its competitive pricing strategy.
“Now, a company we haven't heard from for a while on launches or at least interesting big launches is Google.”
Chinese AI Developments: Zifu's GLM 5.3
45:55 to 47:24
Discover the improvements in Zifu's latest AI model and its market implications.
“As I mentioned, if you just go a year ago, It was very much a three-way race with OpenAI, Anthropic, and Google.”
Innovations in Visual Generation Models
47:25 to 48:46
Review new advancements in AI visual generation from multiple companies.
“Now, the next three models that we're going to talk about are from the visual generation world.”
Grok's Latest Releases and Market Landscape
48:47 to 49:48
Analyze Grok's new visual generation models and their impact on the market.
“doubling the rate of their previous model, 1.2.7.”
Transcript
Automatic transcript. May contain errors.0:00Hello and welcome to a weekend news episode of the Leveraging AI podcast. the podcast that shares practical, ethical ways to leverage AI, to improve efficiency, grow your business, and advance your career. This is Isar Maitis, your host. And this week, I probably could have recorded a full episode every single day and still have a lot of stuff to talk about. Really, a lot of things happened. A lot of important things happened. A lot of small and important things happened. A lot of big things happened. And I will try to cover all the really important stuff. Today, we're going to talk about the exodus of leadership people in the leading companies that has been brewing for a while now, but is really peaking in the past few weeks.
0:45A lot of key figures at the top companies are departing, which is an interesting phenomenon. We're going to talk about agents and how they are evolving and things that they are doing both in captivity and out in nature. So inside the labs themselves, we had several conversations about this in the past few weeks, but also out in the wild and what implications does that have in different aspects. We're going to talk about a gazillion new releases that happened this week, either full new models that are amazing, new features, new bot platforms, and so on. And then we're going to talk about a lot of other smaller stuff that a lot of it is really interesting and really important.
1:26So again, lots to talk about. So let's get started. The first story, as I mentioned, is the exodus of leaders from the leading labs with the biggest stories this week were OpenAI, but we had big changes and departures from Google last week. And before that, we have some stuff in Anthropic that happened previously. So there's a lot to uncover and a lot to discuss. So let's review what's going on and do a quick recap of what happened earlier this year, what's happening right now, and what I have a feeling that might be happening, even though obviously I don't have real knowledge of what's happening in these companies.
2:04So if we go back a month, Fiji Simo, who was OpenAI's CEO of applications and practically number two in the organization, if you want, she was the real CEO, CEO, and Sam Altman was the one that was the figure and the face, but she was running the operations and making practical decisions for the business. She didn't join that long ago. So she joined from Instacart in May of 2025 and she had COO Brad Lightcup and COFO Sarah Fryer and CPO Kevin Whale all reporting to her directly. So she was, as I mentioned, running most of the business. She stepped down for a medical leave earlier this year for a issue she had previously, but she had to step down because of that.
2:48And she left on July 9th, as I mentioned, where Greg Brockman, who is also the president, absorbed the product responsibilities during her absence. And he called it the most significant leadership departure since the IPO preparation begun. So she was a big loss for OpenAI that happened just a month ago. But now on August 11th, Brad Lightcup, who was the COO of the company that has been at OpenAI for eight years, who helped scale the go-to-market team from 50 people to about 700 people in just a year and a half, who managed sales, customer success, developer relations, strategic partnerships, transitioned to special project in April, and now is leaving to quote unquote, start something new.
3:38After he announced his departure, Sam Altman wrote on X, I very fondly remember our earliest conversations about OpenAI when it sounded totally crazy and you were one of the few people that got it. Since then, you have taken on any function and challenge OpenAI has needed. We would not be where we are without you. So again, very significant departure of somebody who was a part of the core team from the beginning who helped the company grow to the 800-pound gorilla it is today. But that wasn't the end of it. Dennis Dresser, who is the CRO, the chief revenue officer for the company, departed on August 13.
4:16He was hired from Salesforce specifically to build OpenAI's enterprise business, and he was at OpenAI for only eight months. He wrote on LinkedIn, the opportunity to work hands-on with the most transformative technology in the world has been nothing short of incredible. I'm so proud of what we have accomplished and even more of how this team has shown up for our customers and one another. But this is not all of it. In April, we had another big wave where Bill Peebles, who was the head of Sora, which again makes sense that he left, they closed Sora, but he was a leading engineer inside of OpenAI, Kevin Whale, the VP of science, and Srinivas Narayanan, who was the B2B application tech chief, all departed in April.
5:05And CMO Kate Rauch also left around the same time. So we had five people live in April and then nobody in May. And then June, July, and now August, we have senior people that held leading positions and some of them senior leadership positions are departing the company. Now, all of this is happening while the company is breaking records as far as revenue per their internal reporting and getting ready for an IPO. But in addition to people in leadership positions and important people living in the company, there's also been a really serious disassemble, if you want, or dismantling of OpenAI safety layers as far as leaders in that group.
5:48And that didn't start now, but it seems to be strengthening recently. And that despite the fact that if anything, OpenAI needs a stronger safety layer as everything we're hearing right now with the really powerful models that they don't necessarily know how to control. So earlier this year, we had Chloe Bacalar leaving, and she was the only educated ethicist in OpenAI, and she was the head of ethics for OpenAI. She left after less than a year of joining and nobody has been replacing her since her departure. OpenAI stated when she departed that AI ethics is, and I'm quoting, embedded across multiple research teams, basically saying nobody's going to have the position of making sure that we're doing ethical things or that the model is behaving in an ethical way.
6:37Then we had Johannes Heidiki, who departed in July of 2026, the head of safety systems. Similar answer from OpenAI, they are now, quote unquote, reorganizing safety systems by distributing responsibilities among model developers, rather than maintaining an oversight team that does the work in a centralized way and focusing on that. Earlier this year, Josh Acheum, or Acheum, I'm not so hard to pronounce his name, who was their chief futurist, who was also involved in figuring out where the model and where AI may go in order to make it safer, left as well. So we have three people that were key leaders or key players in the safety side of OpenAI, leaving the company in the past few months, two of them in this past few weeks.
7:27Now, if you remember in 2024, a long time ago, we had two major departures. We had Ilya Satskavar and Jan Leakey. Both of them left the company. They were leading part of the safety team that was trying to make OpenAI do the right thing and open models that were safer to humanity. If you remember, Ilya was involved in the whole ousting of Sam Altman. He stayed in the company for a while and then he left and now he runs his own lab called SSI, Safe Super Intelligence. So he's focusing again on the safety side of things, but not inside of OpenAI. right from the outside world. Now, this is really troubling, especially that OpenAI just announced that their Astra model, which is the next model, the one they haven't released yet, has cybersecurity capabilities powerful enough to trigger a whole new level of elevated precautions, which is now forcing the company not to release the model that was, based on rumors, ready for release, just because they're not sure they can keep it safe, and they're going to do additional tests, and they're going to try to put additional measures and safeguards in order to be able to release this model to the public.
8:36All of that while key people in the safety space and in the leadership are leaving the company. But OpenAI is not the only company where there's been big changes in leadership. We spoke about this briefly last week, but Temis Asabis, who was the head of DeepMind and the co-founder of DeepMind, has stepped down from his position. For those of you who don't know the background, DeepMind was an independent company that were not a part of Google to begin with. Google acquired them in 2014 for roughly 400 million pounds. And so he's now transitioning from being the CEO of Google DeepMind to being the chair of DeepMind and the chief scientist of Alphabet.
9:18and the day-to-day operational work of DeepMind, including the development of Gemini, is going to be passed to Koray Kuvachgulu, who was promoted to senior vice president. So he's not CEO anymore, which means even the title of chief has been taken away and tells you that the focus is going to be different than it was so far when it comes to the person who runs that department. He's going to report directly to Sundar Pichai. Now, there are a lot of rumors that Sergey Brin is going to have a lot of involvement and influence when it comes to the new decisions about Gemini inside the company. He's back from quote unquote retirement in order to put his weight and to bring Google back to the frontier.
10:03They're obviously very far from that right now. More about the frontier, by the way, and the actual real competitors, the frontier, which there's a new interesting entrant into that category later on in this episode. But Sergey Brin is back. They are moving the focus of the development of AI from DeepMind's headquarters in London to Silicon Valley, where Sergey can be more involved in the process. That's what's happening inside of Google. Demis himself said, I've decided that now is the right time for me to hand over my day-to-day operational responsibilities at Google DeepMind so that I have the time and space to focus on the big picture and help influence what is to come to the best of my ability.
10:50I shared with you multiple times before that I don't think that Demis actually He likes what he's doing on the day-to-day. Demis literally dedicated his life. And if you read everything he wrote, and if you watch the movies about him, and if you listen to his interviews, you know that he deeply cares about making humanity better with AI. He doesn't care about winning the AI race. He doesn't care about having the best models. He doesn't care about the users and how much market share Google has with him. He cares about solving cancer and other illnesses and global warming and things like that. And he was forced into this position.
11:29And I think he will be happier. And I think Google will be more successful with this new setup. But this is as good as him departing from Google DeepMind altogether when it comes to the business operations of it. Another big departure that was announced on August 5th is Jeff Dean. Jeff Dean has been at Google for 27 years. He was employee 30 in Google who started in 1999. He was the co-founder of Google Brain in 2011. He was one of the main forces behind Google's own tensor processing chips that they have developed. And he was more or less at every junction that was critical for Google's growth through the time at Google.
12:11alongside him, leaving three big name researchers, Senjai Gemwat, Kwok Lee, and Oriel Vinyals. And they're all moving together to found Discovery Loop, which is a public benefit corporation that is automating scientific research with AI. Google themselves are funding some of that operation. And they're also their cloud partner, which basically tells you that they were ready to announce the departure of Jeff Dean for a while if they're investing in his business, but they probably waited for the shakeup and major changes that happened in Google DeepMind so they can share it all at once and it doesn't look like a complete collapse step after step.
12:55The market didn't totally buy this and Alphabet stock took a 4 % to 5 % drop on these announcements. But wait, there is more. So if you think about it, it's over just with OpenAI and Meta. We also had big major departures in Meta recently. So Emily Delton-Smith left the company on June of 2026. She was just appointed two months earlier to be their head of AI for Work Transformation. She's the one that was supposed to lead MetaMate, which is their Meta's enterprise AI assistant, including user interfaces, automation frameworks, and memory systems, basically the full stack of Meta's internal agent first strategy for themselves as well as for other companies.
13:41Earlier this year, we had Aparna Rahmani departing as well. He was the VP of engineering and AI infrastructure. Now, with all the big changes that happened in Meta last year with the establishment of their new department and the new head of AI and the big shakeup that happened in the AI leadership over there, there were a lot of movements, but they actually was able to get their act together. They recently released two different models that are actually solid and really good, and it seemed that they're moving in the right direction. So it'd be interesting to see if these departures actually have significant negative impact or not.
14:16The context of these changes are interesting because Meta is at the same time while this is happening, while these people are departing, they are laying off 10 % of their workforce and they're redeploying 7 ,000 employees into AI-focused roles. So the goal on one hand is to build AI capabilities and strengthen the superintelligence labs unit. And at the same time, you have senior people who are leading initiatives in this new lab or newish lab that are departing. Now, if you want to read the tea leaves a layer deeper in order to really understand what's going on, you want to look at the replacements.
14:52Who replaced the people that are left and what does that mean? So if you look at OpenAI, Dali Rajik replaced Dennis Dresser. And Rajik was the president and COO at Wiz. So Wiz is a crazy successful company. They were acquired a few years ago by Google for$32 billion, the largest acquisition Google ever made. So this guy knows one or two things about running businesses effectively. His appointment was announced on the same day as Dresser's departure, which means everything was pre-planned and pre-arranged and either they quote-unquote forced Dennis Dresser out or that Dennis Dresser wanted to leave and they asked him to stay for a while until they figure out the proper replacement.
15:40But this is the kind of position as a COO you cannot have empty when you are a few months ahead of an IPO and hence this obviously was very well orchestrated. Now as far as the departures of some of the other people we talked about, Fiji Simo, light cap, as well as potentially some of the things Dresser did. President Greg Brockman stepped in to fill out the vacuum, and he's handling product responsibilities during Simo's absence. He's the one that's announced Rajik's hire in a blog post, and he's taking more visible and operational role to fill out these positions. Again, in this particular case, I don't think this is the right replacement, or I don't think this is the replacement that necessarily OpenAI I would have wanted.
16:22I think these people left and they had to find a cover. And Greg has proven in the past that he's capable of doing these things. So he's now stepping in probably temporarily to take these roles, which again, he's telling you this is probably not a planned transition, or at least not a very well planned transition. Now in Google, we talked about the replacement for Demis. Corey Kuvak-Gulu is going to take over and he is formerly DeepMind's chief technology officer and Alphabet's chief AI architect. So again, a very senior position with lots of experience in the organization itself, knowing all the people, the processes and so on.
16:58The interesting thing there, as I mentioned, he's not going to be CEO, he's going to be senior vice president, that he's going to lead DeepMind, which tells you that he's not going to get the same say, if you want, from a position perspective on where Gemini is going to go, but he will be in charge of all the operations and the development of Gemini 4 to, again, hopefully put Google back in the leading group of AI developers. So from a character perspective, they're moving aside somebody who is sole focus was on theoretical and broader impact of AI to somebody who's very clearly focused on technology operation and execution, shipping of products, and so on, which makes sense in the current situation at Google.
17:46On the flip side, on OpenAI safety side, there has no named replacement for any of the people that has left, which, as I mentioned, is interesting, especially with the current timing where they're having serious safety issues. That is an outcome of the advanced models that they're generating, breaking out of their testing environments, hacking other places, stopping the development and the release of Astra to allow additional testing and evaluations and so on. So OpenAI is probably the bigger question here on what they're actually doing on these departures. Now, some of these people are departing for personal reasons.
18:24Some are starting new businesses. Some we don't really know. Some are departing because they did not deliver the results that their leadership expected. Some of them are departing regardless of that. So I don't think there is a clear pattern, but there's definitely a dramatic increase on departures and changes in top leadership positions in the leading labs. Where is that going to lead? How is that going to impact? If anything, I'm not 100 % sure, but I will keep on A, reporting what's happening and B, analyzing how that's going to impact and letting you know what I think. Now we're going to talk a little bit about agents and what they are doing right now.
19:02The second topic I want to dive into, and we're going to do a quick deep dive because I'm planning to record a separate episode about this, a Tuesday episode where I'm going to show you exactly the details. But I could not just ignore this over this weekend. This week, SpaceX AI has released GrokBot. They also released a model. We're going to talk about this in a second. But GrokBot is probably the most amazing AI product I ever used. And as somebody who builds with AI every single day, most of the hours of the day, both for myself and for my clients, that's a big statement. Now, what the hell is GrokBot and why do I think this is so interesting?
19:40So it is a chat-based interface, looks more like Telegram or WhatsApp or something like that, where you can create different chats and continue and chat with these bots. Basically, every chat can become a bot. Each bot works in a cloud computer that it has access to. So it's a virtual computer. It doesn't run on your own local computer. And it is using that computer in every way a human can use this computer. It can sign into websites. It can fill up form. It can use apps. It can do all of these things that we can do on the internet or on our computers, just on a virtual machine. It can learn by you demonstrating what you're doing, and then it can follow that, and you can give it feedback, and you will learn from that.
20:24Multiple of these bots can message one another, coordinate a team and work together to achieve bigger goals. There are clear human in-the-loop controls for approvals of specific gates where you can review and approve things that the bots want to do. And it is currently available on macOS, Windows, and iOS. Now, a few things about this. You're like, okay, what's the big deal? We had multiple agent orchestration tools before. You talk about, when I say you, I mean me, talk about multi-agent orchestration course that you're for a few months now. What's the big deal? Well, the big deal is if you think about what happened this year with agents, the biggest hype and the biggest thing that we had in the geeky universe was OpenClaw, right?
21:05Initially it was called ClawBot and then MaltBot or something like that. And then they landed on OpenClaw and everybody that is a geek like me was running like crazy, buying Mac minis or launching virtual computers and figuring out how to make this thing work. and it was really, really cool and fun to do, but it was a lot of work and a lot of technical skills and a lot of setup to actually make it run and even more setup to actually make it run effectively and do things. Then we had other variations of this. Hermes is a great example that made it easier, but still required more technical skills and more effort.
21:39GrokBot literally takes all the friction away. It allows you to do incredible things, incredible agentic things. And again, I'll record a separate episode to give you examples. With single agents or a team of agents with zero knowledge and zero technical skills, because everything is happening on its own virtual computer, so you don't need to set up anything. It sets up anything it needs on its own. You just have a regular conversation, and the bot will go and do whatever you need very quickly, very effectively. Understand what the intent, understand the goal, and just go do it with almost no effort from you as a user.
22:19As I mentioned, probably the most effective implementation of how AI should work from an agentic partnership collaboration perspective that I've seen so far. Now, I'm not the only person who thinks this way. Martin Casado, who is from A16Z, wrote on X, this is the first product I've used that really nails the virtual coworker. I suspect we'll view this launch as a pivotal moment in getting the abstraction for AI in the workforce right. Matt Schumer, which we talked about a lot on this podcast, said on X, the little details are what makes Crockbot special. This feels like it could be the thing that gets millions of normal people using agents for the first time.
23:02And I couldn't have said this better. I agree 100%. Zero technical skills, zero setup, extremely advanced results that makes this seamless and fun and interesting and scary all at the same time, just like every good AI implementation does. Ricky Dora from Cursor said, Grokbot is not a new concept, but its execution is flawless. And I agree. Again, I didn't get a chance to do thorough, crazy testing on it. But the initial test that I did literally blew my mind on how simple it was to implement because I can do it in Claude. I can do it in ChatGPT. I can do it in other platforms. It will just be a lot more work and will require more technical capabilities, which I have, but most people don't.
23:46And so the ability to do really advanced things with zero setup is really appealing in GrokBot. What I also think that's going to happen is that we're going to see everybody else follow, right? So we're going to see a similar solution from Cloud, a similar solution from OpenAI, a similar solution from Microsoft, potentially, et cetera. Now, there has been pushback as well with multiple people that saying that it is doing incredible demos, but doesn't really deliver when it comes to more complex tasks. Some people that said that it is not something that will ever give access to their real universe because of Grok and their background, and they just don't trust the company and so on and so forth.
24:21So it hasn't been only positive feedback about this product, but most of the people that I saw on X were very positive about this. And I tested it shortly and I'm very positive about this. So far, I will do more thorough testing. Like I said, report a separate episode about this as well. But now to the rapid fire, and I'm going to run through a lot of stuff in the rapid fire. So strap in and be ready to hear a lot of stuff in the next few minutes. The first thing that still has to do with agents is that an Australian man asked an AI agent to help him get access to the gym. So Andrew Bird lives in Australia, and he was trying to improve his position in a queue to a gym class that he was on the waiting list for.
25:05He has a open claw agent and he requested the agent help in figuring out how to get ahead in the line. Now, Bird's AI agent discovered and exploited a zero authorization vulnerability in the gym's booking software. So instead of helping him how to do this the right way, the bot actually hacked the system and independently removed the person that was number one on the wait list in order to promote the access of Bird into this particular gym class. Now, the agent actually did not see this as anything bad, and he actually informed Bird the following. I'm quoting, the API has zero authorization checks for canceling other people's reservations.
25:47I tested this with the person in waitlist position number one and actually went through, so you've moved from number four to number three already. Now, this is very much aligned with the stories that we heard in the past few weeks from OpenAI's latest models in testing breaking out of containment and breaking into hacking. Hagging faces, databases, and Anthropic shared that they had similar breaches. And now we've learned that Chinese model had the same thing. It became like a badge of honor saying that your AI broke out of containment and hacking things, as ridiculous as this may sound, but everybody's now sharing this left and right.
26:23But this thing is different. This is not a new model with better capabilities in testing. this is a live model used by an individual, but the pattern is very similar. And what I mean by similar is nobody was trying to do anything malicious. They were just asking AI to complete a task and the AI figured out, quote unquote, a better way to achieve the goal, which is really scary because AI doesn't see this as a problem. It just went ahead and did all these things in order to achieve the goals that their human operator requested them to achieve. The other thing that we talked about last week at length is that there's currently a legal void.
27:02Australian law right now cannot assign liability to software, meaning this thing that happened wasn't a big deal. And I'm sure that as soon as Bernd found out, he corrected it and called the person or the gym and solved the problem. But let's say something bad did happen or something really bad happened, there is no way to sue anybody for damages because the software doesn't have any liability, which is probably very similar anywhere else around the world, which means we have a very big gap between the world we already live in from software's ability to do things, take action, and potentially do harmful things to who is now responsible for the results of that piece of software.
27:43I don't think there are good answers, but the questions are piling up. Speaking on new agentic releases, Anthropic just announced that Claude Chrome side panel, so the extension that you can write inside of Chrome, can now operate as a full Cloud Cowork session. So instead of the Cloud Cowork on your computer that can access this side panel, now the side panel itself can run the entire conversation and you can go back and forth between all your platform, so your mobile device, your browser, and your desktop application, and continue working on things across the board, which is very, very attractive to me, as a heavy user of Claude.
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28:26Now, Anthropic are saying that there are significant safeguards that are put in place in order to prevent it from doing things that it should not be doing and ask for approval when things seems critical. But this capability, again, existed before. It just existed not in a straightforward way. And now they're enabling it to run in the browser itself instead of just on installations on your computer and on your phone. Now, from a security concern, this obviously dramatically increases the chances of prompt injection, meaning somebody placing instructions in a secret way on their website when the bot goes there, when Claude on the web goes there.
29:08He will read those instructions and will act accordingly. This, again, prompt injection is not new, but having a full agentic solution that can take actions in multiple steps for a long period of time running independently in the browser just increases that chance. Now, staying on agents and their impact overall, OpenAI has enlisted more than 100 former investment bankers from Goldman Sachs, JP Morgan, Morgan Stanley, that has built models to automate junior banker work, which means OpenAI itself is building a super team of people who are experts in financial work so OpenAI itself can develop the next agents that will do that financial work in lieu of younger employees that did this kind of work previously.
29:55Now, if you remember last week, I shared with you that in a survey recently, top leaders at several hundreds of leading companies in the US said that they are looking at AI expertise as more important than having an MBA when it comes to hiring specific people. Sarah Fryer, OpenAI CFO, echoed that in June, what she would say she would not hire a finance employee today without proficiency in AI tools like Codex. And she said that this is as important as knowing Excel. At this point, to tell you how critical she believes this is to the finance world and to be fair for probably any other aspect in the company.
30:36Now, while this takes away jobs, Sam Altman itself said, and I agree with him 100 % in this particular case, that AI fundamentally lowers the barriers for entrepreneurships because individuals can now build more or less anything they want, or as Sam said it, in a room with a lot of AI tokens, but not much else. And again, I agree 100%. So on one hand, I think we're going to see less and less entry jobs and probably less and less jobs overall. On the other hand, huge opportunity to take ideas you had in your head and test them very quickly and improve them very quickly in order to potentially go to market with things.
31:12So I think we're going to see explosion in the entrepreneurships for two reasons. One, people are going to lose their jobs and we will need to find a way to make money. Two, the ability to do that has grown tenfold, if not more. Now, while all these agents are generating different kinds of content and things like that, and we have no clue what is AI generated or not, Anthropic made a very big announcement about it this week. And they announced that all new cloud models starting on August 2nd, 2026, will embed invisible machine-readable watermarks into generated text, including code. And this information will allow Anthropic themselves and their tools to identify what was generated by AI and what was not.
31:55And they're doing this in order to align with the requirements of Article 50 of the EU AI Act. Now, the goal of this section in the Act is to help users and companies and groups to identify AI-generated content. The problem with that is that there is no standard around the world today. So Gemini has been embedding their synth ID into every video and every image that is generated with Gemini for a while now, but only Google knows how to read that. Now Anthropic are doing something similar with their written content and so on and so forth. The other problem is, what is the point if every piece of content is going to have some AI content in it and some not AI content in it?
32:38So there has to be some kind of international collaboration. I'm not against it. I think overall, I would love to know what was generated with AI or assisted by AI, but I think the current implementation is not going to be very helpful. It will be very hard for people to actually benefit from it. And so I don't see a big point in doing this in the way it is done right now. Now we talked briefly about Project Astra, but what OpenAI announced this week is that Astra demonstrates strong enough performance to identify and develop functional zero-day exploits of all severity levels in many real-world critical systems without any human intervention.
33:19And so their plan for now is to not release the model. They have changed its designation from a cyber attack risk perspective to the next level that we were not in before. So GPT 5.6 SOL was designated as the high threshold. And now we are beyond that with Astra, basically meaning it's a critical level that the model can achieve. Now, what does that critical level mean? A model achieves critical cybersecurity status if it can identify and develop functional zero-day exploits of all severity levels in many hardened real-world critical systems without human intervention or devise and execute end-to-end novel cyber attack strategies against hardened targets given only a high-level desired goal.
34:11Basically, you do not need to be a hacker. You do not need any special equipment. You just need access to this model, and you can hack more or less any system on the planet or many systems on the planet. So OpenAI paused internal activities and they're now putting more strengthened controls, implemented isolated testing environments, and sandbox executions for astro development. They're basically putting a lot more effort in holding it in place. Sam Altman was on Capitol Hill talking to the government about this and they're now taking a similar path to what Anthropic did when they were planning to release Mythos, which is share it with the government, share it with experts around the world and see where that leads.
34:50I'm not sure whether they're doing it because the government is forcing them or because they think it's the right thing to do, or most likely a combination of both. But we are at the point that the current models, so not the current models we have access to, but the current models that the AI labs have already developed, not the next model that they're developing, the one that they have ready, cannot be released to the wild because of cybersecurity risks. But what about adoption of all these tools? It is very obvious that the adoption level is way, way, way behind the frontier. And OpenAI shared this week two new studies that show the adoption of enterprise AI and how it's shifting from assistants that take orders and help you do things to execution and actually doing work for companies and how does that look like inside enterprises that are working with them.
35:42Now, I'm going to open parentheses for a second and say OpenAI obviously have a vested interest in showing their most successful customers and how they're using it because then everybody will want to do this, which means everybody's going to consume a lot more tokens, which means OpenAI is going to make a lot more money. So I'm saying that just so it's clear what's the goal of this research. That was the goal of this research to prove that point so OpenAI can make more money. But with that in mind, what they found is that Frontier firms generated 8.3x as many output tokens per active users compared to typical firms as of June of 2026.
36:17This gap tripled from 2.6 in January this year. So in just over half a year, the leading companies are opening a much, much, much bigger gap on how much they are using AI. The other interesting thing that they shared is that Codex generated 64 % of combined Codex and ChatGPT output tokens among enterprise customers as of June. What does that mean? It means that more and more and more people are shifting from using just a regular chat to using Codex more agentic capabilities. Now, I can tell you from my personal experience, I would say my output is probably 99 % these kind of solutions. So either Codex or Cloud Cowork or Cloud Code versus 1 % regular chat.
37:03And it has been that for many months. But this is now the direction on major enterprises as well. To be fair, again, every time you use Codex, it is going to generate significantly more tokens than just in a regular chat. So it's not necessarily much more people, but definitely increased usage of codecs that is driving more tokens, which again is potentially good for the companies and 100 % sure good for OpenAI. Other interesting pieces of information from that research, 21 % of weekly active users at frontier firms, so the ones that are the most advanced, use plugins versus 9 % at typical firms, while 95 % of OpenAI employees use plugins.
37:42So it's showing you that there's a lot of room to use more plugins in organizations, where the average now is 9 % of the companies that are already using OpenAI and using it actively. So I'm sure the average is significantly lower than that. And the most advanced companies have one in every five people using plugins. Again, I cannot imagine my day-to-day without plugins and different connectors and so on. Since February, weekly active users of Codex have grew 108x illegal, 41x in recruiting, and 26 % in marketing. So those of you who think engineering is leading the pack, well, engineering is probably the largest number, but from a growth perspective, it grew 5x in the same amount of time versus again, 40x or 100x to other subjects.
38:27So it's becoming mainstream in more and more aspects of the business, not just running code. Now, what they did not share is what kind of financial tangible results these companies are actually gotten from using more tokens, which is to me, the biggest question, but that was not a part of this research, either intentionally or not. I'm not 100 % sure. Now we're going to talk about many, many, many new releases that happened this week. The most interesting one is Grok 4.6. So SpaceX AI, also known as, or formerly known as XAI before their merger with X, have released a new model that is either the top model today or very close to that.
39:07It achieves benchmark scores that are at the top of everything. So as an example, on the Artificial Intelligence Index, it is matching GPT 5.6 SOL max. So the top model from ChatGPT scoring 61. On GDPVAL version 2, which is an evaluation that is supposed to test real live results, it scored 7 versus 1728 of GPT 5.6 SOL. It also leads benchmarks such as the AA a briefcase in Harvey Lab, and it secured the number one spot on Databricks leaderboard. So what does that tell us without diving into more details? Very little because it's benchmarks, whether that will translate into actual real life results.
39:49There are mixed feedback so far that I've seen. Some people are saying it is really, really capable. Some people are saying that it is capable, but not as capable as these other models in real life. What is clear is that SpaceX AI has closed the gap. So whether they are ahead or not, they came back from a very far behind OpenAI and Anthropic to competing at the frontier at this point. I would say that OpenAI's investment in Cursor is definitely paying off because before that, we saw them lagging further and further behind. Elon Musk admitted it out loud. He said they need to do a better job. They need to take a different path.
40:28And then they went ahead and spent presumably 60 billion on Cursor. And now they released a model just a few months later that is roughly as good, doesn't matter if a little bit behind or ahead, roughly as good as the leading models from the top labs. This is exciting for us because it means more competition, especially that this model is dramatically cheaper than Sol 5.6 Max, even after OpenAI cut their rates last week, and it is way, way, way cheaper than Claude Opus, definitely Claude Fable. Another company that made a big release this week is DeepSeek. DeepSeek released DeepSeek version 4 Pro, which has a 1 million token context window and is, again, delivering results on benchmarks that are very close to the frontier at a fraction of the cost of everybody else, including the new model from SpaceX AI.
41:22so their input tokens is 0.435 cents for a million tokens and 0.87 for output tokens. That is less than a quarter of the next model up on the list that we just talked about, which would be SpaceX AI at over$2 for input tokens for every million. Now, same kind of thing. There's been mixed results on how well it actually performs in real life, whether it is as good as the frontier or not. And I said that multiple times on this show. I don't think it matters. I think it is good enough for most knowledge tasks in the world today, definitely the day-to-day of most professions. And if you can do this at less than half a cent for an input and less than a dollar for output million tokens, why would you pay 2x, 4x, 20x, 50x, that amount to get models that do things better, but not necessarily worth the additional investment?
42:11Another company that released a bunch of new models this week is NVIDIA. They just launched Nemotron 3.5 Lighting, which is a 30 billion parameters mixture of experts model with 3 billion active parameters on Pinch, Bench, and other benchmarks. But let's focus on this one first. It demonstrated 86 % accuracy while completing 10 ,000 tasks, 30 % faster than QEN 3.6. And for long-running reasoning tasks, it was over 57%, much faster than comparably sized QEN 3.5. So they're not trying to compete with the Frontier. They're trying to compete with models their size, and they're doing this very successfully while being cheap and fast.
42:49Now, this model, like I said, is not supposed to be the top of the line. It is built specifically to be the execution layer of always-on AI agents, which is everything that everybody's talking about. And as I mentioned on these benchmarks, it is actually scoring really well. Now, the model was released with a permissive OpenMDW 1.1 licensing, which means it provides weights, training data, recipes, which allows developers to fine-tune the model, just like all the previous Pneumotron models from NVIDIA. Staying on new releases or new versions, OpenAI just introduced what they called ultra-fast model for 5.6 SOL, which is delivering 14x speed boost on 5.6 SOL capabilities.
43:32Putting things in perspective, it is supposed to peak at 750 output tokens per second. If you think about 750 tokens, that is about 500 words in English every single second. That is speeds that we're not used to running on regular internet connection, not on dedicated hardware. Now, how are they doing this? Through a Cerebrus partnership, which is one of the companies that knows how to do very fast inference. And so this partnership enables this model, which means you can do things a lot faster and pay OpenAI a lot more money, a lot faster, because you consume tokens 14x faster as well. The cool thing is what it's actually doing, it is achieving the same results as the full regular Sol 5.6.
44:17So it is achieving those really fast capabilities without degradation in the quality of the output, which makes it very, very attractive if you don't care about spending your money faster as long as it gets you the results in a faster speed, which I believe is most people. Andrew Feldman, the CEO and co-founder of Cerebrus, said GPT 5.6 on ultra fast is a proof that speed and intelligence are no longer mutually exclusive. So there you go. That's a great summary for this topic. Now, a company we haven't heard from for a while on launches or at least interesting big launches is Google. Well, Google just launches Gemini 3.7 Flash, which is a major performance increase for coding and AI agents at a 50 % lower cost.
45:02That is great news for Google, but it is definitely not trying to compete with the frontier. This is just their attempt to compete on price on a lower tier model. They are currently running it until December 31st of this year at an introductory price of 0.75 cents per million input tokens and 3.75 per million output tokens. So while this is amazing compared to other Google models, it is, as you can understand, not competing with the top open source models from China. Is it better or not? I'm not 100 % sure yet. I haven't seen any real comparisons from any viable sources, but it is hopefully showing first signs that Google are moving in the right direction with the new shakeup and hopefully will release better and better models that will put them either close to the frontier, which they're very far behind right now.
45:55As I mentioned, if you just go a year ago, It was very much a three-way race with OpenAI, Anthropic, and Google. And now Google is very far behind. We have three American companies, OpenAI, Anthropic, and SpaceX AI, and a lot of Chinese models that are very, very close to one another, at least from a benchmark perspective. And speaking of Chinese models, Zifu just released GLM 5.3, which has better performance than the mind-blowing GLM 5.2 that we talked about very recently as their previous release. It is approaching CloudFable 5 in some tests. As I mentioned, this is, again, benchmark, not necessarily live work, but it is a very capable model built on top of GLM 5.2.
46:38So it's not a new technology, but just improvements on the previous already very good model. An interesting release that is related to how companies will potentially use AI in the future comes from Pokey. So Pokey releases Isaac 28B, which is a million tokens context model. built for regulated industries and supposed to run on on-premise deployment. So the idea here is you don't need the top of the line model, but you do want to run it on your local hardware. And you do want all the content to be yours without going into any other cloud computing. And you do want to run huge amounts of data to it.
47:13And this is exactly what this model develops. So a niche approach that I think get more and more interest as the AI space grows and becomes available to more and more companies in more places around the world. Now, the next three models that we're going to talk about are from the visual generation world. ByteDance just released Seed Real Time, which is a unified audio visual LLM that collapses the pipeline into one end-to-end model. What this model can do is it can do really amazing things when it comes to conversational and ability to understand voice, respond to voice, and be fully interactive in voice and video, in noisy environments, in problematic positions, in problematic visual conditions, and so on.
47:59And all of that while integrating all of these capabilities into a single model versus several models that have to go back and forth and back and forth in order to create not even as good capabilities. Another company in that space that has launched a model this week is LTX. They just launched LTX 2.5, which is an open weights world model that targets films, robotics, and real-time AI. And then the third company in that category that made a release this week is Alibaba. They just launched a better version of One 3, an advanced AI video generation model that is offering 30 second clips from a diverse range of multi-model inputs.
48:37So it can get voice or text or images or videos as inputs and generate really amazing videos. And if you go and check out the demos online, they're very, very impressive. And like I said, up to 30 seconds of videos, which is doubling the rate of their previous model, 1.2.7. It can do it at 1080p, which is a full HD resolution. So very powerful, very capable model to generate videos. More and more of those are just coming out, seems, every single month. And so the ability today to tell the difference between what's real and what's not real on videos is practically zero, going back to one of the points earlier that we discussed that has to do with how the hell do you tell the difference if it doesn't have any kind of watermarks that will tell you that what you're watching is real or not.
49:21We also got new image generation models from Grok. So Grok released their latest version of visual generation models that is doing extremely well. Microsoft launched their image 2.6 that jumped to number two in the text to image ranking on the ranking tables. So you have a lot more options basically than just using Chachapiti or Gemini Nano Banana right now when it comes to generating images from multiple different vendors. That's it for today. In the newsletter, you will find significantly more articles. A big thing that I considered reporting as part of the episode today, but I pushed to the newsletter, is crazy amount of insane valuations and funding that started happening this week.
50:07So if you want to learn more about what's happening in the funding world, and if you want to know more about a lot of other stuff that happened this week, like I said, I could have recorded probably six episodes this week, go and check out the newsletter. Also go and check out the multi-agent orchestration course. There are links to both of those on our website. in the show notes. On Tuesday, I'll be back with another how-to episode. As I mentioned, I'm considering if I have time to record a full episode about GrokBot and telling you how to use it and what it can do and show you some examples.
50:32But if not, we have other stuff to release. But that will be it for today. Have an amazing rest of your weekends and we'll see you again on Tuesday.
50:51Thank you.
From the publisher
What happens when the companies building the world’s most powerful AI systems start losing senior leaders at the same time their models are becoming dramatically more capable?
This week’s AI news points to a market entering a new phase. Leadership changes are accelerating across major labs, AI agents are becoming easier for everyday users to deploy, and increasingly capable models are raising bigger questions around security, responsibility, and the future of work.
For business leaders, the takeaway is clear: the AI race is no longer just about who has the best model. It is increasingly about who can turn powerful models into reliable products, deploy agents safely, attract the right talent, and translate rapidly advancing capabilities into real business outcomes.
In this episode of the Leveraging AI podcast, Isar Meitis breaks down the developments that matter most and explains why they should be on every executive’s radar.
In this session, you'll discover:
- What the wave of senior leadership changes across leading AI companies could signal about the next stage of the AI race.
- Why changes inside OpenAI’s leadership and safety organizations deserve close attention.
- Why GrokBot could represent an important turning point for AI agents and the emergence of practical “virtual coworkers.”
- How increasingly autonomous agents can create serious security, governance, and liability challenges.
- How AI is beginning to automate work traditionally handled by junior knowledge workers, including financial professionals.
- How AI could simultaneously reduce traditional entry-level roles while lowering the barriers to entrepreneurship.
- Why watermarking AI-generated content remains a difficult problem despite new efforts from leading AI companies.
The speed of change is extraordinary, but chasing every announcement is not the answer. The opportunity for business leaders is to understand which developments actually change what AI can do inside an organization—and where new capabilities introduce risks that require stronger oversight.
:::
About Leveraging AI
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