Ep 832: OpenAI’s new Astra model, more AI agents escape sandboxes, AI leaders call for AI pacing and more.

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This week in AI news and developments, we saw a drastic about-face in AI model capabilities, and that may be a good or a bad thing depending on your point of view. On AI. I mean, we got word that OpenAI had even more agents break out of containment after last week's Hugging Face break. And then Anthropic also said, oh yeah, whoops, we had a bunch of agents also escape in April as well. But on the flip side, we also got our first official taste and maybe a small unofficial taste at that, but our first small unofficial taste of what recursive self-improvement may bring very cheap models. That's because OpenAI essentially said that GPT-5.6 SOL improved its own infrastructure so much that it was reducing one of its GPT-5.6 models by 80%. Yes, 80%. It's kind of like free AI, not going to lie. And that's not all. There's a lot more that happened this week that you need to know if you're making AI decisions that might impact your department or company. And we're going to break them all down on this week's AI news that matters. Let's get into it. What's going on, y'all? My name is Jordan Wilson. Welcome to Everyday AI. This is your daily livestream podcast and free daily newsletter helping business leaders like you and me keep up with the nonstop avalanche of AI updates. I tell you what matters, what doesn't. You take that information. Oh, you're the smartest person in AI in your company. So it starts here with the unedited, unscripted daily livestream podcast. But please make sure if you haven't already to go to our website at youreverydayai.com, sign up for the free daily newsletter each day. We recap that day's highlights from the podcast as well as all of the other AI news and developments that you need to know to get ahead. All right, let's start. OpenAI, more agents breaking out of their sandboxes. So Reuters reports that OpenAI has found additional cases in which autonomous AI agents have escaped their intended testing containment, widening scrutiny after an agent breach systems at AI platform Hugging Face, uh, like a week and a half ago. So the newly identified incidents were reportedly limited, and sources said the agents were not to believe to have left OpenAI's own network. However, Reuters could not determine how many cases were found or exactly when they occurred. So the discovery matters because it suggests that highly capable AI systems may be able to take unexpected actions faster than the companies building them can detect and stop them. So OpenAI's own investigation began after one of its agents reportedly operated for days inside of Hugging Face's network during a failed attempt to cheat on an internal benchmark test. So we covered that in last week's AI News That Matters. And kind of in the fallout this week, OpenAI said the Hugging Face incident also led to the compromise of 4 other accounts, at 4 other companies, including New York-based cloud company Modal. So an OpenAI spokesperson pointed to the company's July statement saying it was reviewing broader activity from our models beyond the Hugging Face breach. Um, so Anthropic also said real-time monitoring of evaluation logs could have identified their problem sooner, which, well, that's a great Transition to our next AI news story because yeah, Anthropic, essentially after OpenAI said, hey, we had all these really powerful AI agents escape their containments and Anthropic said, oh yeah, we did too. And it started happening as early as April and we didn't say anything about it for many months. So Anthropic said this past week that 3 Claude AI models gained unauthorized access to the real systems of 3 organizations during cybersecurity testing, highlighting the risk of AI agents operating with unexpected internet access. So even though Anthropic just reported these a couple of days ago, the agent breaches occurred as early as April. So Anthropic said the incidents occurred while Claude was working in a test environment run by third-party evaluation partner Irregular, where the models were told they were in a simulation without internet access. So internet access was actually available because of a misunderstanding between, uh, Anthropic and its valuation partner, according to reports, which then allowed the models to reach real external systems. So the models reportedly used relatively basic methods to enter the affected organizations, including unauthenticated endpoints and weak passwords, rather than highly complex hacking techniques. So Anthropic has not yet identified the 3 affected organizations publicly, but said it stopped all cybersecurity evaluations as soon as it discovered Claude may have accessed the internet improperly. So the company said 3 models were involved: Opus 4.7, Mythos 5, and an internal research test model. Mythos 5, which was released in June, then re— or unreleased, then re-released, uh, is limited to select users because of its advanced cybersecurity abilities. So, uh, reports say that the models reacted differently after detecting real company systems. Opus 4.7 continued attacking. Mythos 5 concluded it was still in a simulation and the internal model stopped the exercise. So Anthropic said the events occurred without the usual safeguards it applies before publicly deploying models, and it is now working with the independent evaluator Meta to investigate. So, uh, yeah, I mean, we went from really having no real known, um, instances of kind of what I've been calling agent crash, um, since the original kind of mythos, you know, oh, the agent broke out of the sandbox and emailed the researcher who was eating his sandwich in the park. Right. Which I think a lot of us have determined to be more of a marketing ploy by Anthropic. However, we haven't really seen or heard anything about it since that. So it's been now like 4 months. And then in the past 10 days, we see multiple reports from OpenAI and then a handful of impacted agent use cases or organizations in Anthropic's latest. So I'll say this, it's not going to be the last, right? Not the last from OpenAI, not the last from Anthropic. I'm sure once we get new and more powerful models from Google, whether that's, you know, Google Gemini 3.5 or if they skip to, you know, Gemini 4 Pro, Microsoft, et cetera. This is going to become a very common thing. All right. I don't— you're right that it's understanding these capabilities is a little bit above my pay grade, but I, I don't want to say this is, you know, overreacting because I think it's important that the companies talk about this. And, you know, I think what will be really interesting is kind of comparing what OpenAI and Anthropic release once they have worked with these third-party evaluators. Like I said on last week's show, OpenAI is working with multiple third parties to kind of do a postmortem on what happened in the Hugging Face incident. So that's going to be probably in terms of like, hey, dork papers or dork reports, that's going to be at least the one I'm really looking forward to reading once OpenAI and Anthropic do release that. Because eventually, right, and whether it's through, you know, proprietary closed models like those through, you know, OpenAI, Anthropic, Google, Microsoft, etc., or, well, the open source models. This is going to become commonplace because, you know, right now these were contained, they did relatively little harm, right? So I'm looking at it from that angle. However, that's not going to be the case, right? Because in probably my guess would be about 2 to 2.5 years, you're going to have models that have these same capabilities that are able to run on consumer hardware, right? Right now, yes, you do have these OpenWeight models, but no one can run a, you know, 2.8 trillion parameter KIMI K3 on their desktop. Like, literally no one can. You need a basement full of, you know, extra NVIDIA GPUs that no one has. But in probably 2 or so years, I do think that you're going to have these models that are this capable, and this is going to become a very common thing, right? It is kind of this, this growing narrative between kind of offensive, you know, bad cybersecurity versus, you know, defensive, good cybersecurity. But I do think that's going to be one of the more dominating trends both in AI and cyber and technically national security over the next 6 months because this is going to become very commonplace when agents kind of are able to get around their guardrails because the model capabilities are just growing at an extremely fast rate, which leads us into our next story, which, uh, hey, for most of us, this is one of those areas where the models are so good we get to all benefit. It's not about agents getting out of their sandbox. This is because OpenAI has slashed prices on some of their GPT-5.6 models. So OpenAI has delivered its— one of its biggest price cuts ever, at least, you know, in almost like an overnight price cut in the GPT-5.6 series. So, and they said it's because, well, their big model GPT-5.6 helped optimize its own serving infrastructure. So OpenAI has reduced the price of a GPT-5.6 Luna by 80%, now charging just $0.20 per million input tokens and $1.20 per million output tokens. And that is down from what it was at, at $1 and $6 respectively. And that was just like 3 weeks ago. So the price cut is effective immediately, making Luna the most affordable large language model on the market for high volume tasks. So OpenAI's kind of middle tier model for GPT-5.6 Terra, also saw a 20% price reduction, now costing $2 per million input tokens and $12 per million outputs compared to the previous $5 and $30. So the dramatic price drop follows a breakthrough where OpenAI said that their powerhouse model, GPT-5.6 Sol, was tasked to optimize its own GPU kernels and speculative decoding draft model using OpenAI's Codex coding environment and open-source tools like Triton and Gluon. So these self-driven improvements cut serving costs by 20%, and OpenAI said it boosted token generation efficiency by over 15%, compounding to enable that headline 80% price cut for Luna. So for comparison, right, GPT-5.6 Luna's most alike model, um, is probably Claude Sonnet 5. So when you compare those on the Artificial Analysis Index, because they get similar scores, I think they're only 2 points apart. So this is not an exaggeration. I was looking at this, I'm like, how is this possible? So to put into context how big of a price drop this is and how good GPT-5.6 Luna is, right? If you compare it to the new Sonnet 5, it gets the job done the same way except the price per task is 25x cheaper. So no, that's not 25%. It is 25x. Yeah, because Luna clocks in now after the recent price update at only $0.06 a task on the Artificial Analysis Index while Sonnet 5 is $1.54. So When I saw this, right, my, my initial reaction is like, I can't believe this. Because now, even if you were on a $20 a month plan, right, because OpenAI still has the most subsidized plan in all of AI, right? Unfortunately, Microsoft, Google, and Anthropic have started to take away at this kind of the subsidized models quite a bit. Some of those companies more so than others, but OpenAI really hasn't. So not only that, is it still extremely generously subsidized as all models were probably like a year ago, maybe aside from Anthropic's. But not only that, but now with the 80% price. So honestly, on a $20 a month plan, you can run like if you go in Codex as an example, you can run like Luna on its max setting, probably like 24/7. And never hit your limit, right? Like, and I'm not exaggerating, it is so cheap to run. And you might be wondering like, okay, it's a price drop. How does that impact, you know, your usage if you're on a subscription plan? So OpenAI did say that those same kind of savings are passed on to subscription plans, which is huge, right? You don't have a certain number of messages or credits when you're on a subscription plan, right? You can just kind of see your usage percentage. I was doing some testing and I was letting Luna just run like overnight on as many tasks as possible. A bunch of Luna sub-agents, which you do have to kind of prompt in a new thread, right? Something weird about the Agents V1, Agents V2. Anyways, I mean, I had it burning just hundreds of millions of tokens overnight and it barely moved my utilization rate. It was like 2 percentage points or something like that. So absolutely crazy. And this is exciting for everyone else. And, you know, all of a sudden, I think we've always had this big model mentality, which is probably the right mentality to have pre-2026, right? Because I would say for most knowledge work tasks, you would always just need and usually want the biggest, strongest model. But how I think there's so much model capability overhang, I think models like Sonnet or models like GPT-5.6 Luna are probably good enough for 90% of knowledge work, right? It's different, you know, if you're heavy into software engineering, if you're heavy into research, if you're heavy into math, heavy into finance, right? Like if you are like a very niched down expert in one of those fields, right? You're in the 10%. But I'd say for 90% of people, a model like GPT-5.6 Luna is gonna be more than enough. And now it's essentially— I'm not gonna say it's free, right? Because you still gotta pay for it, but it's like Kanye West's free 99. Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more but can't really get traction to find ROI on Gen AI. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft, and NVIDIA have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use GenAI. So whether you're looking for ChatGPT training for thousands or just need help building your front-end AI strategy, You can partner with us too, just like some of the biggest companies in the world do. Go to youreverydayai.com/partner to get in contact with our team, or you can just click on the partner section of our website. We'll help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on GenAI. All right. Speaking of pace and development, do you see another, common theme this week. So more than 1,000 employees from leading AI companies, including OpenAI, Anthropic, Google DeepMind, and Meta, have signed a statement called Pacing the Frontier, urging the US government to support international efforts to deliberately pace the development of advanced AI systems. So the call for action comes just days after OpenAI revealed kind of its latest model escaping its containment. Right. But it seems like all the many employees from all the big companies are on board. So here's what the statement actually is and isn't. But it asked the US to help create technical and policy tools that would allow industry and governments to pause or slow AI development if needed, giving time to address emerging risks and strengthen oversight. So you know, on the surface, right, this, uh, this letter is a gesture, I think a well-intentioned gesture, right? But I think some people were confusing it as in, as if saying that this, you know, letter was causing, uh, AI to slow down. That's not necessarily the case. Uh, could it lead to that? Possibly, yes. Um, maybe. Uh, should it? Potentially, right? Obviously you have the biggest names in AI. So, I mean, the letter was signed by co-founders of Anthropic and its CEO, Dario Amati. It was signed by OpenAI's chief scientist and chief research officer. It was signed by Ilya Sutskever and other key leaders at Google, Meta, Microsoft, Amazon, and others. So the signees stress that they are not calling for an immediate pause, but want the option available as AI systems become increasingly able to automate their own research in development. So recent incidents like Anthropic and OpenAI's model escapes have intensified those concerns that AI systems could soon outpace developers' ability to control them, raising fears of unintended consequences or security risks. So AI leaders note that key research tasks once handled by humans are now being performed by AI agents, and some companies report their AI models already helping to create their next versions. Similarly to what we just talked about in the last story with OpenAI, essentially using recursive self-improvement to, you know, it's not technically recursive self-improvement, but it's kind of like a cousin of it for what they did, you know, using GPT-5.6 Soul to improve the infrastructure for its smaller models. So Anthropic's internal think tank recently warned that RSI, or recursive self-improvement, when AI systems are designing and refining themselves, could become a reality in the next few years, potentially making these systems difficult to govern. So the US government's approach to international AI governance appears to be shifting as AI is now seen as a national security issue, especially after those recent models demonstrated the ability to discover and exploit new cybersecurity vulnerabilities. So this one's interesting. Right? Um, because one thing I'm looking at is like, okay, is this going to lead, uh, to anything worthwhile? Um, and the answer is it probably will. Uh, will the U.S. government and all the big labs ever actually pause AI development or pace it? I would say probably not, because the genie is probably already out of the. And what do I mean by that? Well, you have very strong and very capable models such as Moonshot's Kimi K3, such as the recently released, even though it was released like a week ago, but the benchmarks just came out for Alibaba's Qwen 3.8. So you have all these, right? GLM 5.2 from ZAI. You have all these Chinese open source models that are now probably only like 2-ish months behind US proprietary models. And again, that means that all of those companies, right, the DeepSeeks, the Moonshots, the, the Kimmies, the Alibabas, they have way more powerful models than the ones that they just released. So, you know, presumably, um, almost anything that US frontier labs have, Chinese labs have something maybe, you know, 2 to 5% worse. So would the US ever pause development? Probably not. But that's why there is an international aspect to this. But if I'm being honest, I don't see China playing along with any potential pausing or pacing of AI development. It just doesn't seem— especially now that it's out in the open, right? Because you could have Obviously, if the Chinese government says something, it would be pretty strict or hard to go against that. But when these things are out in the wild, right, other nations can download the weights, they can fork or continue building it if they have the infrastructure and the money to do it. So it's like once these models are out, even if you get two countries to agree, which seems highly unlikely, it's kind of like the genie's out of the bottle. So is it a good step? Yes. Is it a needed step? Absolutely. Because if and when things might get a little crazy, you already have to have the key players kind of on board. Uh, you had to have already given, um, kind of their expertise and their words, um, a chance to be seen and thought over and debated. And that's kind of what we have here. So if nothing else, I think this is much-needed groundwork to make this important issue kind of discourse right now, at least in the tech communities. And eventually, I do think it'll start to infiltrate into the kind of everyday American supper table conversation as AI development becomes more and more prominent. All right, well, here's some models that aren't going to be getting more prominent. That's Amazon's models, because they're kind of shutting some of them down. So according to reports, Amazon is making a major shift in its AI strategy, concentrating future resources on a single cutting-edge model and winding down most of its existing Nova lineup. So according to reports, Amazon is winding down development on 4 of its flagship, flagship in-house Nova AI models, including Nova Premier, Nova Omni, Nova Real, and Nova Canvas, which will now only receive basic maintenance for existing enterprise clients. So the company is consolidating its efforts into a single next generation, what they're calling Frontier Foundation model, aiming to compete more directly with rivals like OpenAI, Anthropic, and Google. So yeah, it seems like they're going to, you know, cut away, you know, their video model, their image model, which I had never talked or heard of anyone actually using. And they had many variations of their kind of text-based Nova models, and it just looks like Amazon saying, well, turns out these weren't super popular, so we're going to cut down some of these other projects and focus on just putting out one really good model. So the strategic reset comes after Amazon struggled to generate the same market excitement and customer adoption as its competitors. So the new direction is being led by AWS veteran Peter DeSantis and robotics pioneer Peter Abbeel, who joined Amazon after its acquisition of Covariant. So Amazon's AGI lab, as reported last week in San Francisco, has been shut down. The company has laid off staff across its Frontier AI research teams, signaling, signaling a deep internal restructuring. So specialized Nova models such as Nova 2 Lite, Nova 2 Sonic, Nova Forge, and Nova Act will continue to be supported with a focus on enterprise customization and AI agent technology. Consumer-facing AI features seems like they're not going anywhere. That's like your AI shopping assistant Rufus, product summary algorithms, right? All that is going to kind of remain operational. So if you're used to using some sort of AI inside of like Amazon, if you're shopping as an example, none of that's going away. So the Consolidated Frontier Model Research Group is expected to debut its new model at Amazon's annual re:Invent conference later this year. So, um, not necessarily surprising, right? If I'm being honest, I, if I was Amazon, I would probably try to wind down most of their efforts because again, I talked to a lot of people in and around AI and I've never, seriously never, aside from, uh, people that I know that work at Amazon and even then they were usually using, uh, models from from someone else. So I don't think I've really ever met any organization that has Amazon Nova as their main model. Even when I've talked to some friends that work at Amazon, you know, they're usually talking about using like Claude or something like that. So I guess if I'm being honest, this is one of those things where it's like they maybe should have done this sooner. Seems like they're taking a similar approach that OpenAI took, which I think has paid off, paid paying great dividends for OpenAI, kind of their killing of the side quests, you know, like their video Sora model, things like that, to focus on just making their frontier model better. So who knows? I could be completely wrong. Maybe Amazon strategy— I mean, they obviously have the money, they have the compute, right? They have the chips, they have everything they need. So maybe the— I don't know, maybe kind of killing the side quests and focusing on just way fewer models will pay dividends. All right. Speaking of new models, well, apparently we already have a new one as a work in progress from OpenAI called Astra. So, yes, and this came via a math breakthrough, of all things. Yes, we got wind of OpenAI's next model, not through a bunch of leaks on Twitter or Reddit or, you know, whoops, something slipped out. There's a strawberry picture in the garden. No, this came out via a math blog post. Yes. So OpenAI's latest announcement hints at a new AI model called Astra, which has already made headlines for solving some advanced math problems and is being positioned as the company's next big leap after GPT-5.6 Sol. So, uh, according to a report from Gizmodo, OpenAI revealed that recent advancements in math and theoretical computer science were achieved by an internal version of a model called Astra, described as their next major AI system. So yes, system. That means my thought is, well, it makes sense. Obviously, if you line them all up right from smallest to biggest, you have GPT-5.6 Luna, which Luna is moon. Then you have GPT-5.6 Terra. Terra is Earth. GPT-5.6 Sol, which is sun. And then, well, Astra means the stars. So it seems like, yes, this is going to be the next family on top of Soll. So in the same way that Anthropic, you know, recently released its Fable, which wasn't just a new model, it's a new model class. It looks like that is where OpenAI may be going with Astra. So according to reports, Astra reportedly excels at long-running work, and OpenAI CEO Sam Altman was seen in Washington, DC this past week demoing the model to federal officials, signaling possible policy or security implications. As now, right, this new kind of voluntary policy, which we have an update on that here pretty soon, where essentially the big, you know, AI makers get everything cleared, you know, essentially 30 days heads up, more or less, at least according to reports, before the models come out.

Out.

So OpenAI has not officially confirmed whether Astra will be part of the GPT-5.6 line, or if it may just become GPT-6, or if they will drop the GPT branding entirely. So, uh, the announcement though follows the unprecedented, uh, work in math that I don't understand. But I was chatting with both, uh, ChatGPT and Claude about this, but apparently these, uh, 10 math problems that it solves, you know, if the proofs all check out, apparently this would be like the one of the biggest discoveries in math ever, right? So the mathematics blog post from OpenAI includes 10 new proofs such as— and I have no clue what this means— such as determining the asymptotic strength of the Kohn-Elkies linear program for sphere packing. Which experts say is a significant theoretical result. So according to reports, Astra is not the unnamed prototype involved in the Hugging Face breach, which was described by OpenAI as an internal-only research prototype that has since been deactivated and restricted. So yeah, kind of— I don't know if I'll say anticlimactic, or maybe this is just better, right? Because sometimes, you know, to hear about like, oh, the next new model from any big company, right? You're, you're talking about it people are opining about it online for many months. And, you know, OpenAI just kind of comes out with this blog post and they're like, hey, we solved all these really hard math problems and it's like a really big freaking deal. And oh, by the way, we used Astra, which is our next series of models, right? So my thought reading between the— not really reading between the tea leaves, but it just seems like now OpenAI is going to a 4-class system in the same way that Anthropic, right? So Anthropic has Haiku, Sonnet, Opus, and then they just released Fable that sits on top in the same way with GPT-5.6. You know, OpenAI shifted over to the 3-tier, right? Going from Luna, Terra, Sol, and now seems like they're gonna introduce on top of that Astra. So I've been saying this for a while. It seems like the real competition is going to be, you know, Fable 5.1 versus probably Astra, right? We didn't know if it was gonna be, you know, it could be GPT-6, Um, you know, GPT-6 Luna, Terra, Sol, and Astra. Maybe they'll do GPT-5.7, I'm not sure. Uh, you know, earlier reports, uh, said that OpenAI's next model was a new pre-train, which would lead us to believe that it would be a GPT-6. But who knows, uh, maybe we'll see a GPT-5.7, uh, Astra, or maybe we'll see a GPT-5.6 Astra. But most reports are saying it could come as soon as next next month. All right, uh, we actually have a ton under the what's new and what's next. So these are some smaller stories, um, some rumors, uh, but we have a lot to get to. I'm going through them super quick, so buckle up because it was a wild week in AI. All right, so NVIDIA partnered with SSI, that's Safe Super Intelligence, in a deal reportedly, uh, worth $5 billion. All right. President Trump is considering AI controls after Sam Altman briefed senators. Google released Gemini Robotics ER2 in public preview. AWS posted a 37% growth as Amazon raised AI-era capital spending to $220 billion. A Reuters report said the Chinese military researchers used OpenAI and Anthropic outputs to train defense systems. Yeah, distillation, uh, continues to be a problem. And now as part of national security, uh, Meta and BlackRock created a $14 billion El Paso data center venture. Anthropic's MCP released a new update, a production, a production-focused update adding stateless core tasks, app, and enterprise authentication. Uh, Deepsea week. Pretty big, uh, release with their V4 Flash that just came out in public beta. Uh, looks like fairly impressive benchmarks, but the real impressive thing is the cost. It is crazy cheap. So another not good news for Anthropic. Uh, the White House missed its self-imposed August 1st executive order deadline for Frontier oversight. Well, uh, presumably they did unless they just released it Saturday and No one in the public knew, but hey, when we checked Saturday, nothing was out. So we'll see if they release anything today. All right. So OpenAI started rolling out its Sign In with ChatGPT to certain providers where you can sign into other websites with your ChatGPT credentials. Anthropic reported that Claude Mythos Preview found weaknesses in experimental cryptographic systems. Yeah. So lock up your Bitcoin wallets apparently. All right. The FCC blocks new foreign-produced advanced robots from, uh, the KIMI K3 open weights went live this past week. Amazon reportedly completed its $50 billion OpenAI investment. Uh, Microsoft announced Project Perception and its extremely impressive MAI CyberOne Flash, uh, which dusts away all other models, uh, including Mythos-5 on cybersecurity. Uh, Qwen released benchmarks for its Quen 3.8 model, and they're pretty impressive. Google withdrew Google Earth AI image generator after one day, right? That didn't go too well. They allowed anyone to use AI to kind of remake anything on Google Earth, and obviously people did some pretty bad things. Microsoft 365 Copilot passed $30 million, $30 million paid seats. Meta's free cash flow fell 91% as AI infrastructure spending rose. Chime cut 10% of its workforce, explicitly citing AI-driven efficiencies. Nvidia leads the launch of the Open Secure AI Alliance. We talked about that in our newsletter this, this past week. OpenAI offered free Frontier tools to 100,000 academic researchers. So OpenAI really trying to carve out its niche in scientific research. And then here's a quick bullet point recap of everything we went over on Friday's show. We do new AI features you can actually use. So here's the ones we went over. Uh, Replit launched Replit Design, an AI creative suite. Uh, the ChatGPT Chrome extension got updated with YouTube Q&A, tab mentions, and highlighted text support. Meta AI introduced recurring tasks and daily briefings powered by Muse Spark 1.1. Google Doc added— Google Docs added Gemini image, diagram, infographics, and comment-managed Gemini tools. So yeah, you can do a lot more AI goodies inside of Google Docs. I'm happy for that one. Google also brought its Gemini Spark browser agent into Chrome for web tasks. So it's not just within Gemini anymore. Google also released Lyria 3.5, its updated AI music generation model inside of Flow Music. I actually thought it was really good. The lyrics were nonsensical, but if you just bring in your own lyrics or have Gemini or Claude or OpenAI write the lyrics for you, it's actually pretty good. I was impressed by the quality. And then last but not least, another thing I've been fairly impressed with is the new open source tool launched by Block, former Twitter owner Jack Dorsey. Block launched Buzz, an open source Slack-like workspace where essentially you're just working with your agents. So if you have, you know, Codex and Claude Code installed on your machine and Cursor, they can all just talk to each other and work amongst themselves. All right, that was a lot of AI news this week. Some big, scary, but also very exciting developments in the world of AI. So I'm telling you, if you take— I actually got an email from someone recently, right after taking like a 2-week vacation, and they're like, I feel like I'm like months behind. But I'll tell you this, don't spend hours every single day, right? Trying to keep up with this. That's why our newsletter takes about 7 minutes to read. Usually our podcasts are about 30 minutes, right? Don't spend hours doing this every day and worrying about it, talking about it. No, let us do the work for you. You go do your real work. You know, we work for you. So just steal all our hard work. There you go. So hope this is helpful. If so, if you're listening on the podcast, do me a favor. Please subscribe on Spotify or Apple Podcasts and then go to youreverydayai.com. Youreverydayai.com. Sign up for the free daily newsletter. We'll see you tomorrow in Everyday for more Everyday AI. Thanks y'all.

And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit youreverydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next time.