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The Month AI Woke Up

The AI Daily Brief: Artificial Intelligence News and Analysis

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  • Claude Used In Military Analysis Despite Supply Chain Concerns
    • Anthropic’s Claude was reportedly used to analyze intelligence and run battlefield simulations during US-Israel strikes on Iran.
    • Pentagon still labeled Anthropic a supply chain risk even as Claude supported targeting analysis, creating public confusion. Transcript: Nathaniel Whittemore Welcome back to the AI Daily Brief Headlines Edition, all the daily AI news you need in around five minutes. I said over the weekend as we were covering the Anthropic Pentagon story that we were probably going to have quite a few updates on this one in the weeks to come. And indeed, that is certainly the case. The conflict between Anthropic and the Pentagon slash White House slash Trump slash Hegseth took on a new light over the weekend as the US and Israel launched preemptive strikes on Iran. Now, while some thought that maybe this made that 5.01pm deadline on Friday not arbitrary, and instead driven by the Pentagon’s need for an approved and operational AI system in place Ahead of the Saturday operation, but as per Wall Street Journal reports, Anthropics technology ended up being used in the strikes despite being declared a supply chain risk hours Earlier. Sources said that Claude was used to analyze intelligence, help select targets, and carry out battlefield simulations. To be clear, there are no suggestions that Claude piloted fully autonomous weapons, but the Pentagon has confirmed that this was the first time that autonomous Lucas kamikaze drones Were deployed in an active mission. Their use highlights that autonomous weaponry is part of modern warfare already and doesn’t require the use of frontier LLMs. Additionally, despite OpenAI signing a new deal on Friday, that company’s models were not used in the attack. Katrina Mulligan, OpenAI’s head of national security partnerships, said that that wouldn’t have been possible as the models haven’t yet been approved for use in classified settings. TLDR, in spite of some of the chatter, it doesn’t actually appear that the Pentagon hot-swapped AI models on the Friday night before an operation. As the president said on Friday, there’s a six-month phase-out period where Anthropics tech will remain in military use. Still for some, all of this makes the way that it played out even more confusing and contradictory. Democrat Congressman Seth Moulton wrote, Friday, the Pentagon claims Anthropic is a national security risk and should be blacklisted. Saturday, the Pentagon still uses Anthropics Claude during its strikes on Iran. Either they used tech that is a NATSEC risk during military action, or they lied in the first place. (Time 0:00:59)
  • OpenAI Secured A Historic $110B Strategic Round
    • OpenAI closed a record $110B strategic round led by Amazon, NVIDIA, and SoftBank and reported 900M weekly active users.
    • Amazon’s $50B investment ties OpenAI to AWS Tranium chips and expands server rental deals and model partnerships. Transcript: Nathaniel Whittemore The round ultimately totaled $110 billion, valuing OpenAI at an $840 billion post-money valuation. The valuation positions OpenAI as the most valuable startup ever and the 15th most valuable company in the world. They are now worth slightly more than JPMorgan Chase. Notably, the round remains open and OpenAI expects another $10 billion from financial entities, including UAE investment fund MGX, by the end of March. The $110 billion is entirely from three corporate strategic partners. NVIDIA and SoftBank invested $30 billion each. Details were a little scant on this front, but OpenAI mentioned the NVIDIA strategic partnership includes additional chip supplies. But the largest investor was Amazon, who put $50 billion into the round. This investment is split between $15 billion due at the end of March, and a further $35 billion contingent on OpenAI going public or hitting unspecified milestones. Previous reporting rumored that these milestones included achieving AGI. I don’t know why these companies keep putting a term as nebulous as AGI as a condition on their contracts. It’s just going to make lawyers rich later. Now, overall, the Amazon strategic partnership is wide-ranging. OpenAI will expand their server rental deal with AWS from the previously announced $38 billion over 7 years to $138 billion over eight years. As part of the agreement, OpenAI has also committed to use Amazon’s Tranium 3 and forthcoming Tranium 4 chips. OpenAI and Amazon will also jointly develop AI models to power Amazon’s consumer apps. The Amazon deal also has some interesting implications for Microsoft, who notably did not make a further investment as part of this round. Microsoft continues to hold the exclusive right to serve so-called stateless versions of OpenAI’s models, and the revenue sharing agreement also remains in place, so Microsoft Will take a cut of revenue generated through AWS. Amazon will be the exclusive provider of OpenAI’s Frontier AI agent management tool, aside from the first-party deployment. However, the OpenAI-branded version of the tool will be hosted on Azure. Alongside the fundraising numbers, we also now learned that ChatGPT has 900 million weekly active users. The last reported figure was 800 million in October, and reports suggested that stagnating user growth had been part of the trigger for Sam Altman’s Code Red in December. The announcement underscored that subscriber growth is also strong, now reaching 50 million. Writes OpenAI, subscriber accelerated meaningfully to start the year, with January and February on track to be the largest month of new subscribers in our history. People use ChatGPT to learn, write, plan, and build. As usage scales, the product improves in ways people feel immediately. Faster responses, higher reliability, stronger safety, and more consistent performance. (Time 0:06:15)
  • Get Agents Certified To Win Enterprise Adoption
    • Enterprises should seek third-party certification for agents to unlock adoption, focusing on data, safety, and accountability.
    • AIUC1 and Eleven Labs’ certification show insurable real-time guardrails and full safety stacks enable enterprise trust. Transcript: Nathaniel Whittemore It’s called AIUC1, and it builds itself as the world first AI agent standard. It’s designed to cover all the core enterprise risks, things like data and privacy, security, safety, reliability, accountability, and societal impact, all verified by a trusted Third party. One of the reasons it’s on my radar is that Eleven Labs, who you’ve heard me talk about before and is just an absolute juggernaut right now, just became the first voice agent to be certified Against AIUC1 and is launching a first-of insurable AI agent. What that means in practice is real-time guardrails that block unsafe responses and protect against manipulation, plus a full safety stack. This is the kind of thing that unlocks enterprise adoption. When a company building on 11 Labs can point to a third-party certification and say our agents are secure, safe, and verified, that changes the conversation. Go to AIUC.com to learn about the world’s first standard for AI agents. (Time 0:09:53)
  • Programming Has Shifted To Goal Driven Agents
    • Agentic AI shifted programming from typing code to spinning up goal-driven agents that plan and execute tasks autonomously.
    • Andre Karpathy and the host noted models since December gained long-term coherence and tenacity, enabling multi-agent orchestration for complex engineering work. Transcript: Nathaniel Whittemore Despite the incredible amount of attention around it, not every month in AI is huge. However, February of 2026 was. This was the month that crystallized for a number of different groups that, to quote one of the viral pieces from the month, something big is happening. And in fact, one of the things that made the month so interesting was the extent to which the broad recognition that something had changed, and that something big was indeed happening, Was the way that that realization cascaded across all sorts of different groups. Let’s talk about the AI insiders first. This is basically the people like you guys, the enfranchised, highly engaged, probably using vibe coding tools type of AI users, who actually pay attention to when new models launch And what new capabilities they have. This is the group for whom basically the period from the holiday break at the end of last year up until now has been a steady realization and embracing of the idea that the generation of Models that came around last November represented something meaningfully different than those that came before. The core and first manifestation of this was of course around software engineering, and one of the people who’s been in the eye of the storm and communicating what so many others have Felt is former OpenAI founder Andre Karpathy. About a week ago, he tweeted, it’s hard to communicate how much programming has changed due to AI in the last two months. Not gradually and over time in the progress as usual way, but specifically this last December. He then goes on to explain exactly what happened. Effectively, he says, coding agents basically didn’t work before December, and they basically do now. As he puts it, the models have significantly higher quality, long-term coherence, and tenacity, and they can power through large and long tasks, well past enough that it is extremely Disruptive to the default programming workflow. Programming, he writes, is becoming unrecognizable. The era where you type code into an editor is done, he says, and instead we are now in the era of spinning up AI agents, telling them what to do in natural language, and then managing their Work. The biggest prize, he says, is about orchestration. How many of these agents can you have going at once in a way that actually adds up to something real? He concludes, this is nowhere near business as usual time in software. And I think this does a pretty good job of summarizing what has shifted. In short, agents that could actually do work, whom you give not a plan but just a goal, and let them come up with a plan, are now, for many of these most enfranchised users, the primary way That they get value out of AI. And what’s more, in February this was given a name and a face and an icon in what was first named Claudebot, for a very short time named Moltbot, and ultimately finalized as OpenClaw. OpenClaw has been, so far, the biggest, clearest manifestation of the change in autonomy ambition. OpenClaw created a process by which users could give those powerful new generation of models access to their systems and let them actually do meaningful work on their behalf. (Time 0:12:52)
  • OpenClaw Spawned Real Multi Agent Teams
    • OpenClaw users built multi-agent teams for real work, including a 10-agent setup with developers, researchers, and project managers.
    • The host ran a Claw Camp and ~5,500 people joined the self-directed program to reproduce that agent-team approach. Transcript: Nathaniel Whittemore Almost immediately, people were using OpenClaw for much more extensive and much more ambitious, autonomous or semi-autonomous work. I did a show around mid-month about the 10-agent team that I had built, which included one developer agent, two researchers, five project managers, one chief of staff, and a partridge In a pear tree. Because of OpenClaw, Mac minis, and for some even Mac studios, became the hot new visualization of the new era of AI. And again, what’s super important to point out is that despite OpenClaw being very meaningfully not for beginners, something that indeed requires a ton of technical work, and frankly Beating your head against the wall as you sort through just legions of different problems, despite all of that, it was not just developers who were excited about it. It was all sorts of different types of people. I have no better evidence for this than the response to Claw Camp, which is the self-directed program I put together that basically took the process that I had gone through to figure Out how to build both my first agent and then the agent team and turned it into a sequence that other people could follow. It is not an easy sequence. It takes a lot of time and a lot of hard work, and yet nearly 5,500 people are doing it right now. (Time 0:15:49)
  • Pulsia Launched A Million Dollar Agent Company
    • Solopreneur Ben Serra used autonomous agents to create Pulsia, an AI that builds and runs companies end-to-end.
    • Pulsia plugged into GitHub and Meta ads and reached a $1.25M ARR within weeks. Transcript: Nathaniel Whittemore Solopreneur Ben Serra by himself built a company called Pulsia, which is an AI for running autonomous AI companies. Basically, you sign up for Pulsia, give it an idea, or just ask it to surprise you where it’ll go do some research and come up with a relevant idea that seems related to you, and then it will Build a company around it. Pulsia gives it access to everything from GitHub to meta ads, basically everything that you could need to run an online business. The company is up to an annual run rate of over $1.25 million in just a couple of weeks. (Time 0:17:03)
  • Agents Let Non Engineers Build Functional Apps Fast
    • Non-developers rapidly adopted agent tools; CNBC’s Deirdre Bosa built a Monday.com clone in an hour using Claude Code.
    • This showed agent workflows are accessible beyond engineers and drive rapid prototyping. Transcript: Nathaniel Whittemore In preparation for a segment about these new tools, CNBC’s Deirdre Bosa went to try to build her own version of Monday.com with clawed co-work just to understand and share with her audience What’s actually possible. She figured it won’t work, but it would be a good way to show people the current state of the technology. An hour later, she writes, I literally have my own Monday.com that’s plugged into my calendar in Gmail and surfaced a kid’s bidet that was not anywhere on my radar and I need to get a gift For. Finance and markets content creator Joe Weisenthal was actually a couple weeks ahead of everyone else, starting to play around with Cloud Code in a big way back in January, and in many Ways preceding the realization that the rest of Wall Street would have coming into February, because if one group that woke up in February was the AI Insiders, the other group was Wall Street. (Time 0:19:24)
  • Markets Sold Stocks Vulnerable To Agent Disruption
    • Wall Street reacted violently to agent capabilities, triggering the SaaSpocalypse as investors dumped stocks vulnerable to AI disruption.
    • Games, productivity, finance, and legal stocks fell after Anthropic demos and plugin announcements signaled substitution risk. Transcript: Nathaniel Whittemore February was the month of the SaaSpocalypse, and it actually started off at the end of January, when, after Google shared the demo version of Genie 3 where you could create 60-second Immersive worlds, a bunch of gaming industry publisher stocks fell. But that would be just the very beginning. The big actual story of the SaaSpocalypse would end up being that basically every time Anthropic announced some new plugin for Cloud Code or Cowork, a set of stocks that were somewhere Between directly and nominally related to that plugin’s focus would just absolutely crater. On February 10th, Bloomberg wrote that Wall Street’s new hot trade was dumping stocks that were in AI’s crosshairs. And it was not just one category. We saw this in games. We saw this in productivity software. We saw it in finance. We saw it in legal. On February 10th, the Wall Street Journal went so far as to call Wall Street’s hot new trade dumping stocks that, in their words, were in AI’s crosshairs. And remember, this is not just one category. This is games, legal, software, general productivity software, IBM seeing their worst single day drop in 25 years because Anthropic wrote a blog about its COBOL tool, which had been Announced months earlier. All of this was the perfect caustic environment for Citrini Research to drop their highly viral piece called the 2028 Global Intelligence Crisis, which basically articulated a theoretical Doom loop scenario that led to utter economic catastrophe. Despite that report producing a lot of good counter-conversation as well, when in the middle of last week, Block announced that it was cutting 4,000 employees, about 40% of its overall Staff, many pointed to it as evidence of the exact sort of white-collar carnage that the Citrini report was discussing. Now, there has of course been a lot of debate about the extent to which it might be the biggest case of AI washing we’ve seen so far, but this is where the environment is heading out of February And into March. Wall Street is extremely jumpy when it comes to AI, and this time it’s not because of the size or circularity of infrastructure deals, but because AI might be too good. (Time 0:20:08)
  • Anthropic Versus The Government Is A Control Struggle
    • The Anthropic–Pentagon fight revealed an emerging power struggle over who controls AI use and red lines.
    • Disagreement centered on Anthropic wanting contract carve-outs for autonomous weapons and surveillance versus the White House’s “any lawful use” stance. Transcript: Nathaniel Whittemore I just did an extended episode about this, and we talked about the latest in the headlines. But of course, the TLDR is that through a series of steps, seemingly going back to the Nicolas Maduro Venezuela raid, there was a negotiation where Anthropic wanted specific red line Carve outs around AI being used for autonomous weapons and for domestic mass surveillance, with the White House instead wanting the standard to be any lawful uses. Now, of course, this disagreement wasn’t just about these specific uses. It was much more about who gets to determine for what and how AI is used. It was the first manifestation of what was always an inevitable power struggle, even if it happened in a very ugly way. Indeed, before the fight took its most dramatic turn, already members of Congress like Tom Tillis were pretty disgusted around how the whole thing was happening. Tillis said, why in the hell are we having this discussion in public? Why isn’t this occurring in a boardroom or in the Secretary’s office? I mean, this is sophomoric. US government not be working with Anthropic, but that they were going to be designating them a supply chain risk, arguing that that meant that other contractors of the US government Would also have to drop their relationships with Anthropic, which if it came to pass would have some pretty serious and dramatic implications. Now this particular manifestation of the battle itself isn’t even done yet, and again it is just the first in what will be a much bigger power struggle in the years to come. (Time 0:22:10)
  • Some Model Metrics Are Now Off The Charts
    • Opus 4.6 scored so highly on long-horizon tasks that standard progress metrics became inadequate.
    • Meter’s Long Horizon Task Study showed Opus 4.6 was effectively off the charts compared with prior baselines. Transcript: Nathaniel Whittemore Both were high, but Opus 4.6 especially was basically off the charts. At this point, in other words, we are in uncharted territory, where even the metric that became one of the most, if not the most important metric in some ways of showing AI progress last Year, just can’t keep up any longer. And with March now here, we could be heading for something else huge. (Time 0:25:09)