The AI Daily Brief: Artificial Intelligence News and Analysis - Claude Code Killed the AI Bubble

Episode Date: February 8, 2026

For months, critics have warned that AI is a bubble built on hype, overinvestment, and tools that don’t deliver real value. Over the last few weeks, that argument has started to fall apart. The widespread adoption of Claude Code and agentic coding tools has made it unmistakably clear that AI systems can now do meaningful, end-to-end work, not just generate impressive demos. This episode explores why Claude Code feels like an inflection point, how it changes the economics of software and information work, and why the real risk facing companies may be underestimating how fast agents are becoming the default way work gets done.Reading: https://newsletter.semianalysis.com/p/claude-code-is-the-inflection-pointBrought to you by:KPMG – Discover how AI is transforming possibility into reality. Tune into the new KPMG 'You Can with AI' podcast and unlock insights that will inform smarter decisions inside your enterprise. Listen now and start shaping your future with every episode. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.kpmg.us/AIpodcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Rackspace Technology - Build, test and scale intelligent workloads faster with Rackspace AI Launchpad - ⁠⁠http://rackspace.com/ailaunchpad⁠Zencoder - From vibe coding to AI-first engineering - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://zencoder.ai/zenflow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Optimizely Agents in Action - Join the virtual event (with me!) free March 4 - ⁠⁠https://www.optimizely.com/insights/agents-in-action/⁠⁠AssemblyAI - The best way to build Voice AI apps - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.assemblyai.com/brief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Section - Build an AI workforce at scale - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.sectionai.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LandfallIP - AI to Navigate the Patent Process - https://landfallip.com/Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Agent Readiness Audit from Superintelligent - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://besuper.ai/ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://pod.link/1680633614⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Interested in sponsoring the show? [e-mail]

Today on the AI Daily Brief, how Claude Code killed the AI bubble. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, Assembly, robots and pencils, blitzie, and super intelligent. To get an ad-free version of the show, go to patreon.com slash AI Daily Brief, or you can subscribe at Apple Podcasts. Ad-free is just $3 a month. If you are interested in sponsoring the show, send us a note at sponsors at AI Daily Brief.

And finally, while you are at AIdailybrief.aI, you can find out about all the various projects that we have going on, including one, which as I am recording this, I have not pushed live yet, but which I am clearly committing to by Sunday. It's the follow-up to our AI New Year's self-directed learning program, and it's going to be a new program to match OpenAI's internal objective of Agent First Work by March 31st. The safest thing is to go to AIdailybrief.ai to look for the link, but I assume it will also be on March 3rd. and AIDBTraining.com. And with that announcement out of the way, let's move on to today's episode. So this is a weekend episode, which as you guys know is a long reads and or big think episode. And there is a really interesting theme that has taken hold that I think is so fascinating and a perfect encapsulation and capstone to everything we've been talking about throughout

26 so far. On Thursday, of course, we got two frontier models within 20 minutes of each other. Anthropics Opus 4.6, and OpenAIs, ChatGBTGPT, 5.3 Codex. Something about this clicked for people. Prominent thinker Tyler Cowan wrote, Today we'll go down as some kind of turning point, somewhat arbitrarily, but it is okay if journalists and historians have to present things in that manner. Nathan Young wrote,

If you're walking around SF, does it feel like the early days of COVID, where it's clear what's on everyone's mind? Wayne on Twitter said, Can someone explain to me what concrete thing happened in the last 48 hours that explains the fact that I've seen 57,246 vague posts like this one? Andy Masley wrote, I know everyone's saying it's feeling a lot like February 2020, but it is feeling a lot like February 2020.

So what is going on? Investor Chow Wang put it simply. He wrote, I think AI is much less of a bubble than I thought two months ago. And pretty much everyone I know who used Claudex in the last two months feels that way. In short, what we have experienced so far in 2026, is a set of cascading recognitions. As we've discussed ad nauseum, it took even the most enfranchised and technical AI users going home over the holidays and having some time and space to really understand

just how different the capabilities of the models, including Opus 45 and Codex 52, really were. Quad code, of course, became the harness encapsulation of using those things to transform what you can do. When people came back, they started talking about how they had pushed more code in the last two weeks than they had done in the year before. You started to see a shift in the narrative. where even the folks who had previously said vibe coding is just for prototyping, were now recognizing that agented coding was kind of for everything. Claude Co-Work came out, and the team behind it revealed that they had put it together in 10 days, and it was basically exclusively coded using Claude Code.

Now, Claude Co-Work was interesting as an inflection point in the story, because it came out around the middle of the month, and that's when the mainstream started picking up on this story as well. It wasn't just that they were using Claude Co-work, although many of them were. Some were even finding their way into Claude Code, even though it's technically more challenging. You started to see think pieces show up in business and finance publications away from technology about how different the agenic capability set was with ClaudeCode.

And you started to see it have a market impact as well. The new concern started to be less about an AI bubble and more about what some dubbed the SaaSpocalypse, a broad-based plunge specifically in software but not other types of technology stocks, where the rise of these agentic coding tools had people really questioning how valuable and how durable the positioning of those SaaS companies was. That is the environment into which 4-6 and 5-3 Codex came. And that's the environment in which Semi-analysis wrote their recent post, Claude Code is the inflection point.

So this will be the long-reads portion of this episode, and we'll read not the whole thing but a number of excerpts from the great team at Semi-analysis that starts with a fairly profound stat. Claude, which was released less than a year ago in March of 2025, As a research preview, mind you, just about one month after Andre Carpathy coined the term vibe coding, now represents 4% of GitHub public commits. And you can see in this chart that this is accelerating. There started to be viral growth around October.

Then at the beginning of January, things really started to heat up. It came in part around Boris, the creator of CloudCode, introducing himself on Twitter and starting to talk about how he used it. But obviously, there has been a lot going on this month that has significantly increased the engagement with Claude Code. OpenClaw Mulpbook, this has been the story of 2026 so far. Semi-analysis's Dylan Patel continues, at the current trajectory, we believe that Claude Code will be 20% plus of all daily commits by the end of 2026. While you blinked, AI consumed all of software development.

Let's continue on into the larger piece. The semi-analysis team writes, We believe that Claude Code is the inflection point for AI agents and is a glimpse into the future of how AI will function. It's set to drive exceptional revenue growth for Anthropic at 2026, enabling the lab to dramatically outgrow Open AI. Anthropic, they argue, is on track to add as much power as Open AI in the next three years. They then share a building-by-building tracker of Anthropic and Open AI, and write,

Sam's AI lab is notably suffering from multiple data center delays. And since more compute means more revenue, we can forecast ARR growth and compare Anthropic to Open AI directly. Notably, they continue, our forecast shows that Anthropics' core. quarterly ARR editions have overtaken Open AIs. Anthropic is adding more revenue every month than Open AI. We believe Anthropics' growth will be constrained by compute. The next section they call Claude Code in the Agentic Future.

Agents, they write, will be the primary method of how organic intelligence, humans, interacts with artificial intelligence. But Claude Code is also a demonstration of the reverse, showing how agents interact with humans. We believe the future of AI will be about the orchestration of tokens, not just selling tokens at base cost. With history as a guide, we view the OpenAI chat-chap API as the call-and-responsive tokens, akin to Web 1.0 with TCPIP, connecting users to static websites hosted on the internet. While TCPIP is a foundational technology, this communication protocol became just the means to the end of enabling the internet during Web 2.0, and the shift to dynamic web pages.

Today, the internet uses TCPIP packets to organize much larger sets of information than a static website. The protocol matters, but it was the applications built on top of this protocol that created trillions in value. This is why Semi-analysis believes we are yet again at another critical moment in AI, one that matches, if not exceeds, the chat GPT moment in early 2023. Each moment expanded what AI could do. GPT3 proved scale worked. Stable diffusion showed AI could make images. ChatGPT proved demand for intelligence. Deepseek proved that it could be done on a smaller scale, and O1 showed you that you could scale models to even better performance. The viral moments of Studio Ghibli are just adoption points, while Claude Code is a new breakthrough in the

agentic layer of organizing model outputs into something more. Now, in describing Claude code, they continue, it might be incorrect to think of Claude Code only as focused on code, but rather as Claude Computer. With full access to your computer, Claude can understand its environment, make a plan, and iteratively complete this plan, the whole time taking direction from the user. Claude Code does more than just code and is the best example of an AI agent. You can interact with a computer with natural language to describe objectives and outcomes rather than implementation details. Provide clawed and input such as a spreadsheet, a codebase, a link to a web page, and then ask it to achieve an objective. It then makes a plan, verifies details, and then executes it. It's a glimpse

of the future, but it is also here today and software already. Your favorite engineers are Vibecoding. Andre Carpathy, who coined the term vibe coding one year ago, is openly discussing the phase shift, and specifically says, I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation, writing code, and discrimination, reading code, are different capabilities in the brain. Maltai Uble, the CTO of Versel, claims that his new primary job is to tell AI what it did wrong. Ryan Dahl, creator of NoJS, says the era of human's writing code is over. David Henemaer Hansen, creator of Ruby on Rails, is having some sort of anticipated nostalgia, reminiscing about writing code by hand while writing code by hand.

Boris Churney creator of Claude Code says that pretty much 100% of our code is written by Claude code in Opus 4-5. Even Linus Torvalds is vibe coding, but it isn't just coders, from which semi-analysis describes how the different members of their team all use this tool in different ways. They write that the data center model team needs to review hundreds of documents every week. The AI supply chain team needs to inspect BOMs with thousands of line items. The memory model team needs to bill forecasts in near real time as spot market prices explode. Technical staff needs to maintain a live dashboard, meaning in total, as they write, from regulatory filing to permits, spec sheets to documentation, config to code, the way we interact

with our computers has changed. Coters will stop doing code and rather request jobs to be done on their behalf, and the magic of Claude code is that it just works. Many famous coders are finally giving in to the new wave coding and now realizing that coding is effectively close to a solved problem that is better off supported by agents than humans. The locus of competition is shifting. Obsessions over linear benchmarks as to what model is quote unquote best will look quaint, a case. A case of akin to how fast your dial-up is compared to DSL. Speed and performance matter, and the models are what power agents,

but performance will be measured as the net output of packets to make a website, not the packet quality itself. The website features of tomorrow is going to be the orchestration through tools, memory, subagents, and verification loops to create outcomes and not responses. And all information work is finally addressable by models. If you're building anything with voice AI, you need to know about assembly AI. They've built the best speech-to-text and speech-understanding models in the industry, the quiet infrastructure behind products like granola, dovetail, Ashby, and Cluley.

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Impact at velocity. Weekends are for vibe coding. It has never been easier to bring a passion project to life, so go ahead and fire up your favorite vibe coding tool. But Monday is coming, and before you know it, you'll be staring down a maze of microservices, a legacy cobal system from the 1970s, and an engineering roadmap that will exist well past your retirement party.

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See why Fortune 500's trust Blitzy for the code that matters at blitzy.com. That's BLYTZY.com. Today's episode is brought to you by my company Super Intelligent. In 2026, one of the key themes in Enterprise AI, if not the key theme, is going to be how good is the infrastructure into which you are putting AI in agents? Super Intelligence Agent Readiness Audits are specifically designed to help you figure out, one, where and how AI and agents can maximize business impact for you, and two, what you need to do to set up your organization to be best able to leverage those new gains.

If you want to truly take advantage of how AI and agents cannot. not only enhance productivity, but actually fundamentally change outcomes in measurable ways in your business this year, go to B-super.aI. And this is really the big theme they pick up from there, that the reason that this is an inflection point moment is not just about coding capability, but about what that leads to. They continue, coding was once the most valuable work of all, with programmers in hot demand during the 2020 era of software engineering. Coding is now a beachhead in terms of the disruption that agentic information processing has,

and the larger $15 trillion-dollar information work economy is now at risk. There are 1 billion-plus information workers or roughly a third of the global workforce. Every single workflow in the information work category is often similar and shares a workflow that Claude-Code proves works for software. Read, ingest unstructured information, think, apply domain knowledge, write, produce structured output, and then verify, check-again standards. This is large swaths of most information workers, including research. And if agents can eat software, what labor pool can they not

touch. Our view is quite a few, and with the rise of Claude Code and Co-Work, the total addressable market of agents is much larger than LLMs. Given the killer use case encoding and the clear generalizability of cloud code and co-work, this justifies a completely different calculus. Automating most call-in-response and information fetching is likely doable, and this opens the absolute dollars possible. And what they say really makes larger parts of the Pi available for disruption is longer task horizon. How long can an agent work before it fails its task? Meter data shows autonomous task horizons doubling every four to seven months, accelerating to around every four months in 24 and 25.

Each doubling unlocks more of the total pie. At 30 minutes, you can auto-complete code snippets. At 4.8 hours, you can refactor a module. Multi-day tasks, you can automate an entire audit. And it's clear Anthropics sees this too. On January 12, 2026, Anthropic launched co-work, Claude Code for General Computing. Four engineers built it in 10 days. Most of the code was written by ClaudeCode itself.

Same architecture, Claude Agent SDK, MCP, subagents. It creates spreadsheets from receipts, organizes files by content, and drafts reports from scattered notes. It's cloud code minus the terminal plus a desktop. This is the glimpse of the future, a harness that understands the context of your day-to-day job or work and can build and generate information processing as needed. Instead of creating images from reports you download from your database, an agent will generate a report with better formatting than you could do yourself within Excel for you. Whenever you need to gather information about, say, a sales quota, your agent will extract the

information from a UI or API and generate the report for you on your behalf. Information work itself is going to be automated like Claude Code has automated software engineering. And while it's not perfect today, it clearly can generally process, synthesize, and format data faster than most humans can. This all comes at higher fidelity and lower costs than the average worker in some areas. While there will be hallucinations, most systems already exist with many human-led errors in the process.

If the information is processed at a viable level of fidelity and then pass to the next step, this itself will massively increase the supply of work. We are literally at the point where any individual could type into one of these agent workflows to run a multivariable regression that would have taken a lifetime of training in the 2000s. The Stack Overflow 2025 developer survey has 84% of coders using AI, and that is the bleeding edge of adoption. Only 31% use coding agents. And that means that this penetration curve is early for broader waves of information work,

Just like the blink for coding agent penetration, broader information work will quickly see AI adoption. Now, the last section of this piece that we're going to read is about cost and market impact. They have a whole secondary section on competitive race and who's winning, but that's less the point, at least for this show. Moving back to where we left off, they write, Now, engineering has and always will be the gold standard information work, but as the quality has finally crossed over a critical threshold, the relationship between coders and their tools have flipped. Coters are effectively just harnessing a black box to achieve outcomes. And that was all possible because not only the quality but the cost of the intelligence of tokens

has fallen an amazing amount. One developer with Claude can now do what took a team a month. And Enterprise is already starting to move. The massive deflationary cost of intelligence is going to reprice every information company's margin for repeatable work. Accenture just signed a deal to train 30,000 professionals on Claude, the largest Cloud Code deployments to date. Accenture will focus on financial services, life sciences, health care, and the public sector. Those are all huge, untapped markets for information automation. OpenAI just announced Frontier focused on enterprise adoption.

Enterprise software has easily been the first casualty of the great cost decline of intelligence. SAS itself is just crystallized information processing of workflows into code. The three modes of SaaS, switching costs of data, i.e. data is trapped, workflow lock-in, i.e. learning the UI, and integration complexity, how Slack works with Jira, have all been partially eroded at the margins. The 75% gross margin of SaaS looks like a huge opportunity, as agents migrate data between systems with lessened migration costs, agents themselves do not rely on human-oriented workflows, and MCP integrations make integration much easier. Every aspect of SaaS is cheapening, and the margins have become the first opportunity of AI. In our view, anything that has a human

click buttons, gather information, reformatted into another medium, is a huge risk. So, okay, that's the part of this essay that we're going to read. And when push comes to shove, the key phrase here is inflection point. What's important about the last month is not just that en masse the most enfranchised and highly technically literate AI users realized that we had reached an inflection point. It's that that perception has now cascaded into the wider world. What really crystallized this for me and what basically prompted me to want to do this show was when former Atlantic author and co-author of abundance, Derek Thompson, tweeted out on Thursday, for me, the odds that AI is a bubble declined significantly in the last three weeks,

and the odds that were actually quite underbuilt for the necessary levels of inference and usage, went significantly up in that period. Basically, I think AI is going to become the home screen of a ludicrously high percentage of white-collar workers in the next two years, and parallel agents will be deployed in the battlefield of knowledge work at downright Soviet levels. The New York Times, Kevin Ruse reposted it and said,

this is why everyone was freaking out about Claude Code over winter break. Once you see an agent autonomously doing stuff for you, it's so instantly clear that roughly all computer-based work will be done this way. Kevin continued, this is why my serious AI policy proposal is to sit every member of Congress down in a room with laptops for 30 minutes and have them all build websites. Deirdra Bossa, who you might remember in preparation for a show about the Saspocalypse as a reporter for CNBC, try to code herself up a version of Monday.com not expecting to actually do anything. About an hour later, she had a fully working version and kind of became a convert.

The way that she described this shift, which I thought was quite crisp, was that over the last couple of months, in her words, AI went from talking to doing. Now, not everyone fully agrees. Mike Coton, reposted Derek and said, I agree mostly with this. However, there's a big assumption contained within that the organizations these white-collar workers are employed by actually have the appetite to integrate the tools.

Lots of process and system change will need to be made with current capabilities. I think it goes even farther than that. To put it bluntly, the value of using AI well has gone way up. But the difficulty of learning how to use AI well has also gone way up. That makes the natural enterprise inertia barriers even more pronounced. There's also plenty of reactions like this one from Van Jackson, who writes, The AI Bubble is about lack of profitability in firms being over-leverage,

not about usage. Everyone already uses AI unprofitably, destroying most of the workforce and press-ganging those still clinging to jobs into using AI changes nothing. But this, at least on the market side, is kind of what's shifted. The interesting wrinkle that this adds to the bubble conversation and the reason that folks like Derek and Chow are talking about why an AI bubble is likely is that for the average person, the AI bubble argument was that we were overbuilding

AI infrastructure that maybe we weren't even going to need, or that maybe these companies couldn't even pay for. You kind of want it running all the time. In fact, you want multiple agents running all the time to do more things. Multiple agents running all the time means more tokens consumed. And that, as Ethan Malik puts it, we are going to need more compute now that agents can complete long-term economically viable tasks. Ethan clarifies this does not mean that there couldn't be some sort of financial issue with financing the compute, but does point to the idea that compute is not being overbuilt. And that is what is at least starting to shift. Now, it would be way overblown to argue that this has fully found its way into public markets. But you're starting

to see it happen, and it's kind of headspinning, as no one knows what all these signals taken together should mean an aggregate. Seb K sums up the confusion. Sudden smart consensus today is that the AI takeoff is rapidly and surprisingly accelerating, but stocks for Google, Microsoft, Amazon, Facebook, Palantir, Broadcom, and NVIDIA are all down 10% over the last five days. SMCI is down 10% today. This, by the way, was from Thursday. Only Apple's up and it's the least AI.

Strange in my opinion. All I can say is buckle up, friends, because I think we are in for an interesting and confusing period. Back in October, OpenAI's Rune wrote, Not enough people are emotionally prepared for if it's not a bubble. And I kind of think that's part of what we're seeing here. AI, as Deirdre put it, over the last couple months, has entered the show-not-tell phase. It's doing things, not talking about them.

Agents have turned the corner from a thing that would be really cool to a thing that is doing real work right now. And everywhere around us, the signals that the way that work is done has changed are profound. To take an example that we shared the other day, OpenAI President Greg Brockman says that by March 31st, for any technical task that happens inside that company, the tool of first resort for humans is interacting with an agent rather than using an editor or a terminal. Agent First Work by March 31st. Now, as I mentioned in the intro, if you want to get on that timeline as well, I decided to

throw together another free self-directed learning experience like the New Year's resolution, because heck yeah, if Greg is going to challenge his team to meet that goal, why shouldn't the rest of us figure it out too? In any case, whether Tyler Cowan is right, and last Thursday when Opus 4-6 and 5-3 codecs were released, goes down in history of some kind of turning point. What's clear is that a shift has happened. It has in fact been happening for two months, but now it is fully working its way through the system,

and everyone is grappling with the implications. I wish all of you, listeners, nothing but the best navigating this period, and I will, of course, continue to do my best trying to help you make the most of it. For now, that is going to do it for today's AI Daily Brief. Appreciate you listening and watching, as always, and until next time, peace.