Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.

“you burned how many tokens today?”

I have some big news to share. Workera is being acquired by Pearson! Over six years ago, I was teaching at Stanford and thinking about a simple question: what if we could understand everyone's skills as precisely as the best teachers understand their students? I believed it could lead to a more meritocratic world. People could be recognized for what they can actually do, not just their credentials or network. They could understand their strengths and gaps, and rapidly develop the skills they need next. Organizations could discover talent they might otherwise overlook and manage their workforce with trusted skills data. What felt like a dream at the time is now a reality. Workera brought together experts in AI, psychometrics, and enterprise execution to build AI systems that reinvent how skills are measured. Our team pioneered AI-native skills intelligence, agent-led multimodal assessments, and even ambient skill measurement. We've established skills benchmarks across organizations, industries, and roles. And this mission feels more important today than ever! AI is changing work as we speak. Some roles are disappearing, new ones are emerging, and we need to help billions of people develop new skills and navigate what comes next. When I first spoke with @omarabbosh, it became clear that our companies shared the same mission. Pearson has helped generations of people learn and prove what they know. If you're reading this, there's a good chance you've taken a Pearson assessment, learned from their educational materials, earned a professional credential through them, read their psychometrics research, or benefited from their enterprise products in many other ways. Bringing together Workera's technology and AI talent with Pearson’s global scale and deep expertise in learning and assessment means we can pursue our mission at a scale we could only imagine on our own. To our customers and partners, thank you for believing in us. Expect even more innovations coming out of Workera and Pearson. To the Workera team, I’m incredibly proud of what you've built, and your continued dedication to our beautiful mission. To our board and our chairman @AndrewYNg, thank you for your belief, support, and mentorship. To everyone, we have big plans for this next chapter, so please stay tuned. We're just getting started! 😊

Claude Tag in Slack can now use your personal connectors! You can now securely access that Drive doc, Salesforce account, or Warehouse table that you have personal access to right where the work happens. Avail. on Teams today and Enterprise next week https://claude.com/blog/claude-tag-now-supports-personal-connectors-in-channels