As foundation models continue to improve, the lack of relevant context often limits what they can do, especially as they are used to build agentic systems. While these models can help you write code, summarize documents, or analyze a dataset, they still need the right information to produce accurate and actionable results.
That’s why today, we’re introducing the Open Knowledge Format (OKF), an open specification that formalizes the LLM-wiki pattern into a portable, interoperable format. This is a vendor-neutral, agent- and human-friendly standard for representing the metadata, context, and curated knowledge that modern AI systems need. — Read More
Daily Archives: June 15, 2026
Jeff Bezos’s Prometheus raises $12B to build an ‘artificial general engineer’ for the physical world
Prometheus, the physical AI startup co-founded by Jeff Bezos and Vik Bajaj, the former co-founder of Verily, Google’s life sciences unit, announced it raised $12 billion at a $41 billion valuation.
… Prometheus is building what it calls an “artificial general engineer” — software capable of automating the design and manufacturing of complex physical systems, from jet engines to drug compounds. — Read More
The Mythical Agent-Month
Like a lot of people, I’ve found that AI is terrible for my sleep schedule. In the past I’d wake up briefly at 4 or 4:30 in the morning to have a sip of water or use the bathroom; now I have trouble going back to sleep. I could be doing things. Before I would get a solid 7-8 hours a night; now I’m lucky when I get 6. I’ve largely stopped fighting it: now when I’m rolling around restlessly in bed at 5:07am with ideas to feed my AI coding agents, I just get up and start my day.
Among my inner circle of engineering and data science friends, there is a lot of discussion about how long our competitive edge as humans will last. Will having good ideas (and lots of them) still matter as the agents begin having better ideas themselves? The human-expert-in-the-loop feels essential now to get good results from the agents, but how long will that last until our wildest ideas can be turned into working, tasteful software while we sleep? Will it be a gentle obsolescence where we happily hand off the reins or something else? — Read More
‘Tell Him He’s a Piece of Shit’: Meta’s New AI Unit Is a Total Mess
Someone interrupted a livestreamed, employee-only presentation at Meta earlier this week with an expletive-filled outburst about “being the company’s bitch,” according to a recording heard by WIRED. The individual then asked the people leading the call to write to a specific Meta AI executive and “tell him that he’s a piece of shit.”
… The incident, which took place on a call open to thousands of employees, reflects growing frustration inside the company’s Applied AI team, which was formed in March to support the work of AI researchers at Meta Superintelligence Labs. — Read More
Selection Debt: On Doing Things That Don’t Matter
AI has made execution extremely cheap. What’s expensive is committing to the wrong thing. I’ve been thinking of this as Selection Debt: the cost of moving quickly on a poor foundational premise.
… As Derek Sivers puts it, you have to say no to many things to leave space for the one or two HELL YESes. — Read More
Anthropic’s AI Jobs Paper
Anthropic recently published a policy paper about AI, jobs, and what governments should do if AI causes major labor-market disruption. The original paper is here: Anthropic’s economic policy proposal.
The paper is about the question: if AI creates huge wealth while also replacing a lot of human labor, who gets the money, who pays the costs, and who gets blamed?
Anthropic is warning that AI could seriously disrupt jobs. It says governments should prepare now with better unemployment systems, wage support, retraining, public benefits, and possibly new taxes or wealth-sharing mechanisms later. That sounds responsible. It also protects Anthropic’s business interests. — Read More
How To Make Your Design System AI-Ready
AI-generated prototypes often don’t deliver consistently decent results because of tiny inconsistencies scattered all across a design system. I’s decisions made but not documented, hard-coded values never cleaned up, or relying too much on AI making sense of mock-ups or design flows on its own.
Yesterday I stumbled upon a useful practical guide by Hardik Pandya from Atlassian — on how to reduce drifts, minimize mistakes, maintain context, and improve the quality of AI-generated prototypes. Let’s see how it works. — Read More
Doing nothing at work
Many engineers should be doing less work. I don’t necessarily mean producing less code or fewer changes, but literally working fewer hours in the day. When they do work, they should be working at a slower pace. I like to aim to be running at 80% utilization by default: unless I have a high-pressure project going on, I spend 20% of my workday away from the computer.
Why? Performance at tech companies is dominated by outlier events. When I think about the most impactful changes I’ve made, many of them involved a surprisingly trivial amount of work. There are no points for effort in software development. What matters is solving the right problem at the right time. — Read More
Amazon voiced concerns about Anthropic AI models before US crackdown, source says
Amazon CEO Andy Jassy was among tech leaders who raised concerns to senior Trump administration officials this week about security risks in Anthropic’s most advanced AI models, a person familiar with the matter told Reuters.
Jassy’s involvement sheds light on the extraordinary move by Anthropic on Friday to shut down its latest models globally in response to national security orders from President Donald Trump’s administration. — Read More
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