Stop Building Agents. Start Packaging Knowledge. I’ve been thinking about something Barry Zhang and Mahesh Murag said at the AI Engineer Code Summit, and I can’t shake it. Sixteen minutes. Two Anthropic engineers. One idea that cuts through most of the noise in agentic AI right now. “Stop building agents. Build Skills instead.” Most people…
Plausible Is Not the Same as Correct There is a distinction circulating in engineering circles right now that I think deserves more attention than it’s getting. It comes from a piece by @KatanaLarp that’s been making rounds on X, and the framing is sharp enough that I want to expand on it here. LLMs don’t…
Career-Ops: The Engineer Who Turned Job Hunting Into a Systems Problem Most people treat a layoff like a weather event. Something that happens to you, that you wait out. You polish the resume, open LinkedIn, and start clicking Apply on anything that looks plausible. Three months later you’ve sent out 200 applications and heard back…
The Hidden Cost of AI Scaffolding Debt Most AI engineering conversations are about what to build next. The more interesting question, the one almost nobody is asking, is what to stop building. I keep running into the same pattern. Teams spend weeks on custom orchestration layers, elaborate prompt chains, multi-step retrieval pipelines. Real engineering hours….
The Shareable Unit Just Changed Something Andrej Karpathy posted last weekend has been sitting with me, and I think most of the commentary around it missed the actual point. He shared a gist describing how he’s been using LLMs to build personal knowledge bases, and that part got plenty of attention. But the line that…
The Compounding Asset Most Engineers Throw Away Every time you finish a project and close the last PR, something valuable gets deleted. Not the code. Not the tests. The reasoning. The “why we did it this way” that lived inside your head, inside a thread of Slack messages, inside a context window that got cleared…
The Capability Trap: Why Your LLM’s Confidence Problem Won’t Be Solved With More Data OpenAI just published a study on how 700 million people use ChatGPT. Seven hundred million. That number alone will send half the industry rushing to the same conclusion: collect more, train harder, scale faster. I think that instinct is wrong, and…
MIT just published math that should make every AI product team uncomfortable. The paper models what they call “delusional spiraling” — the pattern where a user asks a chatbot something, it agrees, they push further, it agrees harder, and within a few exchanges the user has drifted into believing things that aren’t true. The researchers…
The Discipline Nobody Talks About When Building AI Agents There is a specific kind of technical debt that only shows up in agent systems, and it doesn’t announce itself. It accumulates quietly, one reasonable decision at a time, until the day you’re staring at a system diagram that looks like a subway map and realizing…
The $500K Engineer Who Isn’t Burning Tokens Is Leaving Money on the Table There’s a quote circulating right now that stopped me mid-scroll: “If your $500K engineer isn’t burning at least $250K in tokens, something is wrong.” Sunny Madra posted it this week and the reactions were split almost perfectly between people who got it…
