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…
Andrej Karpathy’s LLM Knowledge Base Workflow Is the Personal Computing Shift Nobody’s Talking About Most people use LLMs like a search engine with better grammar. Ask a question, get an answer, close the tab. Nothing carries forward. Every conversation starts cold. Karpathy just published a workflow that flips that pattern completely, and I think it…
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 Overnight Engineer There’s a pattern showing up in OpenAI’s Codex usage data that I think deserves more attention than it’s getting. Developers are queuing up their hardest tasks at the end of the workday and letting Codex run through them overnight. Refactors. Architecture planning. The stuff that has lived on backlogs for months because…
The Failure Mode Nobody Is Logging Most production AI systems don’t fail loudly. They don’t throw exceptions, trigger alerts, or produce obviously wrong outputs. They drift. Quietly, confidently, step by step, until you’re ten downstream tasks deep and the original intent is completely unrecognizable. I’ve been running multi-agent pipelines for over a year, and this…
Grok Just Broke Language Barriers in Your Feed. Here’s Why That’s a Bigger Deal Than It Sounds. Most of the best content on the internet is invisible to you. Not because it doesn’t exist, but because you don’t speak the language it was written in. That’s been true since the first social platforms went global,…
The API Moat Is Dissolving. Most Product Teams Haven’t Noticed Yet. Mistral just open-sourced a text-to-speech model that runs on 3 GB of RAM. Locally. For free. And according to quality benchmarks cited by George Pu on X (https://x.com/TheGeorgePu/status/2037930340975538184), it beats ElevenLabs. Read that again. The thing product teams were budgeting per-word API costs for…
