Category: AI
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When AI Hallucinates in Production
The failure looks like a confident answer that is wrong in a way the system cannot detect, and the cannot detect is the part the production team has to live with.
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The Local LLM Stack Is Real in 2026
A field guide to the local LLM stack in 2026, with what the open weights models can actually do, what the hardware requirements look like, and the part about the workloads that are going to stay in the cloud.
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The Day AI Stopped Being the Story
The day AI stopped being the story arrived without anyone noticing. The product launch that the press no longer covered, the research paper that the analyst no longer cited, the announcement that the executive no longer read, the day the AI hype peaked and the AI started becoming the background the work happens in.
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LLMs Are Still Mostly Plagiarism With Better Punctuation
The training data is still mostly text written by humans, the loss function is still mostly next token prediction, and the result is still mostly text that looks like the training data, rearranged, smoothed, and served with the confidence of a system that does not know it is rearranging.
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Your AI Agent Logs Are Your Liability
Your AI agent logs are your liability, in 2026, and the reason is that the AI agent logs contain everything the user did, and the user did a lot, and the stuff the user did is increasingly the kind of stuff that creates legal and regulatory exposure.
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The Twelve Things That Will Define Tech in 2026
The start of the year is a useful prompt to look at the shape of the next twelve months. Here is what we think is actually going to happen, in order from most likely to least.