Tag: LLMs
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The Q1 2026 AI Roundup (or, What Just Happened)
Q1 2026 was the quarter the agentic AI moved from demo to production. Three stories defined the quarter. The fourth, the one nobody is talking about, will define the next.
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How to Tell if an AI Image is Fake (Without Going Down a Rabbit Hole)
AI image generators are good now. Scary good. Here is a practical 30-second checklist for catching fakes before you share them.
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The Claude Code Effect on the Engineering Org
Claude Code and the other agentic coding tools have changed what an engineering team looks like. The senior engineer writes the prompt. The junior engineer runs the code. The middle engineer is being squeezed out.
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What the AI Labs Aren’t Telling You About Safety
AI labs in 2026 are not telling you the full story about their safety work. They are not telling you because the full story is not flattering, because the full story would invite regulatory scrutiny, and because the full story would slow down the product release. The patterns in what the labs are not saying…
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What “Human in the Loop” Actually Means (And Why Most AI Products Get It Wrong)
A human is not meaningfully in the loop because a product displays an approval button. Real oversight requires context, time, authority, and evidence. Many products include the human only to absorb liability.
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Voice Cloning and the Death of Voice Verification
Voice verification sat as the security control the bank, the call center, the enterprise helpdesk relied on for years. The five second voice sample, the my voice is my password pitch, the security control that worked until the voice cloning tools became good enough to defeat it.
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What AI Cannot Do, Yet
A field guide to what AI cannot do in 2026, with the four areas where the models are still bad, the four areas where the models are getting better, and the part where the honest answer is that nobody knows yet.
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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.