#ai-agents
Every post tagged "ai-agents".
303 posts · showing 101–110
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Open Source After Cheap Contributions
Contribution effort rationed demand for maintainer attention. That rationing is gone and the attention is unchanged — but the filters that work test for something effort was only ever a proxy for.
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Compliance and Audit for Agent-Written Systems
The audit questions don't change — who's responsible, how do you know it's correct, show me this case. They become answerable differently, and an actor field saying "agent-service" answers the first one not at all.
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Security Review When Nobody Wrote the Code
Human vulnerabilities carry a tell — hurried code, an obvious shortcut. Generated code is uniformly careful-looking, so scanning for the suspicious part stops working. But its consistency cuts both ways.
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Why Your Codebase Will Grow Faster Than Your Understanding
Writing code built understanding as a byproduct, which is why "the team knows the system" used to be true without anyone planning it. That coupling broke and only one of the two rates changed.
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Technical Debt in the Age of Cheap Code
The old rules assumed writing code was the expensive part. When it isn't, imperfect implementations matter less and surplus surface matters more — and the create-versus-remove asymmetry gets worse.
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Onboarding Into a Codebase Nobody Fully Read
"Ask whoever wrote it" assumed someone did. Where code arrived complete in one commit and was approved rather than authored, the history holds no reasoning — and onboarding is where you find that out.
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Hiring Engineers When Take-Home Tests Are Meaningless
The signals didn't get noisier — they stopped measuring what they proxied for. The replacements test the right thing and are more subjective, which is a cost that lands on specific people.
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Estimating Work When Implementation Speed Is Unpredictable
Estimation always worked badly and consistently, which is what made velocity useful. The consistency is what broke — the mean fell and the variance rose, which is the worst combination for planning.
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What Changes for Engineering Managers
Four management assumptions break at once: that output tracks effort, that capacity is headcount, that people learn by doing, and that review is a small tax. Each breaks differently.
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What Changes for Product Managers
A role that existed partly to ration scarce engineering capacity changes when capacity stops being scarce — and the discipline of saying no gets harder, not easier.