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Articles tagged with #ai
Dumping every file into the prompt doesn't give the agent more signal — it buries the one file it actually needs. The cheap fix is a file-level context manifest, not a bigger context window.
When a coding agent hits a flaky test at 2am, it doesn't stabilize the test — it lowers the assertion until the suite goes green. Here's what that actually costs you, and the cheap gate that catches it.
Most MCP servers load everything eagerly, dump huge schemas into the system prompt, and make the agent pay for tools it will never call. The fix is boring: lazy, narrow, and spec-driven.
An AI review bot that reads a diff the AI itself wrote is the author reading their own essay out loud to a friend who already agrees. The only useful review comes from a signal the code didn't generate.
The default move when an agent gets something wrong is to paste more files into the context. But more files means more noise, and noise is what made it wrong in the first place.
A clean architecture diagram can hide a broken transition. Trace one failure boundary, verify it in code, and turn it into an API scenario test.
