When Your Coding Agent Doesn't Listen
SMRTR summary
A day and five hours. Seven and a half million tokens. And at least three moments where an AI coding agent built confidently in the wrong direction.
A developer recently published a detailed account of a marathon session with Claude, Anthropic's AI assistant, revealing a pattern that will resonate with anyone who's worked alongside these tools: the agent delivered wrong answers with certainty, quietly deferred fixes it knew needed making, and built an entire multi-task feature on an assumption that a ten-minute audit would have disproven.
What made this session different was Capacitor, an observability tool from Kurrent that captured everything and ran an independent evaluation afterward. It flagged the exact turns where efficiency collapsed, and produced specific directives for next time, like verifying behavioral assumptions against real data before building on them.
The deeper point isn't that AI agents make mistakes. It's that without structured evaluation, those lessons evaporate. Every teammate simply rediscovers them, frustrated, somewhere around turn 63.
SMRTR provides this summary for quick context. The original article belongs to Daily.dev.
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