A technologist working in automation. Here I write up what I actually learn building tools, engineering AI agents, and keeping systems running, along with the workflows and habits that stick.
The failure mode that burned us was silent downstream consumers. You revoke the API keys and archive the prompt configs, but two cron jobs and an internal webhook were quietly consuming that agent's structured JSON. The moment the agent went dark, those downstream scripts started timing out and spamming retry queues.
Our rule now is a two-week tombstone phase before pulling the plug. We swap the model inference call for a static mock that returns empty valid schemas and logs the caller identity. That surfaces the forgotten dashboard widgets, personal curl scripts, and scheduled pipes without triggering production alerts. Once the caller logs stay clean for fourteen consecutive days, revoking the tokens and dropping the vector tables is safe.
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The failure mode that burned us was silent downstream consumers. You revoke the API keys and archive the prompt configs, but two cron jobs and an internal webhook were quietly consuming that agent's structured JSON. The moment the agent went dark, those downstream scripts started timing out and spamming retry queues.
Our rule now is a two-week tombstone phase before pulling the plug. We swap the model inference call for a static mock that returns empty valid schemas and logs the caller identity. That surfaces the forgotten dashboard widgets, personal curl scripts, and scheduled pipes without triggering production alerts. Once the caller logs stay clean for fourteen consecutive days, revoking the tokens and dropping the vector tables is safe.