Configure an AI agent for one job: instructions, tools and boundaries
Build a focused cloud cost investigator with six adaptable samples covering purpose, instructions, tool contracts, user requests, findings and acceptance checks.
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Build a focused cloud cost investigator with six adaptable samples covering purpose, instructions, tool contracts, user requests, findings and acceptance checks.
Read the story ↗Build a focused cloud cost investigator with six adaptable samples covering purpose, instructions, tool contracts, user requests, findings and acceptance checks.
Turn artifact provenance into a deployment decision by verifying the exact output, constraining its origin, and testing both acceptance and rejection paths.
Distinguish rejected eviction, pending replacement, and slow termination, then find the narrowest safe correction for a blocked maintenance operation.
Evaluate tool selection, argument scope, action order, and resulting state alongside the final response, using a cancellation assistant as a worked example.
Build a useful self-service path from observed developer work, with safe retries, clear ownership, diagnostics, cost responsibility, and a complete service lifecycle.
Separate initialization from application and dependency delay, compare prepared-capacity windows, and build a repeatable cost-performance decision for one important route.
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