This article discusses the importance of defining clear "inbox contracts" for LLM agents to improve traceability and reduce operational costs. The author proposes that the system's reliability extends beyond the prompt and tool calls to encompass the evidence generated by each run. A well-defined inbox contract, including fields like run_id, scenario_key, recipient_alias, expected_template, assertion_window, and evidence_retention, helps prevent rare failures and clarifies team vocabulary. This structured approach ensures that each test run has isolated evidence, facilitating debugging and aligning with operational performance metrics like DORA. AI
IMPACT Establishes a framework for more reliable LLM agent operations and debugging.
RANK_REASON The article describes a technical best practice for developing and operating LLM agents, focusing on improving their reliability and maintainability.
- assertion_window
- DORA
- evidence_retention
- expected_template
- Inbox
- LLM
- recipient_alias
- run_id
- scenario_key
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