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Babysitter, Auditor, Prayer. Or Tests.

TL;DR AI

Key summary

2 min read
  1. The article argues that reliable LLM agents need code-level tests and assertions, not just prompts or human oversight.

  2. It criticizes prompt-driven control flow and says the better approach is to verify model outputs before any next step or tool action runs.

  3. Practical safeguards include schema checks, predicates, evals, dry-runs, and runtime assertions.

  4. The core idea is to treat LLM agent reliability as a software testing problem, blocking bad outputs before they can cause damage.

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