Babysitter, Auditor, Prayer. Or Tests.

TL;DR AI
2 min readKey summary
The article argues that reliable LLM agents need code-level tests and assertions, not just prompts or human oversight.
It criticizes prompt-driven control flow and says the better approach is to verify model outputs before any next step or tool action runs.
Practical safeguards include schema checks, predicates, evals, dry-runs, and runtime assertions.
The core idea is to treat LLM agent reliability as a software testing problem, blocking bad outputs before they can cause damage.
