The Real Reason AI Agents “Work” in Software

Agents don’t work. Verifiers do. LLMs propose; deterministic systems decide what’s allowed to run. Code agents succeed because software already has compilers, tests, linters, and CI—the “domain validator” for free. (This is a personal analysis. I’m not trying to criticize any specific company or product.) We’re seeing more examples of AI agents that “run well” in real work settings. But in most success stories, the secret isn’t a smarter model—it’s the surrounding guardrails . In this article, guardrails means: Not “trust the LLM output,” but a deterministic validator layer (and an operating process) that accepts/rejects proposed actions and makes execution auditable . If you want agents to work outside software—legal, accounting, healthcare, ops, customer support—you need the same idea: LLM + domain validator (policy engine / deterministic gate / “domain compiler equivalent”) 1) Why code-generation agents seem to work Software is unusually friendly to agents because verifiability is b