InfoQVinoth Govindarajan24 min readtalkintermediate
Presentation: The Agent Harness: Control Planes, Invariants, and Approval Boundaries for Production AI Agents
Summary
Production AI agents often fail silently due to issues beyond model hallucination, such as state inconsistencies. This talk outlines principles for building reliable agent harnesses, focusing on explicit state ownership, ordered mutations, and verifiable actions, using real-world case studies.
- Production AI agent failures often manifest as "silent successes" where the user sees success but the system's durable state is inconsistent.
- A fact needs one owner and one replay path; state ownership defines the boundary for recovery, not just storage.
- Concurrency is acceptable, but shared state mutations must be ordered via a single commit path to prevent accidental interleaving.
- The transcript is not the receipt; actions must be proven by what was attempted, approved, and committed at the user-visible edge.
Engineers building or operating production AI agents need these distributed systems principles to prevent subtle, hard-to-debug failures that undermine trust and system integrity.
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