The original title is "The Agentic Harness: The Part That Actually Keeps Agents Reliable"

Short summary

Most production AI agent failures stem from weak harness design, not model limitations. The harness — code that executes tool calls, tracks state, enforces limits, and defines termination — determines what an agent can actually do and how it recovers from failure. Key failure modes like retry loops and oscillation are structurally invisible within a single turn and require the harness to maintain a history window with outcome-digest tracking and hard caps.

• •Agent failures in production are usually harness problems, not model problems
• •Harness responsibilities: execution validation, state/memory tracking, termination logic, and budget enforcement
• •Retry loops and oscillation patterns require cross-turn history tracking, not just current-state inspection

Generated with AI, which can make mistakes.