5 Harness Engineering Techniques That Turn LLMs Into Reliable AI Agents

goyalshaliniuk · x · 2026-11-01

Shalini Goyal argues a powerful model alone doesn't make a reliable agent — the harness around it does. Her five techniques:

Bounded control loop: plan → act → observe → evaluate with iteration limits, timeouts, stop conditions, and loop detection.
Context & state management: task-relevant context only, working memory, persisted checkpoints for resuming after failures.
Secure tool access: least privilege, input/output validation, human approval for sensitive or irreversible actions.
Verification & evaluation: validate against explicit requirements, run independent checks, track real-world success rates.
Observability & recovery: log tool calls, decisions, errors; track latency, token cost, outcomes; add retries, fallbacks, human escalation.

Her infographic also links Microsoft Agent Framework, Snowflake, Anthropic evals docs, and an arXiv harness-engineering paper.

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