Steer by Intent, Monitor by Exception

Short summary

Argues that most teams deploy AI agents with excessive step-by-step human oversight, creating automation that requires more attention than the manual process it replaced. The proposed alternative: define precise outcomes and constraints upfront, then monitor results against dashboards—only intervening on exceptions, like CI/CD pipelines. The hard part is writing measurable intent definitions, but that investment unlocks parallel autonomous agent execution at scale.

• •Stop supervising AI agents step-by-step; instead define outcomes and constraints upfront, then monitor by exception
• •Treat agents as process executors whose outputs need verifying, not autonomous decision-makers needing judgment checks
• •The key investment is precise intent-definition—outcomes, constraints, and escalation thresholds—before the agent starts

Generated with AI, which can make mistakes.