Keep Automated Agents on Proposals, Not Auto-Writes

A durable pattern for agentic systems: let agents propose changes rather than commit them directly. When an agent derives candidate links, updates, or entities from activity logs, route those findings into a human-gated review step instead of writing straight to your source of truth. The agent does the tedious extraction; you keep the final say.

This matters most when the agent works from noisy signals—transcripts, metadata, fuzzy name matches. Automated inference will produce near-duplicates and false positives (the same entity spelled two slightly different ways, a match that looks right but isn’t). A proposal queue turns those errors into a quick accept/reject decision rather than silent corruption you discover months later.

The cost is a small amount of review friction; the payoff is trust. You can let agents run broadly and aggressively precisely because nothing they surface becomes permanent without a human nod. Aggressive discovery plus conservative commitment is a healthier balance than trying to make the agent perfect enough to trust with writes.