Improving your agents in production.
Big launch coming in four weeks.
Most agent tooling stops at the classic Observe - Evaluate loop. You can stop, pause, insert a human into your flows. But it mostly happens in development. Once agents hit production they're on their own, and engineers lean on Sentry or PostHog to find out something broke. Then improvement is you, by hand: digging through traces, tuning a prompt, redeploying, hoping.
The system you use to know what your agents are doing needs to be executed through the agents you use every day.
This launch changes that.
When something breaks in prod, you shouldn't get an alert and a spike on a dashboard. You should get the answer: what went wrong, why, and what to change. Not a debugging exercise. Not manual. Not broken by every model update.
Today Prefactor lets you:
Evaluate agents in development using production or synthetic data. Bring your own evals or use Prefactor's heuristics and technical metrics, and track designed behaviour against actual.
Move agents from dev to prod and compare versions across models, prompts and schemas.
Control your agents. Stop on a specific scenario, insert a human when a conversation gets difficult, pause for a deeper look.
This launch completes the loop: Observe - Evaluate - Control - Improve. AI evaluating AI, with improvement as the output instead of the homework.
We want your feedback. How are you improving your agents today? By hand? Would this solve your problem?
Replies