Goal · Measure · Improve
Self-Improving AI Agents
Give an agent a goal and a metric, like conversion or win rate. Every run it makes one focused improvement, an independent evaluator measures the result, and its playbook learns from every outcome.
- Goal-Driven Agents That Optimize A Metric You Define
- Independent Evaluator Grades Every Run
- A Playbook Of Proven Lessons, Updated Every Run
- Scheduled Runs That Compound Gains Over Time
Evaluator measures the starting point: 4.1%.
Worker agent reads the playbook and makes one change: a personalized opener.
Independent evaluator agent measures the result…
Evaluator measures 4.6%. Outside the noise band: improved.
Agent learns Personal Openers Lift Replies and ranks the next idea.
Worker agent tries the next ranked idea: pricing in the first email.
Independent evaluator agent measures the result…
Evaluator measures 4.45%, below the best: regressed.
Agent rules it out: Early Pricing Hurts Conversion. Next run fixes it.
Worker agent reverts the pricing and adds an industry case study.
Independent evaluator agent measures the result…
Evaluator measures 5.0%, a new best: improved.
Agent learns Industry Proof Converts Best. The loop keeps going.



