autonym (n.) — a name a thing gives itself.
We build AI agents that improve themselves.
Most AI agents are frozen the day they ship. Ours learn from every task — remembering what worked, correcting what didn't, and growing new skills without retraining.
Get in touchAgents shouldn't be frozen at deployment.
Today's AI agents don't get better with use. The same prompt makes the same mistakes on day one hundred that it made on day one, and every fix waits for a human to notice, diagnose, and rewrite. We think the missing layer is a feedback loop — one that lets an agent learn your work on the job, safely.
The improvement loop
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1
Act
Agents do real, multi-step work: research, writing, operations, code.
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2
Evaluate
Every outcome is scored against what was actually asked.
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3
Learn
Memory and skills update from the score: wins are kept, mistakes become corrections.
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4
Verify
No self-change sticks until it's checked. Improvement is gated, never silent.
What we hold constant
Persistent memory
An agent that forgets you every session can't improve. Ours remember across sessions, projects, and months.
Skills that evolve
Capabilities grow with use — new skills are drafted from real work, not shipped in a retrain.
Oversight built in
Self-improvement without review is drift. Every change an agent makes to itself is evaluated before it's applied.
Talk to us
We're early, and building. If you're a partner or investor who wants to talk about self-improving agents, we read everything.
Email ussupport@autonym-ai.com