Guide · Corrections Become Playbook Improvements
The self-improving AI employee: how corrections become rules
A self-improving AI employee gets better at your work over time — in a way you can see and undo. When you correct it, the correction becomes a durable, visible rule in its instructions, applies on the next job, and carries before/after proof. It's bounded, visible instruction improvement — not invisible, runaway self-editing.
What “self-improving” should actually mean
The useful version of self-improvement is not a black box that quietly rewrites itself. It's an employee that turns your feedback into a rule you can read, keep, or remove. Three properties make it safe: it's visible (you can see what changed), it's explained (you know why), and it's reversible (you can undo it).
How a correction becomes a rule
- You correct the employee in plain chat — “don't promise same-day delivery,” “always cc the office.”
- The correction becomes a durable learned rule and appears in the employee's Instructions and its “How it's improved” surface.
- The rule applies on the next job — the employee speaks and acts from its updated state.
- Before/after eval proof shows the same kind of work improving, so the change isn't just a claim.
Why this beats workflow-maintenance debt
With fixed automation, every exception becomes another branch you own forever. Mistakes become corrections, not permanent workflow debt. Correct the employee once, see the instruction update, and watch the next run improve — instead of maintaining a growing canvas of edge cases.
The guardrails on learning
Honest bounds
Self-improvement is a shipped product loop, but it is not magic. Learning is not perfect, not fully automatic, and not shared across customers — your employee's memory and rules are yours. Every learned rule stays visible in the Instructions surface, and you can edit or remove it. The employee improves its own instructions on a bounded shape; it does not silently escape your control.
Frequently asked questions
- Does the AI employee change itself without me knowing?
- No. Improvements come from your corrections and show up as visible rules in its Instructions surface. You can see what changed, why, and undo it. It's bounded, visible instruction improvement — not invisible self-editing.
- Does it learn perfectly, or from other customers' data?
- Neither. Learning is not perfect and not shared across customers. Your employee's memory and learned rules are private to your account.
- How do I know a correction actually stuck?
- The learned rule appears in the employee's Instructions, applies on the next job, and carries before/after eval proof so you can see the same kind of work improving.
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