Solutions
Start with the problem you already recognize.
Three operating contexts. One judgment idea: re-check what is feasible now before intelligent output becomes consequence.
The answer can be good while the execution context has moved.
AI Judgment Wrapper
When a good answer is no longer enough.
Re-check the situation before action becomes consequence.
Experience can help — but experience is not authority.
Autonomous AI Judgment
Learn without turning experience into permission.
Grow judgment with the product while re-checking reality.
Local controllers may each be valid while the whole system repeats.
Robotics Judgment
When no controller is wrong — but the system does not converge.
Bring valid controllers toward a feasible next state.
Common design
Keep the host. Add judgment where combined conditions become difficult.
LimFlex does not move every known rule, safety function, or deterministic restriction into an AI wrapper. Existing design stays first.
Keep what should already be designed.
- Known rule → keep it explicit
- Known safety limit → keep it enforced
- Known access restriction → keep it encoded
- Certified control → keep its authority
Add LimFlex where judgment changes.
- Context or evidence changed
- Experience may be stale
- Authority differs now
- Locally valid decisions conflict
- The same unresolved state returns
Which failure pattern looks familiar?
You can start with one bounded problem instead of choosing a full architecture.