Context Grammar Simulator — Pipeline

Context Grammar · Live Pipeline

Context Grammar running live.

Pick a scenario on the left. Toggle context — watch all four stages recompute in real time.

← Context Grammar
1

Pick a scenario — dinner, commute, hospital, driving at midnight.

2

Toggle a context overlay — add a guest, turn off the lights, make it public.

3

Watch all four stages recompute — the UI at the bottom changes because context changed.

01 Intent 02 Context Tokens 03 Brain · Rules · AX 04 UI Output
01

Intent

What does the user want?
02

Context Tokens decompose the moment

8 signals · sensed in parallel
03

Brain → Rule Engine → AX Patterns

memory · evaluation · named moves
04

The interface assembles itself

no designer drew this for this moment
AI Agent UX Checklist Use this against your own product — 11 dimensions, scored 0–2
0 Missing or unsafe 1 Partially handled 2 Clear, tested, visible in UX If the only win is speed, the design is unfinished.
  1. Situation Reading

    Does the system understand what the user is trying to accomplish, why it matters now, who else may be affected, and what context is missing or stale?

  2. Stakes & Reversibility

    Does the action affect money, health, safety, reputation, or relationships? Is reversal easy and visible? Has the user explicitly authorized irreversible action?

  3. AI Role Fit

    Is the AI playing the smallest useful role? Clerk / Scout / Draftsperson / Coach / Guardrail / Steward — chosen for this situation, not defaulted.

  4. Autonomy Dial

    Is the autonomy level visible? Can the user lower it at any time? Does the system lower it automatically when risk rises?

  5. Consent & Control

    Does the user know what will happen, when, and who is affected? Can they pause, cancel, edit, or undo?

  6. Human Judgment

    Does the AI show key tradeoffs? Does it distinguish facts, guesses, preferences, and judgments? Does it leave the user more capable next time?

  7. Value Conflict Handoff

    When convenience vs. privacy, speed vs. care, or cost vs. trust collide — does the AI return the decision to the human?

  8. Explanation Depth

    Low-risk: concise. Medium-risk: rationale + editable assumptions. High-risk: evidence, uncertainty, consequences, alternatives.

  9. Memory Boundaries

    Can the user inspect, edit, or delete memory? Can work, family, health, and private reflection remain separate?

  10. Error & Repair

    Can the user see what the AI did, reverse it, and report "wrong context" separately from "bad output"? Does the product lower autonomy after serious mistakes?

  11. Success Metrics

    Track reversal rate, manual override rate, trust after error, and user understanding — not only speed or completion rate.