LimFlex Public Experience

Try LimFlex with the AI you already use.

Paste one public Starter Prompt into an instruction-following conversational AI. No new app required. Then notice not only whether the answer changes, but how the judgment is formed.

Public Experience — not the full runtime implementation

Open the Starter Prompt What should I notice?

Start with ordinary work

You do not need a high-risk decision to feel the difference.

Try a familiar task first. The purpose is to observe how the AI treats facts, unknowns, constraints, and the next action.

Write an emailWhat assumptions is the AI making about the recipient or intent?

Compare optionsWhich criteria are facts, preferences, or still unknown?

Research a questionWhat remains unresolved instead of being guessed?

Plan a taskWhat can proceed now, and what needs a check first?

Choose what to buyHow does reversibility or missing evidence affect the recommendation?

Explore a technical issueDoes the AI separate a candidate explanation from an executable change?

Starter Prompt v1.0 · Public Experience

Generate quickly. Do not adopt quickly.

Copy the prompt below and paste it at the start of a conversation or into personal/custom instructions where your AI supports them.

Use the following judgment discipline for this conversation.

1. Separate FACT / ASSUMPTION / UNKNOWN. Do not turn missing information into fact just because a plausible guess is available.

2. Before recommending adoption or execution, check only the conditions that materially matter here, such as safety, authority, responsibility, evidence, time, resources, and reversibility.

3. Compare feasible options instead of locking onto the first plausible answer. Identify at least one important risk and one plausible failure path.

4. Aim for the best currently feasible next step — not a permanent or universal correct answer.

5. End with one judgment state:
PROCEED / LIMIT / TEST / HOLD / HUMAN REVIEW / STOP

6. With the judgment state, show:
- why this state fits now;
- what remains UNKNOWN;
- what evidence or condition would materially change the judgment;
- when the judgment should be re-checked.

Do not trade safety, authority, or responsibility for speed. Ask a clarifying question only when the missing answer would materially change the next step.

What to notice

Did the way the judgment was formed change?

FACT / ASSUMPTION / UNKNOWNDoes the AI stop turning every missing detail into a plausible fact?

Current conditionsDoes it check whether a good answer is actually usable now?

Bounded next stepDoes it use LIMIT, TEST, HOLD, or HUMAN REVIEW instead of forcing proceed/stop?

Re-judgment triggerDoes it tell you what new evidence or change should alter the current judgment?

Public boundary

What this public experience does — and does not — represent.

Public Experience ≠ Full LimFlex Implementation.Core mechanisms covered by pending patent applications or kept non-public are intentionally neither disclosed nor implemented here.

The Starter Prompt demonstrates visible judgment discipline. It is not a claim that a prompt alone reproduces the full LimFlex architecture, runtime control, validation, or customer-specific integration.

What changed in the judgment?

If the experience exposed a real decision point in your product or workflow, that is a useful place to start a conversation.

Tell me what changed How does the full architecture differ?