Optimized Intelligence Verification Rules

• Outcome: what “better” means in this domain
• Signals: what you measure repeatedly
• Verification: trends instead of one-offs (avoid noise)
• Decision flow: if/then rules that stay consistent
• Actions: small, repeatable moves you can run weekly
• Feedback: measure results, refine, repeat

• Acting on single data points
• Changing 5 variables at once
• No baseline, no trend window
• No “stop rules”

Verification should become stricter as the cost of being wrong increases. A low-impact content suggestion may need only a basic source check, while a financial, legal, safety, or production decision may require multiple independent sources, stronger provenance, and a higher confidence threshold. OI makes that relationship explicit instead of applying the same standard to every task.

The rule can be defined before execution: identify the risk class, list the required evidence, and specify who has authority to approve the action. That prevents urgency from quietly lowering the verification bar after the workflow has already started.

Ten pages repeating the same statement do not necessarily provide ten independent confirmations. OI verification should distinguish original evidence from copies, summaries, syndicated material, and sources that ultimately depend on the same underlying claim. Independence matters because correlated errors can create false confidence.

A stronger rule prefers primary records when available, then looks for genuinely separate corroboration. When only derivative sources exist, the system can lower confidence or keep the result provisional. This gives the final decision a more honest relationship to the quality of its evidence.

Verification is not only about whether a source is credible. The information also has to be current enough for the decision and specific enough to support the claim. OI rules can define maximum age, acceptable confidence, required fields, and what to do when two high-quality sources disagree.

Contradictions should not be hidden by averaging them away. They can trigger a deeper check, a narrower claim, or an explicit unresolved status. A workflow that can say "not verified" is often more reliable than one that is forced to produce an answer every time.

A verification rule is incomplete if it only describes success. The workflow should also define what happens when evidence is missing, stale, inconsistent, inaccessible, or below the required threshold. Depending on the risk, that result may block the action, request human review, seek another source, or return a limited recommendation.

Recording these failures creates useful operational data. Teams can see which inputs repeatedly break, where source coverage is weak, and which decisions require too much manual intervention. Verification then becomes both a safety mechanism and a way to improve the system itself.

1. Define your outcome and a 14-day baseline
2. Pick 3 signals that actually correlate with the outcome
3. Write a simple weekly playbook you can repeat