The Act / Review / Ignore Rule

In production

AI Design · The named framework behind the patterns · Last updated September 2026

Part of A Field Guide to Trust · updated September 2026

Seen in production: the AdTech case → · the FinTech case →

The Act / Review / Ignore rule Three model scores — ninety-two, sixty-one and twenty-three — each resolving to exactly one verb: act with a visible override, review with the reasons named, or ignore where the model declines to bluff. The Act / Review / Ignore Rule One score, one action — a number never reaches the screen alone. SCORE 92 · HIGH → Act signals named · safe to run Apply Override ↶ SCORE 61 · MIXED → Review reasons on the card, not a tooltip: — recency conflict, panels 12 & 14 — surfaced for a human · never auto-run SCORE 23 · LOW Ignore below the line, the model declines to bluff — the honest no is what makes the act believable.

The Act / Review / Ignore Rule

One score, one action — a number never reaches the screen alone.

  1. Score 92 · high

    → Act

    signals named · safe to run

    Apply · Override ↶

  2. Score 61 · mixed

    → Review

    reasons on the card, not a tooltip: — recency conflict, panels 12 & 14 — surfaced for a human · never auto-run

  3. Score 23 · low

    Ignore

    below the line, the model declines to bluff — the honest no is what makes the act believable.

In the 'Where the rule earned its name' AdTech bullet: 'the roomful of traders from the first line of this page — recommendations shipped as full plans with KPIs and one-click customisation; their accept-adjust-reject rhythm is what later crystallised into the three verbs.'

An unexplained 87% is a shrug with decimals. It reports the model’s mood and assigns the user all of the work: is 87 high for this kind of call? High enough to spend money on? Higher than my own hunch? While the person does that math, the moment to act expires — and a recommendation nobody acts on rounds down to zero, whatever the model’s accuracy says.

The rule: a confidence score should never reach the screen alone. It resolves into an explicit next state before the user sees it — across the products I’ve shipped, three verbs covered the production cases — act, review, or ignore.

The rule, in one sentence

A score never reaches the screen without resolving to a verb — and a person owns where the verbs begin.

Try it — the rule, live

Three scores from the same model. Watch each one resolve to a verb with its reasons — never a naked number. Synthetic data; nothing leaves the page.

1. The score resolves to a verb — not a number

Act. Confidence clears the threshold where the cost of checking exceeds the cost of being wrong. The interface makes acting one motion. Review. The model has a position but not the standing to hold it alone — the interface opens the reasoning, not the spinner. Ignore. Below the floor, a recommendation is noise wearing a number; the interface says so and steps aside.

Confidence bandActionWhat the interface does
HighActOffers a default the user accepts in one motion, undo always in reach.
MediumReviewOpens the reasoning and hands the call to a person. The system declines to decide alone.
LowIgnoreHolds the recommendation back rather than guess, and points to the manual path.

Where each band starts is a product decision someone owns, argues for, and revisits against real outcomes — that ownership is the point a raw score lets nobody take. The rule isn’t the cutoffs. The rule is that a score lands on an explicit next state, never on the reader.

2. “Review” forces the reasoning surface to exist

A verb of review is empty without something to review. So the moment a score lands there, the interface owes the user the handful of signals that drove it, in language the person can test against their own judgment. Build the rule and you have to build the reasoning panel; there is no skipping it.

Even when the user overrules the model, they should see how it got there. A review without a reason is a shrug with extra steps. (See the ML Explainability and Confidence Score patterns for the surfaces that do this.)

3. The override stops being a failure mode

An act the user can’t undo is a bet they never agreed to make. So every recommended action carries a first-class override — not a buried setting, but a path visible at the point of decision.

A user correcting the model inside a review state is not the system breaking; it is the training data the next version needs. Log it, feed it back, and show people their fingerprints on next week’s calls. The first time someone watches their own pushback sharpen the model, the override flips from a fight into coaching. (This is the Human-in-Loop pattern in practice.)

The strongest objection, kept in

“The band edges are arbitrary.” They are — that is the feature. A raw score lets nobody own the cutoff; the rule forces someone to set it, defend it, and revisit it against real outcomes. Arbitrary-and-owned beats precise-and-orphaned in every deployment I’ve shipped.

Ship it: the checklist.

  • Bind every score to exactly one verb — act, review, or ignore — before it reaches the screen.
  • Write down where each band starts, and who owns that call. Band edges are a product decision, not a stats default.
  • Build the surface “review” demands. Reasons named on the call itself — not in a tooltip, not in the docs.
  • Give “act” a visible override — one click, logged, and fed back to the model as training signal.
  • Let “ignore” say the honest no. Below the line, the model declines to bluff — the honest no is what makes the act believable.
  • Revisit the band edges against real outcomes on a schedule, not when someone complains.
  • Audit your screens: any score not bound to a verb is decoration. Delete it or finish it.

Where it has run

PE screening and technical diligence run the rule as shipped; media buying ran its ancestor — plans a trader could accept, adjust, or reject. PE screening: 60% faster once analysts stopped re-deriving the score. Technical diligence: three-week cycles to four days. Different stakes, same three verbs — and it holds for agents too: a tool call is an act, a draft is a review, an abstention is an honest ignore. If a score or an action on your screen doesn’t bind to act, review, or ignore, with a reason for every review and an override for every act, it’s decoration. Delete it or finish it.

Where the rule earned its name

No single product taught me this rule — the same pattern kept recurring across the AI work until it earned a name. It runs across these case studies:

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Where this breaks — do not use it here

Skip the rule when every output is safe to auto-apply (no verb needed but Act) or when the volume is so low a human reviews everything anyway — three bands with nothing in them is ceremony. And if the model can’t be calibrated well enough to place the two thresholds honestly, fix that first; verbs on top of noise just launder the noise.