Humanize Loop

What it does

Humanize Loop keeps humanization inside the UI development loop instead of treating AI-slop as a final cosmetic cleanup. Its internal routing layer is the Switchboard: a small control plane that decides whether intervention is needed, what depth is appropriate, which specialist fits the moment, whether a validator is useful, and when to stop.

The operating rule is route, don’t pile. The default ceiling is one primary Humanizer and at most one validator. If the interface is already intentional and fit for purpose, intervention: none is a successful outcome.

When to reach for it

Use it when AI-assisted frontend work needs deliberate design judgment at the start, during implementation, at a checkpoint, during repair/rescue, or before shipping. It is most useful when “this looks AI-generated” is too vague to justify a redesign by itself.

The Switchboard first preserves the product context, then classifies the surface, lifecycle moment, problem depth, and minimum useful intervention. A product dashboard, a marketing page, a small component, and a structural rescue should not automatically receive the same Humanizer.

What one run does

1. Inspect existing product intent, design tokens, components, IA, responsive behavior, and accessibility constraints.
2. Decide whether humanization is materially needed.
3. Classify the UI context and deepest relevant problem.
4. Select the smallest appropriate intervention and at most one primary specialist.
5. Add one validator only when a separate verification pass is useful.
6. Preserve intentional patterns and stop before preference-level polishing becomes churn.

External Humanizers remain independent tools or services. Humanize Loop may route to them when they are already available, but it does not silently install, update, vendor, or pretend to have executed them.

Common failure modes

• Treating every gradient, card, rounded corner, or familiar pattern as proof of AI slop.
• Loading several taste systems at once and producing contradictory redesign pressure.
• Letting an external Humanizer overwrite an established product system.
• Escalating a cosmetic or compositional issue into a structural redesign without diagnosis.
• Replacing generic AI defaults with an equally generic “tasteful minimal” house style.
• Reporting fake precision such as a numeric “human score.”

It’s working if

The UI has fewer material generated-looking defaults while still feeling like the same product. The intervention is explainable, bounded, and matched to the task; existing behavior and usability remain intact; and the process can explicitly conclude that no further humanization is necessary.

Where it fits

Humanize Loop is primarily an Execute-phase operating skill, but it intentionally spans the UI lifecycle from prevention through final verification. PAOS publishes this as an editorial capability description, not as an executable Skill marketplace entry or a mirror of the private Skill Registry.