Create Action Funnel (CREATE)

Canonical
WendelBehavioral EconAgentic UX

Confidence

95%

Cognitive Load

High

Evidence

production validated

Impact

product

Ethical Guardrail

Agent must cite the specific data source or policy reference before executing any action on behalf of the user.

Design Intent

Every meaningful action in software is the result of a cognitive journey. The CREATE funnel asserts that action is not a moment -- it is a sequence of psychological gates. Users do not fail to click a button. They fail to notice, emotionally engage, believe the action is worthwhile, feel capable, or act at the right moment. This pattern exists to help designers and AI agents identify exactly where behavior breaks down and intervene with precision rather than intuition.

Psychology Principle

Five mental events must align for any user action: Cue, Reaction, Evaluation, Ability, Timing, then Execute.

Description

The CREATE funnel is the foundational diagnostic model for every flow in a product. Each stage represents a cognitive gate the user must pass through before acting. If any gate fails, the action does not happen. For AI agents, the funnel provides a diagnostic framework: when a user stalls, identify which gate is blocked and intervene there. When used correctly, CREATE transforms product design from guesswork into behavioral engineering.

When to use

Every single product flow. This is the default diagnostic lens. If users are not completing an action, the responsible CREATE stage must be identified before UI changes are proposed.

Example

Stripe payment processing flow: email notification triggers Cue, payment summary shapes Reaction, line-item breakdown supports Evaluation, pre-filled payment methods enable Ability, due-date awareness drives Timing, one-click pay now enables Execute.

Autonomy Compatibility

SuggestConfirmAuto

Behavioral Objective

Users complete critical workflow actions before deadlines without abandonment.

  • Users complete multi-step workflows without abandonment
  • Users escalate ambiguous items earlier in the process
  • Users develop confidence in AI-supported decision making

Target Actor

role

Product Manager / Product Analyst / Engineering Team Lead

environment

Time-constrained, outcome-sensitive product workflows

emotional baseline

Mild anxiety, high accountability pressure

ai familiarity

medium

risk tolerance

low

Execution Model

1

cue

User must notice the opportunity to act.

User receives invoice but does not open payment flow.

2

reaction

User forms emotional response.

User dismisses alert or postpones action.

3

evaluation

User decides whether action is worth effort.

User opens flow but abandons before starting.

4

ability

User must feel capable of completing action.

User stalls in form or navigates away.

5

timing

User must perceive urgency or appropriateness.

User delays until after the deadline.

6

execute

Final irreversible or meaningful action occurs.

User hesitates indefinitely at confirmation.

Failure Modes

Excessive friction causes shadow workflows (email/Slack bypass)

Use Confidence Signaling to calibrate urgency

feature

Over-automation reduces user ownership of outcomes

Bind automation to Autonomy Dial position

feature

Poor cue placement leads to missed critical actions

Position cues within existing workflow context

micro

Cognitive overload at Ability stage causes abandonment

Apply Progressive Disclosure for complex workflows

feature

Timing signals too aggressive trigger alert fatigue

Adapt signal frequency based on user response history

micro

Agent Decision Protocol

Triggers

  • User fails to act within expected workflow window
  • High-risk decision detected
  • User repeatedly abandons task

Escalation Strategy

L1: Diagnose failing CREATE stage via behavioral_signals

L2: Nudge -- resurface cue, adjust timing, add confidence signal

L3: Restructure -- simplify form, add progressive disclosure, restructure flow

L4: Constrain -- lock Autonomy Dial to confirm_execution, add Strategic Friction

L5: Yield -- flag for human designer or domain expert review

Example

User abandons invoice payment flow -> ability_failure signal fires (form_focus_time > 90s) -> L1 diagnoses Ability failure -> L2 nudge adds inline help -> still failing -> L3 retrieves Action Structuring -> proposes simplified 3-field payment form with pre-filled amounts.

Behavioral KPIs

Primary

  • % of critical actions completed before deadline
  • Median time from notification to action initiation
  • Workflow abandonment rate

Risk

  • Number of post-execution error discoveries
  • Escalation frequency

Trust

  • User-reported confidence in AI recommendations
  • Autonomy Dial usage distribution

Behavioral Signals

cue_failure

alert_viewed=false AND time_since_notification > 600s

scroll_depth < 20% on action page

reaction_failure

alert_dismissed=true

action_postponed=true

evaluation_failure

preview_opened=true AND action_started=false AND dwell_time > 30s

ability_failure

form_focus_time > 90s

field_error_count > 3

navigation_away_from_form=true

timing_failure

action_started=true AND time_to_deadline < 24h

action_completed_after_deadline=true

execute_failure

confirmation_dialog_open_time > 30s

confirmation_abandoned=true

Decay Monitoring

Revalidate when

  • Autonomy capabilities expand
  • Workflow complexity increases
  • New user segments onboard

Decay signals

  • Increased abandonment at previously stable stages
  • Reduced alert engagement
  • Rise in manual workarounds

Pattern Relationships

Related Patterns

Canonical Implementation

Notification -> Alert Summary -> Intent Preview -> One-click Action Start -> Step-by-step Flow -> Strategic Confirmation -> Audit Log Entry

Telemetry Hooks

alert_viewedaction_startedaction_completedescalation_triggered

Tags

wendel-corefoundationalagent-readycognitive-loadhigh-stakesdiagnostic