Action Structuring (Tailor, Simplify, Make Easy)
CanonicalConfidence
Cognitive Load
Medium
Evidence
production validated
Impact
feature
Ethical Guardrail
Never simplify to the point of removing necessary security or accessibility checks.
Design Intent
In product development, the gap between a feature existing and a user actually completing the action is almost never a UI problem -- it is an action design problem. The form has too many fields. The workflow assumes knowledge the user does not have. The steps are sequenced for the system, not the human. Action Structuring attacks the action itself before anyone touches a wireframe. By forcing the three-step discipline of Tailor, Simplify, and Make Easy, it prevents the most expensive design mistake in enterprise software: building a pixel-perfect interface around a fundamentally broken action. For AI agents, this pattern is the playbook for how to restructure a workflow when the CREATE funnel diagnoses an Ability failure -- the agent does not just add help text, it redesigns what the user is being asked to do.
Psychology Principle
The target action itself can be redesigned to be more feasible before any UI is built.
Description
Wendel's three-step process for making any action easier. First, Tailor it to the specific actor and context. Then Simplify by removing unnecessary steps and decisions. Finally, Make it Easy by reducing physical and cognitive effort through defaults, templates, and one-click paths. This pattern is applied before UI design begins -- it shapes what the interface needs to support.
When to use
When the target action exists but users aren't completing it. Redesign the action before redesigning the screen.
Example
GitHub PR creation: Tailor to repo type (frontend vs. backend), Simplify to 3 fields instead of 12 (title, description, reviewers), Make Easy with AI-generated PR description from diff and one-click submit.
Autonomy Compatibility
Behavioral Objective
Users complete target actions with minimal unnecessary cognitive or physical effort by restructuring the action itself.
- Forms and workflows contain only the fields and steps required for the specific actor and context
- AI agents pre-fill, default, and template wherever policy rules allow
- Abandonment rates drop because the action matches the user's actual capability and context
Target Actor
role
Engineer / Designer / Product Analyst
environment
Fast-paced product team environment with limited time, often context-switching, frequently interrupted
emotional baseline
Task-driven, impatient with unnecessary steps, focused on getting back to deep work
ai familiarity
low-to-medium
risk tolerance
medium for routine submissions, low for security-linked actions
Execution Model
tailor
Customize the action to the specific actor role, team, project type, and context. A frontend engineer creating a PR needs different fields than a platform engineer submitting an infrastructure change.
All users see the same generic form regardless of role or team.
simplify
Remove every step, field, and decision that is not strictly necessary for this specific actor in this specific context. Challenge every required field.
Form has more than 5 fields for a routine action, or workflow has more than 3 steps for a standard submission.
make_easy
Reduce the remaining effort to the absolute minimum through defaults, pre-fills, templates, and one-click paths.
User must manually enter data that the system already has, or no defaults are offered for predictable fields.
validate_compliance
Verify that simplification has not removed any required security or policy fields or steps. Required fields are never candidates for removal.
A required field was removed during simplification.
Failure Modes
Over-simplification removes a required policy field
Maintain a required field registry that blocks removal of protected fields. Agent must check registry before recommending any field removal.
Tailoring creates too many variants, making maintenance impossible
Limit to 3-5 role-based variants. Use conditional logic within a single form rather than separate forms per role.
AI pre-fill introduces incorrect data that users accept without checking
Pair pre-filled fields with Confidence Signaling. Flag low-confidence pre-fills with visual indicator and verification prompt.
Action restructuring invalidates existing training materials and workflows
Version the action structure. Provide migration guidance and in-app onboarding for restructured workflows.
Agent Decision Protocol
Triggers
- CREATE funnel diagnoses Ability failure
- Form abandonment rate exceeds 25%
- User stalls on form for >90 seconds
Escalation Strategy
L2: Nudge -- offer to pre-fill remaining fields based on project data
L3: Restructure -- propose simplified form variant tailored to user's role and current context
L4: Constrain -- reduce form to minimum viable fields with validation check, defer optional fields to follow-up
L5: Yield -- flag workflow for UX review if restructuring does not resolve abandonment
Example
Engineer stalls on 12-field PR creation form (form_focus_time > 90s) -> Agent detects Ability failure -> L2 offers to pre-fill 8 fields from repo metadata and diff analysis -> user accepts but still stalls on reviewer selection -> L3 proposes 3-field simplified form with auto-suggested reviewers based on CODEOWNERS -> user completes in 30 seconds -> agent logs restructured form variant for future use.
Behavioral KPIs
Primary
- Action completion rate (pre vs. post restructuring)
- Average time to complete action by role
- Field count per form by workflow type
Risk
- Required field omission incidents (target: 0)
- Pre-fill error rate (incorrect AI-generated defaults accepted by user)
Trust
- User satisfaction with form complexity (survey)
- Pre-fill acceptance rate (users keeping AI defaults vs. overriding)
Behavioral Signals
ability_failure
form_abandonment_rate > 25%
average_form_completion_time > 3x expected
field_error_count > 3 per session
over_simplification
required_field_missing=true
user_adds_manual_note_to_compensate_for_missing_field=true
pre_fill_distrust
pre_fill_override_rate > 50%
pre_fill_field_cleared_and_retyped=true
Decay Monitoring
Revalidate when
- New policy requirements add mandatory fields
- New user roles onboard with different context needs
- Action completion rates decline after initial improvement
Decay signals
- Rising abandonment rates on previously restructured forms
- Increasing pre-fill override rates (data quality may be degrading)
- New required fields not yet integrated into simplified variants
Pattern Relationships
Supports
Amplifies