Purpose

This guide outlines five initial plays to introduce agentic behavior into a product with minimal disruption, delivering measurable value while setting the foundation for longer-term AI-native experiences.

How to Evangelize

Frame agentic interfaces as a low-risk path to high-value differentiation. Emphasize:

  • Reduced friction in key user workflows
  • Reduced friction in key user workflows
  • Higher re-engagement through contextual responsiveness
  • Data-driven refinement loops to increase user success over time

Position it as a modern enhancement of usability; not a replatforming effort.

Where to Begin

Select one critical but non-core workflow (e.g., task setup, checklist, feedback submission) where:

  • Friction is measurable
  • User success is easy to define
  • Agentic intervention can be tested side-by-side with the current experience

Pilot a single agentic play, observe outcomes, and build momentum.

What to Expect

  • Modest technical effort for high UX upside
  • Initial skepticism from product and UX teams
  • A learning curve in orchestrating transient UI elements dynamically
  • A need to tune prompts and interactions based on usage data

How to Overcome Objections

Objection: "It’s just UX; we don’t need AI for that."

Response: Agentic UX adapts to user context in real time, something static flows can’t do. This is about intelligence, not just design.

Objection: "It complicates our product surface."

Response: The opposite. It reduces UI footprint by surfacing only what’s relevant in the moment.

Objection: "We can’t justify it without hard ROI."

Response: Pilot metrics (e.g., flow completion, task success, re-engagement) can quantify gains and set the stage for scaled investment.

Framing Business Value by Play

  1. Micro-Orchestration → Faster task completion, lower abandonment = efficiency
  2. Suggest, Don’t Command → Higher user success = reduced support burden
  3. Intent Replay Prompt → Reactivation of dormant users = retention uplift
  4. Agentic UI Node Injection → Faster decision inputs = higher productivity
  5. Path-Aware Undo → Error recovery = user trust and operational quality

Agentic Interface: First-Step Experiments

Goal

Introduce agentic behavior in ways that reduce user friction and show smart, context-aware responsiveness.

1. Micro-Orchestration

  • Use case: Multi-step form or workflow
  • Agentic move: Present next most relevant step based on user state
  • Test it by: A/B static vs. adaptive flow
  • Success signal: Higher completion rates, lower drop-off

2. Suggest, Don’t Command

  • Use case: User pauses or hesitates
  • Agentic move: Inline nudge like “Want help setting this up?”
  • Test it by: Trigger on idle/partial entry
  • Success signal: Increased task success

3. Intent Replay Prompt

  • Use case: Returning user with incomplete work
  • Agentic move: “Pick up where you left off?” prompt
  • Test it by: Follow-through on resumed flows
  • Success signal: Higher re-engagement

4. Agentic UI Node Injection

  • Use case: Workflow triggered by event or conversation
  • Agentic move: Inject structured input (e.g., form, file picker) inline
  • Test it by: Compare static vs. dynamic interaction
  • Success signal: Faster completion, user satisfaction

5. Path-Aware Undo

  • Use case: User removes or alters data
  • Agentic move: “Undo last 3 changes?” contextual prompt
  • Test it by: Offer in low-risk flows
  • Success signal: Lower error rate, higher trust

This is a pragmatic path to modern interface intelligence. Start small. Measure fast. Expand deliberately.