AI agents need morethan intelligence.They need goodexperience design.

Help SaaS teams design AI agent experiences that users can understand, guide, trust, and recover when things go wrong.

Discuss your AI agent experience

When AI works technically, but the experience doesn't.

Even when AI is powerful, poor experience can create confusion, reduce trust, and slow down real adoption.

  • Unclear behavior

    Users don't know what the agent is doing or what happens next.

  • Misunderstands intent

    The agent misinterprets requests or loses context over time.

  • Limited user control

    Users cannot easily guide, correct, or take the work back.

  • Poor recovery

    Errors and unexpected outcomes leave users stuck without a clear way forward.

  • Decision uncertainty

    Teams struggle to decide when the agent should act, ask, wait, or hand over to a human.

What we help you design

End-to-end experience design for AI agents, from strategy to detailed interactions.

  • AI Agent Experience Audits

    Identify interaction gaps, confusing behavior, trust issues, and recovery problems in existing AI products.

  • Agent Workflow Design

    Define how the agent interprets intent, uses context, makes decisions, and collaborates with users.

  • Interaction & State Design

    Design progress, waiting, uncertainty, interruptions, confirmations, failures, and handoffs.

  • Trust & Human Control

    Make agent actions understandable and give users meaningful ways to review, guide, correct, or stop them.

  • Prototyping & Validation

    Turn proposed behaviors into Figma prototypes and evaluate the experience before implementation.

From agent behavior to a better user experience.

A structured and collaborative process to design AI agent experiences that work in the real world.

  1. 01

    Audit

    Understand the current product, user journey, and agent behavior.

  2. 02

    Define

    Identify experience gaps, user needs, and the behavior the agent should exhibit.

  3. 03

    Design

    Create workflows, interaction patterns, states, and prototypes.

  4. 04

    Validate

    Evaluate key scenarios, failure paths, and opportunities for improvement.

What you take away

Practical, design-ready outputs that help your team build better AI agent experiences.

  • AI agent experience audit and prioritized recommendations.

  • User journeys and agent behavior flows.

  • Interaction patterns for feedback, uncertainty, and recovery.

  • Figma wireframes and interactive prototypes.

  • Design specifications and implementation guidance.

For teams building AI-powered products.

SaaS founders, Heads of Product, and product teams building AI features, copilots, and agents, or improving an existing AI experience.

  • Building AI features

    Teams adding an agent or copilot to an existing product.

  • Improving agent reliability

    Teams whose agent works in a demo but breaks down in real work.

  • Aligning product teams

    Product, design, and engineering groups that need a shared picture of agent behavior.

Is your AI agent delivering the experience you intended?

Let's examine how your agent behaves, where users struggle, and what to improve first.

Discuss your AI agent experience