AI Product & UX Design

Design AI people understand before they decide to trust it.

We shape the experience around the model, from discovery and first use to uncertainty, recovery, and human handoff. The result is an AI feature people can understand, use with confidence, and return to.

  • Copilot and assistant design
  • Prompt experience
  • Trust and confidence
  • Failure recovery
Book a discovery callSee what we build
app.yourproduct.com/reports/q3

Why did Pro revenue dip in August?

Pro churn rose to 4.1% in August, mostly accounts on annual renewal. New Pro sales held steady.

The copilot answers from the open report and shows which rows it used.

  • Show August churn38 accountstable
  • Compare to Julyside by sidechart
  • Filter annual plansrenewals onlyfilter
Apply filterReview first

In-product copilot

The problem

A capable model cannot rescue a confusing experience.

Users judge an AI feature by the moments around the answer. They need to know where it belongs, what it can do, why they should trust it, and how to recover when the result misses the mark.

We design those moments as part of the product. Sources, confidence, loading, no-answer, edit, undo, and handoff are not edge cases. They are the experience.

What we hear

We shipped an AI assistant. It works, but people try it once and leave. They do not know what to ask, they cannot check the answer, and there is no graceful way out when it is wrong.

Why this matters now
What we do

We design the human side of the AI layer.

  • 01
    Copilot and assistant design

    Put help inside the work with a clear purpose, useful entry points, and a fast path back to control.

    Targets adoption
  • 02
    Prompt experience

    Shape inputs, defaults, examples, and guardrails so users do not need to learn prompt engineering.

    Targets activation
  • 03
    Trust and confidence

    Show sources, uncertainty, and system limits at the moment a person needs to decide.

    Targets trust
  • 04
    Failure recovery

    Give users a clear way to correct, retry, edit, escalate, or continue without the AI.

    Targets completion
  • 05
    AI onboarding

    Introduce the feature at the right moment and guide users to a useful first outcome.

    Targets activation
  • 06
    Human-in-the-loop flows

    Let people approve, monitor, change, and undo AI actions before they affect important work.

    Targets confidence
How we build it

From a blank prompt to a trusted product moment.

Step 01
Define the job and the trust bar.

We agree on what the feature does, who it helps, which metric matters, and what trustworthy use means.

Weeks 1-2
Step 02
Map the complete interaction.

We design discovery, input, response, source, uncertainty, correction, and handoff as one flow.

Week 3
Step 03
Prototype the real behavior.

We connect realistic responses to a clickable experience, including wrong, partial, and empty results.

Weeks 4-7
Step 04
Test where trust breaks.

We put the prototype in front of users and fix the moments that confuse, surprise, or slow them down.

Week 8
Step 05
Hand over the system.

Your team receives the components, states, copy, prompt structure, and interaction rules needed to build.

Week 9
The method

Interaction craft for uncertain software.

The tools support the experience. The important work is making every state understandable and useful.

  • 01Interface designFigma flows and components for the product surface where the AI will live.
  • 02Working prototypesRealistic interactions wired to live or simulated responses so the experience can be tested.
  • 03Reusable patternsCopilot panels, source citations, suggestion chips, confidence cues, and review states that scale.
  • 04Prompt and response designOutput structure, system instructions, and guardrails that keep the experience consistent.
  • 05Usability testingSessions focused on comprehension, trust, and recovery, not only whether a task can be completed.
  • 06State and safety reviewA deliberate pass over loading, low confidence, no answer, partial answer, error, and handoff.
What you get

An AI experience your team can build and users can trust.

yourproduct.com/ai-product-ux-design/deliverables
  • Interaction and flow designsThe complete path from discovery to the core loop and every failure state.
  • Working prototypeA realistic demo wired to live or simulated AI responses.
  • Usability findingsWhat users understood, where trust broke, and what changed as a result.
  • AI interaction patternsReusable source, confidence, undo, suggestion, and recovery components.
  • Prompt experience specThe input structure, output shape, and guardrails behind the feature.
  • Developer-ready handoffStates, copy, components, and rules your engineers can build from.
The Ship-It Guarantee

We agree on the scope and launch date before the build begins. You always know what is included, what is out of scope, what comes next, and when it will ship. If we miss the deadline because of our work, the final payment is on us.

The working agreement

Clear scope, close collaboration, useful handoff.

The same operating commitments apply whether you start with an audit, a build, a rescue, or growth work.

  • Founder inevery engagement
  • Senior teamno shared pool
  • Fixed scopeprice agreed first
  • Weekly reviewshared channel
  • Your repodesign files
  • Stop anytimeno notice period
The usual path
  1. 01Start here
    AI Experience Audit

    A fixed price, two week audit that finds where AI can move a metric in your product, and where it cannot.

    • Ranked AI opportunities
    • Projected return by metric
    • Adoption and friction review
  2. 02
    AI Experience Build

    We build the opportunity your audit proves. Fixed scope, fixed price, same team from strategy through handoff.

    • AI experience design
    • Production build in your stack
    • Guardrails and fallbacks
  3. 03
    AI Growth Sprints

    Keep improving the AI layer after launch. Book one sprint at a time when the next improvement is clear.

    • Plan against the audit projection
    • Evals and live monitoring
    • One improvement per sprint
Built for people and their agents

Design the layer people use and agents can understand.

Your buyers use agents to research products, and your users will ask agents to complete work inside them. We design the boundaries, sources, and actions for both sides of that interaction.

  • Agentic website

    A site with clear, machine-readable answers that agents can cite for buyers. Your team keeps approval over what gets published.

    yoursite.com/llms.txt
    • Structured source
    • Machine-readable pages
    • Review before publish
  • This service

    Agentic application

    An agent inside the product that plans and acts with visible steps, clear approval points, and a way to undo the work.

    • Planning
    • Needs approval
    • Completed
    • Handed back

  • Agentic workflows

    Agents that run repeatable work behind the product, with checks, logs, and a human checkpoint when a wrong action is expensive.

    TriggerAgentReviewSystem of record

Not sure which one you need? The AX Audit covers AI and agentic experience: how people use your AI, and how agents read and act on your product.See the AX Audit

The team behind the work

Senior product, design, and engineering in one room.

  • 11companies the team has built insideEmployment and contract work, 2019 to today
  • 13products shipped to productionCounted, not estimated
  • 8industries servedThe same eight on the industries page
  • 7+years shipping softwareFounder, first production release to today
  • 10+senior designers and engineersEvery one has shipped to production
Where the team has built
In their words

I had to hire Shahriar twice, once at Agora and once at Timescale and hiring him was one of the best decisions I made. He is so reliable, hardworking, and always willing to go the extra mile to get the job done. His technical skills are top-notch, and save a lot of time and effort for the team. I cannot recommend him enough!

Emily KimChief of Staff, ElectricSQLHired 2x, @Agora and @Timescale
Where the layer fits

Where this service does its best work.

A revenue product, a healthcare workflow, and a developer tool need different boundaries. See how the work changes with the context.

Service questions

Questions your team may ask.

StillCurious?Ask us anything about the layer, the process, or what it costs.Talk to Us
Can a good model carry a mediocre interface?

No. Users judge what they can ask, what they can verify, and what happens when the answer is wrong. A capable model still needs a clear and trustworthy product experience.

How do you design for wrong answers?
Do you only design, or can you build too?
What do we get at the end?
Do you test with real users?
Can you work inside our existing design system?
Do we need an AI feature before we start?
Next step

Design is where the layer earns adoption.

A feature nobody understands will not move a metric, even when the model is capable. We make the useful path obvious and the limits visible before the feature reaches production.

The audit chooses the opportunity and the number. We turn that decision into the product experience your users see, trust, and use.

Book a discovery call

Design an AI feature people return to.

We find the opportunity, shape the interaction, and design the trust details that make adoption possible. Not sure where to start? The AX Audit ranks the options first.

  • NDA from the first conversation.
  • Response within 24 hours, guaranteed.
  • Founder-led from first call to handoff.
Shahriar P. Shuvo

Every inquiry receives a focused reply within 24 hours. Qualified projects receive a clear proposal within 3 business days.

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