AI Experience Reviews · For Native AI Products
AI Experience Reviews for Native AI ProductsBuilt for the trust, adoption, and retention problems AI products face.
I'm Jayasri, a Senior Product Designer at Microsoft specializing in AI experience, copilots, agents, and human–AI collaboration. Through a structured AI Experience Review, I help founders and product teams uncover trust gaps, onboarding issues, prompting friction, and workflow challenges before they impact growth.
What you'll receive
A complete AI Experience review.
Designed to help your team improve trust, adoption, and retention.
AI Product Experience Review
What I evaluate: AI onboarding, prompt experience, trust signals, agent workflows, human–AI collaboration, and workflow integration.
AI Experience Scorecard
Structured assessment across key dimensions. Includes scores, findings, and risk areas.
Recorded Walkthrough
45-minute personalized video review. Share with your team and revisit anytime.
Executive Summary
Founder-friendly report highlighting biggest risks, biggest opportunities, and priority areas.
Prioritized Recommendations
Organized by Impact, Effort, and Business Value. The most important deliverable of the engagement.
Strategy Debrief Session
60-minute discussion to review findings and align on next steps.
Watch: Why AI products struggle with adoption
A note from Jayasri
Over the last few years, I've watched teams spend months improving models while ignoring the experience around those models.
The result? Better AI, but poor adoption.
Most users don't abandon AI because the model is wrong. They abandon it because they don't know when to trust it, what to do next, or how the AI fits into their workflow.
In this short video, I explain the patterns I repeatedly see in AI products and how an AI Experience Review helps uncover them.
— Jayasri
Senior Product Designer, Microsoft
A look inside
What a review looks like.
Expand each category to see the kind of scoring, findings, and recommendations your team will receive — based on patterns I see again and again in AI products.
Sample content. Your review will be specific to your product.
AI Experience Scorecard
Acme Copilot · v2.3
Adoption risk
Medium
Common findings
- Confidence in AI output is unclear.
- Missing trust signals around generated content.
- Users can't see the AI's limitations.
Sample recommendations
- Add confidence indicators to AI output.
- Improve transparency around sources and reasoning.
- Clearly communicate model limitations in-context.
The engagement
AI Product Experience Review
Designed for seed-stage to Series A AI startups.
Typical engagement includes
- 4–6 hours of expert product review
- AI Experience Scorecard
- Recorded walkthrough video
- Executive summary report
- Prioritized recommendations
- 60-minute strategy session
Let's talk
Building an AI product?Let's make sure users actually adopt it.
FAQ