Wisary AI for Product Managers
Transforming Disconnected Insights into Actionable Interfaces
Wisary enables product managers to turn scattered user research into clear, prioritized design decisions. By combining AI-powered analysis with intuitive interfaces, the platform accelerates decision-making, improves team alignment, and ensures features deliver measurable value to users.
Client
Wisary AI
My Role
UX Consulting
UX Design
Prototyping
Tools
Figma
Dovetail
Confluence
Timeline
11 Weeks
May-July 2024
Team
Alina Aminova
Jada Olivia
Shahi Anwar
Project Timeline + Collaboration
Context
Project Overview
Wisary is an AI-powered collaboration platform for product managers, designed to streamline product documentation and team alignment.
I collaborated with the UX team and worked closely with developers to redesign the core experience, focusing on simplifying AI-driven feedback and aligning documentation workflows. The redesigned product was successfully launched.
The Problem
Despite its innovative features, Wisary faced adoption challenges. Product managers often found AI feedback too abstract, meeting outcomes disconnected from documentation, and unstructured workflows difficult to navigate. These frictions caused most users to drop off after their first try, making retention a critical design challenge.
Research
Understanding the Market
Existing tools address parts of the product workflow, but none offer an integrated, AI-driven approach tailored for product managers.
Understanding the Disconnect
We interviewed 22 participants to gain diverse perspectives on product usage, challenges, and expectations. The participant pool was composed of two groups:
・Wisary-provided participants (2 total): Clients and contacts shared by Wisary, representing their current and potential user base.
・Research team’s professional network: Product managers, designers, engineers, and industry experts recruited through our extended network to broaden the range of insights.
This combination allowed us to balance direct user feedback from Wisary’s ecosystem with industry-wide perspectives, ensuring that our findings were both context-specific and broadly relevant.
To synthesize findings from 22 interviews, we used affinity mapping in Dovetail. Recurring themes revealed where users struggled most, helping us define key problem areas and guide the next phase of design exploration.
Define
Why Weren’t Users Coming Back?
・AI feedback lacked context and felt too abstract
・Meeting decisions didn’t reflect in documentation
・PRDs lacked structure—users didn’t know where to begin
・Insight overload created cognitive fatigue
・Didn’t fit into existing workflows
Design
AI-assisted PRD System Overview
A dynamic, non-linear workflow where each module supports continuous improvement across the PRD lifecycle.
Help product managers start faster with clarity and confidence.
Context
User interviews showed that PMs struggled to begin writing PRDs. Blank pages and unclear section structures made it difficult to capture goals and requirements.
Design Challenge
How might we help PMs move from a blank page to a structured, editable PRD draft within minutes?
Solution Overview
The Create Flow introduces AI-generated templates and contextual prompts that automatically adapt to project goals and timelines.It sets a solid foundation for consistent, data-driven documentation.
Impact
・Reduced time-to-first-draft by 60 %.
・Improved PMs’ confidence and readiness to collaborate.
・Established foundation for subsequent flows.
Transform abstract AI feedback into actionable collaboration.
Context
PMs and engineers found AI suggestions too generic. Feedback lacked context, forcing users to manually locate issues in long PRDs.
Design Challenge
How might we make AI feedback specific, contextual, and directly linked to the document?
Solution Overview
The Collaborate Flow introduces inline AI comments tied to document sections.
Feedback becomes visible exactly where it applies, allowing real-time edits and reviews.
Impact
・Feedback became traceable and actionable.
・Reduced cross-tool handoffs between PM and Engineer.
・Reinforced AI learning through real user choices.
Keep documentation and meeting decisions perfectly aligned.
Context
Meeting outcomes were often lost—PRDs didn’t reflect the latest decisions, causing misalignment and outdated information.
Design Challenge
How might we bridge meeting outcomes and documentation seamlessly?
Solution Overview
The Communicate Flow connects meeting records directly with the PRD.Users can upload transcripts, and AI auto-suggests document edits, ensuring the latest decisions are always captured.
Impact
・Reduced documentation lag after meetings.
・Improved visibility of decision-based changes.
・Strengthened transparency across leadership and teams.
Connect documentation to execution and feed results back into AI learning.
Context
PMs used multiple tools—Jira, Slack, Confluence—to manage execution, causing friction and lost updates.
Design Challenge
How might we integrate Wisary into PMs’ existing workflows and close the loop between documentation and execution?
Solution Overview
The Execute Flow transforms finalized PRDs into actionable tasks, automating handoff while capturing feedback for AI learning.The system continuously improves future PRD generation based on execution outcomes.
Impact
・Unified documentation and execution pipeline.
・Reduced manual handoff errors.
・Established AI feedback cycle for ongoing improvement.
Design System
We built the interface based on the Radix Design System, ensuring visual consistency, accessibility, and scalable component structures across Wisary’s AI-assisted workflows.
Reflection
Building Wisary, Flow by Flow
In our final design sprint, we transformed Wisary from a feature collage into a coherent product.By unifying all stakeholder communication under one intent — “Communicate to stakeholders” — the experience became simpler and more intuitive.We also made the meeting-to-document loop tangible: PMs can upload transcripts, review “Unapplied decisions,” and apply updates inline — finally bridging discussion and documentation.With only three days of Dev Mode, we learned to prioritize what truly matters: guidance over clutter.When the prototype was demoed to real PMs, one said,
“It doesn’t feel like another tool. It feels like a teammate.”
What Changed at the End
Next Steps
Usability Testing & Heuristic Validation
Run 3–4 short tests with PMs on:
・Discoverability of the “Communicate to stakeholders” CTA
・Clarity of “Unapplied decisions” indicators
・Comfort toggling AI panel visibility during editing
Real-world Integration
Prototype integrations with Confluence, Slack, or Jira, where PMs already live. This was one of the strongest signals from Ala’s demo feedback.
Empty & Transitional States
Design “first-time” screens — when there are no downstream docs, FAQs, or transcripts — to guide users toward first actions.
System Feedback Design
Add micro-success states (“Decision applied ✓”) across the app for better closure and satisfaction.