Beyond the agent :
Informing stealth ai product
strategy
Foundational UXR for an AI startup led by Matt Barclay (ex-Google PM) optimizing cross-functional workflows for agentic systems. This research validates stealth-mode solutions by mapping complex user flows, identifying evaluation gaps, and defining system-driven UI.
Role
UX Reseacher
Team
2+ Researchers
Timeline
1 month
March 2026- Jan 2024
%201.svg){kind=small}
Problem
Plenty of competition exists for evaluating and improving AI. We are advising a stealth startup on collaborative efforts and future market gaps.
Outcome
The project performed a multi-modal investigation involving desk research of the 2026 AI landscape, a competitive analysis of five major industry tools, and six qualitative user interviews with PMs, ML Leads, and Engineers. The team synthesized these findings to identify critical patterns in AI ownership, fragmented workflows, and a heavy reliance on custom evaluation pipelines over generic external tools.
.svg){kind=small}
Impact
Informed Product Strategy for a Funded Stealth-AI venture.
This thorough analysis identified critical market gaps in LLM evaluation processes and tools.
Data-driven insights: integration-based onboarding flow, hybrid deployment models, and adaptive pricing strategies, for example.