Problem
An AI agent for DevOps needs to fit the working reality of enterprise SRE teams: CI/CD processes, security requirements, and compliance constraints.
Insight
The product direction needed evidence from the people doing the work. Discovery and validation sessions provided a way to test assumptions before committing to delivery.
Execution
At Progress, I worked across 34 discovery and validation sessions, tested ten hypotheses, and analyzed eight agent competitors. I translated the resulting direction into eight PRDs and 36 epics.
In parallel, I explored three go-to-market channels and supported conversations with prospective users.
Alignment challenge
Design refinement was slowing delivery because every surface also needed design-system, security, and compliance approval. I defined a good-enough release threshold, secured approval on the core workflow, and moved implementation downstream while preserving the required controls.
Impact
- Validated eight of ten hypotheses.
- Moved from MVP to demo-ready in four months.
- Converted conversations with ten prospective users into three pilots.
- Built a qualified waitlist of 40 people across three channels.
This is a public overview based on my résumé. Internal PRDs and customer details remain private.
Reflection
I would involve design-system and compliance reviewers at kickoff and make approval checkpoints explicit in the PRD. That would surface constraints earlier and reduce late-stage iteration.