Agentic AI Product Strategy for Fortune 100 Telecom

The Challenge

Product Managers were spending 40% of their time on repetitive documentation tasks — writing epics and features in Azure DevOps, creating user stories with acceptance criteria, and drafting process flows. This created PM bottlenecks, inconsistent quality across a 600+ person organization, and slow velocity from concept to dev-ready.

The Approach

Designed a three-part agentic AI system: a Context Agent that ingests business rules and scope, a Generation Agent that creates draft documentation, and a Validation Agent that checks for accuracy and completeness. Designed with human-in-loop review from the start. Piloted with 5 PMs, currently rolled out to approximately 18 PMs with ADO integration in progress.

Key Learnings

• Human-in-loop designed from the start — PMs need control over outputs
• Context quality matters more than model quality
• Enterprise tool integrations (ADO) add significant scope
• Start with willing adopters — organic interest follows