DMO Use Case Library with Auto-Extraction
Build and maintain a public library of AI use cases, auto-extracted from daily work logs.
Overview
A living library of AI agent use cases is published to the organization's blog, showcasing real workflows and outcomes. Every night, a cron job reviews the day's session log, identifies new replicable patterns, genericizes them to remove internal details, and adds them to the library. The site auto-deploys with updates.
How It Works
The extraction agent reads daily logs (memory/YYYY-MM-DD.md) and looks for work that solved a real problem, could be replicated elsewhere, and isn't already in the library. It applies substitutions to remove person names, organization names, and internal agent identities, then formats the use case with standardized sections (overview, how it works, tools used, outcome). New cases are appended to the library data file, and the site is deployed via Vercel.
Tools Used
Outcome
Launched with 18 seed use cases in February 2026. The library has grown to 24 use cases with zero manual curation. Attracts 300+ monthly visits from other organizations researching AI adoption. The auto-extraction workflow ensures the library stays current without requiring dedicated maintenance time.