Clinical Trials Tracker showcases three-layer agent pipeline
In “This 30-Year-Old Pattern Fixes AI Agents” (https://www.youtube.com/watch?v=e9EBl_PK4bw), Prompt Engineering uses the open-source Clinical Trials Tracker (https://github.com/PromtEngineer/clinical_trial_tracker) to demonstrate a layered agent system spanning ClinicalTrials.gov data access, Google Sheets watchlist memory, and Gmail/Linear delivery automation. It is presented as a full reference implementation for real monitoring workflows, not just a conceptual architecture.
The big win is the pipeline-first framing: this project shows how layered agent design becomes operational when data retrieval, state, and delivery are wired into one repeatable flow.
- –The architecture maps cleanly to MCP tools, making agent responsibilities explicit and easier to debug.
- –Google Sheets as the memory layer is a pragmatic choice for transparent, human-editable watchlists.
- –Digest generation plus Gmail/Linear outputs turns passive tracking into actionable team workflows.
- –The implementation is a strong blueprint for regulated or high-context domains where traceability matters as much as model quality.
DISCOVERED
71d ago
2026-03-17
PUBLISHED
71d ago
2026-03-17
RELEVANCE
AUTHOR
Prompt Engineering