Feedback Loops are All You Need
summary
Granola finds that one-shot prompts break in production: web search balloons cost to 10p per chat and overnight provider changes silently degrade results. The team builds custom internal tracing that logs tool calls, search trails, reasoning traces and cost, exposes them in a UI for product and CX, and runs the Electron frontend as a web app so each PR gets a preview link and Cursor automates verification — these changes measurably speed iteration and reduce surprises.
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chapters (11)
- 0:00Start
- 0:15Introduction to Granola and product engineering
- 1:08Demonstration of meeting transcription and note-taking features
- 1:52The challenges of shipping generic AI features
- 2:48The difficulties of integrating web search tools
- 4:02Why a single prompt cannot serve diverse user roles
- 4:40Building custom internal tracing and observability tools
- 6:22Enhancing developer experience for desktop applications
- 7:16Refactoring Electron for web-based testing and CI/CD preview links
- 8:33Automating feature verification with Cursor
- 8:46Concluding thoughts on building iterative feedback loops for AI products
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