The Stack Overflow Podcast AI is a crystal ball into your codebase
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Dec 9, 2025 Kayvon Beykpour, the CEO of Macroscope and a tech entrepreneur known for co-founding Periscope, shares insights on the transformative role of AI in code review. He discusses the challenges of visibility in large codebases and how Macroscope's AI tools can streamline project summaries and bug detection. Kayvon elaborates on using abstract syntax trees for precise context and the importance of human oversight. He envisions a future where AI enhances engineers' productivity, allowing them to focus on more complex problems.
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Visibility Problem At Large Engineering Teams
- Kayvon Beykpour recounts leading product and engineering at Twitter and struggling to know what 1,500 engineers were working on.
- That pain motivated building Macroscope to surface ground-truth from the codebase automatically.
Start Small, Aggregate Up
- Macroscope started by summarizing every commit, then aggregated those into project-level summaries for different stakeholders.
- Building up from atomic commit summaries produces useful higher-level product updates automatically.
AST Context Improves LLM Accuracy
- Supplying an LLM with AST-derived references and usages gives far richer, more accurate summaries than sending just a diff.
- That context dramatically improves signal quality for summaries and reviews.