AI

[One Million AI Engineer Special] How Stanford Teaches AI-Native Engineering — Mihail Eric, Monaco

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Based on the episode description, not a full transcript. Source evidence retrieved 08/11/2026, 23:12:24 UTC.

Briefings

This podcast episode features Mihail Eric, an AI engineer at Stanford, discussing his course CS146S where students learn to maintain open-source repositories. The core finding is that the course integrates real-world maintainers into the curriculum, requiring students to propose changes to unfamiliar codebases. The episode notes indicate the course was revisited in a second run, suggesting an iterative approach to teaching AI-native engineering skills.

Key points

• Stanford's CS146S course integrates open-source maintainers into the curriculum, requiring students to propose changes to unfamiliar codebases.
• The course was revisited in a second run, indicating an iterative approach to teaching AI-native engineering skills.

Context

Mihail Eric, an AI engineer at Stanford, leads a course where students learn to maintain open-source repositories. The course integrates real-world maintainers into the curriculum, requiring students to propose changes to unfamiliar codebases. This approach aims to prepare students for modern AI-native engineering challenges.

Limitations

Evidence is limited to a single podcast episode from November 2026. Specific dates for the second course run are not provided. The course's long-term impact on student outcomes remains unmeasured.

Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 08/11/2026, 23:13:40 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.

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