Raising Python quality across a large & diverse AI org
summary
Intuit raises Python quality by teaching engineering skills to ~3,000 AI practitioners and automating standards with a reusable starter repo platform that ships CI/CD, observability, semantic versioning and an internal package index. Practical stack examples: Poetry, Pytest, Black, Flake8, Mypy. Built artifacts include a paved Road with service templates (FastAPI), a gen OS, a recommender library and a document understanding platform; automation like Auto, a software bill of materials and campaign PRs scale updates. Measured impact: 38 workshops, 49 teams and faster production handoffs and higher velocity.
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chapters (10)
- 0:00Introduction and joke
- 0:46Intuit’s AI mission and platform
- 2:53Python in AI at Intuit
- 3:57Open source contributions at Intuit
- 5:23AI practitioner roles and challenges
- 8:34SEEDS workshops for engineering skills
- 12:28Automating best practices with tooling
- 16:47Paved Road for Python services
- 18:52Recap and open source tools
- 19:35Q&A session
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