Reinventing Agile - When Machine Learning Meets Software Engineering
summary
Claims that ML augmented agile makes code and data converge and that code generation (ChatGPT, co‑pilot, Mistral) can auto‑implement tests and refactor at scale. Uses NLP to classify tens of thousands of customer feedback items, route‑planning models that add 60s per first delivery and ~23s at night, and an automated fulfillment line whose first iteration launched two years ago with a second rollout imminent. Promises an agile x data flywheel and shopfront personalization plus order picking robots that demonstrably reduce manual work.
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chapters (13)
- 0:00Introduction
- 1:58Online grocery needs
- 3:50Picnic’s product evolution
- 5:15NLP for customer feedback
- 6:39Personalized product displays
- 7:22ML in delivery planning
- 9:49Real-time delivery tracking
- 10:29AI impact on engineering
- 13:37Code generation future
- 15:01AI security challenges
- 17:54Making everyone in the organization a developer
- 19:42Robotics in fulfillment
- 21:16Future-proof tech principles
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