What a year of hands-on AI coding teaches you about good ...

What this episode covers

In this episode, Lada Kesseler shares what she’s learned from a year of hands-on experience building with AI coding tools — including the three fundamental challenges that define how these tools work, and why understanding limitations is what makes you better at using them.Lada explains why “focus” is the critical concept most developers miss, how a dedicated committer agent will catch issues that a general-purpose copilot never does, and why software craftsmanship matters more now than ever. She also gets into why using AI to critique itself produces dramatically better results, and how AI works as an amplifier that speeds up both good and bad engineering practices.Find the transcript at: https://www.swarmia.com/podcast/lada-kesseler-logic2020(0:00) Introduction(2:46) The five fundamental gaps in AI development(7:15) “You’re absolutely right!”(8:00) The anti-pattern of the distracted agent(11:09) Do agile best practices still matter in the age of AI?(14:48) Why software craftsmanship is more important than ever(15:46) Managing complexity: Can AI do it, or do we still need humans?(18:19) The difference between vibe coding and craft(20:24) How AI is an amplifier — for better or worse(21:23) Good practices that are suddenly essential(23:02) The superpower of refactoring(25:36) Documentation: harder to maintain but more important than ever(26:58) When developers don’t write code anymore(32:49) AI costs and the coming reckoning(33:54) When AI is not the right choice(36:06) Three things senior leaders need to understand about AI(39:46) Will we still be talking about this in a year’s time?Watch Lada’s talk Augmented Coding: Mapping the Uncharted Territory See the interactive map on Lada’s website Follow Lada on LinkedIn Follow Rebecca on LinkedIn

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How long is this episode of Engineering Unblocked?

This episode is 41 minutes long.

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This episode was published on January 19, 2026.

What is this episode about?

In this episode, Lada Kesseler shares what she’s learned from a year of hands-on experience building with AI coding tools — including the three fundamental challenges that define how these tools work, and why understanding limitations is what makes...

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