Pioneer or Perish: How and When to Evolve Your Engineering Org Toward the AI Development Life Cycle

In this episode of "How Many CTOs Does It Take?" podcast, hosts Scott Porad and Brad Hefta-Gaub discuss a high-performing engineering team that has effectively cleared its product backlog while using AI heavily, including a senior engineer who surprised Brad by running agents overnight to automatically perform fast, high-quality GitHub PR code reviews via a webhook-driven harness. The engineer built an opinionated, RAG-backed "world-class code review" skill set that pulls new PRs from selected repos, reviews them with defined criteria, and posts comments, highlighting the need to articulate engineering judgment rather than relying on gut feel. They explore how models and agent frameworks are becoming commoditized, making the key differentiator the ability to assemble components and codify professional, reusable skills. The conversation turns to how teams should integrate AI into the SDLC, balancing experimentation with a shared, periodically updated "long-term support" approach and quality gates, plus examples like agents generating test coverage and proposing fixes for failing tests.

00:00 Cold OPen 00:25 Podcast Intro And Banter 01:09 Mind Blown By AI Team 03:25 Overnight Agent Code Reviews 06:02 Make Your Opinions Clear 09:05 Models Vs Frameworks 12:32 Standardizing Team AI Use 14:43 LTS For Agent Workflows 15:51 Automate Repeated Tasks 21:52 SDLC First AI Second 25:04 Quality Gates And Automation 28:27 Agents For Tests And Bugs 30:55 Future Of Engineering Taste 32:40 Wrap Up And Credits

Resources:

• How Many CTOs Pod: https://howmanyctospod.com
• Scott Porad: https://www.linkedin.com/in/scottporad/
• Brad Hefta-Gaub: https://www.linkedin.com/in/bradheftagaub/

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