The Productivity Paradox: Why More AI Code is Slowing Down Shiptimes

SUMMARY:  Discover how AI is transforming software development and what it means for engineering leaders. GUEST: Jeff Keyes, Field CTO at AllStacks SHOW: 1017SHOW TRANSCRIPT: The Reasoning Show #1017 TranscriptSHOW VIDEO: https://youtu.be/cXPu8iWeB0kSHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:Topic 1 - Welcome to the show. Tell us a little bit about your background, and what you focus on these days at AllStacks. Topic 2 - You’ve been talking to a lot of engineering leaders using AI coding tools—what’s the most surprising gap you’re seeing between increased code generation and actual delivery outcomes?Topic 3 - Why does increasing developer output with AI often lead to more debugging, duplication, or cleanup instead of faster delivery?Topic 4 - You’ve described an ‘invisible rework loop’—can you walk us through what that looks like inside a modern engineering team?Topic 5 - As code generation gets easier, where does the real bottleneck shift in the software delivery lifecycle?Topic 6 - How do unclear product or engineering specifications get amplified in an AI-assisted development environment?Topic 7 - If traditional metrics like lines of code or velocity are becoming misleading, what should engineering leaders actually measure to know if AI is improving delivery?Topic 8 - What does a ‘healthy’ AI-assisted development workflow look like 12–18 months from now?FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @EntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow