The Reasoning Show

The Reasoning Show AI moves fast. Thinking clearly matters more.

The Reasoning Show cuts through the hype to explore how the smartest people in enterprise AI actually make decisions — the strategy, the tradeoffs, and the hard lessons no press release mentions.

Every week, hosts Aaron Delp and Brian Gracely sit down with the founders building the tools, investors funding the shift, and operators running AI in the real world. Not hype. Not panic. Just clear-headed conversations with people who have to make actual decisions.

Because the AI revolution isn't just happening. It's being reasoned through.

New shows every Wednesday and Sunday.

Topics: Enterprise AI strategy · LLMs in production · AI leadership · Agentic AI · Digital Sovereignty · Machine Learning · AI startups · Cloud Computing

All Episodes

The Reasoning Show

How AI is Transforming Software Development

April 08, 2026 • Massive Studios

0:00 | 33:50

SUMMARY: Discover how AI is transforming software development and what it means for engineering leaders.

GUEST: Jeff Keyes, Field CTO at AllStacks

SHOW: 1017

SHOW TRANSCRIPT: The Reasoning Show #1017 Transcript

SHOW VIDEO: https://youtu.be/cXPu8iWeB0k

SHOW SPONSORS:

ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!
Nasuni - Activate your data for AI and request a demo

SHOW 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?