What if the cost of writing code dropped to zero — but the cost of understanding it skyrocketed?

In this episode, Hugo sits down with Joe Reis to unpack how AI tooling is reshaping the software development lifecycle — from experimentation and prototyping to deployment, maintainability, and everything in between.

Joe is the co-author of Fundamentals of Data Engineering and a longtime voice on the systems side of modern software. He’s also one of the sharpest critics of “vibe coding” — the emerging pattern of writing software by feel, with heavy reliance on LLMs and little regard for structure or quality.

We dive into:
• Why “vibe coding” is more than a meme — and what it says about how we build today
• How AI tools expand the surface area of software creation — for better and worse
• What happens to technical debt, testing, and security when generation outpaces understanding
• The changing definition of “production” in a world of ephemeral, internal, or just-good-enough tools
• How AI is flattening the learning curve — and threatening the talent pipeline
• Joe’s view on what real craftsmanship means in an age of disposable code

This conversation isn’t about doom, and it’s not about hype. It’s about mapping the real, messy terrain of what it means to build software today — and how to do it with care.

LINKS

🎓 Want to go deeper?
Check out my course: Building LLM Applications for Data Scientists and Software Engineers.
Learn how to design, test, and deploy production-grade LLM systems — with observability, feedback loops, and structure built in.
This isn’t about vibes or fragile agents. It’s about making LLMs reliable, testable, and actually useful.

Includes over $800 in compute credits and guest lectures from experts at DeepMind, Moderna, and more.
Cohort starts July 8 — Use this link for a 10% discount

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