In this special crossover episode, Luca brings together his two podcasting worlds: the Agile Embedded Podcast with Jeff Gable and the Embedded AI Podcast with Ryan Torvik. What starts as Jeff admitting he's still a "noob" with LLMs turns into a practical deep-dive on how to actually use AI tools without coding yourself off a cliff.

The three explore the real challenges of working with LLMs: managing context windows that behave more like human memory than computer memory, the critical importance of test-driven development (even more so with AI), and why you absolutely cannot let go of the reins. Ryan and Luca share hard-won lessons about prompt engineering, the value of small iterations, and why your static analysis tools aren't going anywhere. They also tackle team-level questions: how code reviews change (or don't), why prototyping becomes a superpower, and what happens to junior engineers learning their craft in an AI-assisted world.

This isn't hype about AI replacing developers - it's three engineers figuring out how to use a powerful but unpredictable tool to write better code faster, while keeping their engineering judgment firmly in the driver's seat.

Key Topics:

• [02:30] Three ways to interact with LLMs: web interfaces, CLIs, and IDE plugins - and why the right interface matters
• [08:45] The art of prompting: being specific without writing pages of instructions, and learning from your mistakes
• [15:20] Context management: why LLMs forget like humans do, and how to keep them focused on what matters
• [22:10] Test-driven development with AI: why tests matter even more when you're not writing the code yourself
• [28:45] Avoiding 'vibe coding off a cliff': small iterations, frequent commits, and knowing when to start fresh
• [35:30] Code reviews and team dynamics: what changes and what stays the same when AI enters the workflow
• [42:15] Prototyping as a superpower: getting from zero to one in minutes instead of weeks
• [46:00] Junior engineers and learning: why you still need to bash your head against problems to gain experience

Notable Quotes:

"All of us are new to this experience. There's not somebody that went to school back in the 80s and like, I've been doing this for 40 years. Like nobody has that level of experience. So we're all just running around, bumping into things and seeing what works for us." — Ryan

"An LLM is just a token generator. You stick an input in, and it returns an output, and it has no way of judging whether this is correct or valid or useful. It's just whatever it generated. So it's up to you to give it input data that will very likely result in useful output data." — Luca

"The LLM is like the happiest developer that I've ever worked with. Just so excited and happy to do more work than you could ever possibly imagine. Like, oh, my gosh." — Ryan

"Don't ever let go of the reins. They will just sort of slowly slip out of your hands and all of a sudden you find yourself sitting there like a fool with nothing in your hands." — Luca

"I can use LLMs to jumpstart me or bootstrap me from zero to one. And once there's something on the screen that kind of works, I can usually then apply my general programming skill, my general engineering taste to improve it." — Jeff

Resources Mentioned:

• Aider - Command-line AI coding assistant mentioned by Luca as his preferred tool for interacting with LLMs
• Claude Code (Anthropic) - AI coding tool discussed for its ability to search codebases and manage context
• VS Code - IDE with AI integrations that Ryan mentions using despite being a former command-line purist
• RooCode - Tool Ryan used that had a prompt enhancement feature, though he no longer uses it