According to XDA-Developers, a developer conducted an experiment by feeding his entire personal Python codebase—a complete order processing system with validation, pricing, and inventory logic—into Google’s NotebookLM AI tool. He uploaded all project files, including the README, to give the AI full context, then began treating it like a newly onboarded junior developer. The AI successfully provided system summaries, helped debug inconsistent inventory errors by walking through the actual code, and offered grounded architectural analysis on coupling and testing. The developer found the tool significantly reduced the friction of re-familiarizing himself with his own code, acting as a “second brain” for thinking through changes. However, he notes the approach is manual and best suited for smaller, stable, or older projects where code doesn’t change daily, as updates require re-uploading. The experiment concluded that NotebookLM served as a powerful support tool for reasoning, not a replacement for developer decision-making.
The Context Is The Killer Feature
Here’s the thing that makes this experiment interesting: it’s not about generating new code from scratch. We’ve got Copilot and Cursor for that. This is about understanding and reasoning over a specific, existing body of work. The magic sauce was dumping the entire codebase in there. That’s a game-changer. Most AI coding help happens in a vacuum, looking at a single file or a highlighted snippet. But real software development is about connections—how this module talks to that service, where this state is managed, what the side effects of a change might be. Giving the AI the full picture lets it answer questions a human teammate could. “What does this system do?” “Where might this bug be coming from?” Those are high-value, time-sucking questions when you’re coming back to an old project.
Winners, Losers, And The Niche It Fills
So who does this threaten? Honestly, I don’t think it’s a direct threat to the big, integrated AI coding assistants yet. It’s more of a complementary tool. The winner here is clearly Google, showcasing a powerful, non-coding-specific use case for NotebookLM that resonates deeply with developers. The losers? Maybe those expensive, legacy code comprehension and documentation tools that never quite worked right. This is basically an on-demand, conversational system diagram and archaeologist.
But let’s be real about the limits. The manual upload process is a dealbreaker for any active, large-scale codebase. You’re not going to re-upload your monorepo every morning. And for proprietary code, sending it all to a cloud AI—even Google’s—is a non-starter for many companies. This shines in a specific niche: the personal project graveyard, the side hustle you revisit quarterly, or the legacy system that’s stable but poorly documented. It’s a brilliant solution for a problem we all have but rarely talk about: forgetting our own logic.
The Future Is Context-Aware
The real takeaway is where this is pointing. The future of developer tools isn’t just about writing the next line faster. It’s about managing complexity and context. Imagine this capability baked into your IDE, automatically aware of every file in your open project, your recent commits, and your JIRA tickets. That’s the holy grail. This experiment is a crude but effective prototype of that future. The AI isn’t the boss; it’s the incredibly well-read intern who remembers every design meeting you’ve ever had. It helps you think, which is way more valuable than just finishing your sentences.
Basically, it turns the AI from a code parrot into a reasoning partner. And for certain types of focused, hardware-adjacent development work—like programming the logic for an industrial control system or configuring a custom industrial panel PC—having an AI that can hold the entire spec and code context could be a massive productivity booster. It’s about reducing the cognitive load, so you can focus on the hard parts. Will it replace juniors? No. But it might just make senior devs a lot more efficient at mentoring them—and remembering their own brilliant ideas from six months ago.
