How Vibe Coding Affects Technical Debt

I talk to over 40 engineering leaders a month. And here’s what we’re finding: AI coding tools are exhilarating—but unsustainable without structure. Everyone loves the speed. You can spin up a prototype in a day, generate full functions in seconds, and skip the boilerplate. It feels like you’re coding at 10x. But then comes the hard part: What happens when that AI-generated code hits production? Who’s responsible when it introduces a security flaw? Can anyone actually maintain it three months from now? This is the reality of vibe coding—writing code in the moment, fast and loose, trusting that AI will "just figure it out." And while it works beautifully for MVPs and early explorations, it breaks down hard at scale. The cracks show up quickly: -> Architecture gets messy. AI tools don’t necessarily think across larger code bases —they can generate in isolated chunks if the context just isn't there. -> PRs become noise. Reviewing AI-generated changes takes longer than writing them from scratch. -> Security risks slip through. Hardcoded secrets, poor access control, and logic bugs go unnoticed. -> Teams lose trust. No one wants to deploy code they can’t understand or trace. So what’s the path forward? We don’t slow down AI—we build guardrails around it. -> Code review isn’t optional. AI can assist, but someone—or something—needs to catch what it misses. -> Traceability matters. Every AI suggestion should tie back to version control, so nothing gets lost in the fog. -> Security needs to be first-class. AI-generated code must be checked for vulnerabilities before it ships. -> Maintainability is the long game. AI should help refactor, not just generate more mess. At Optimal AI, we’re solving for this with Optibot—an AI agent that reviews, refactors, and protects your codebase while you move fast. Because vibe coding feels great—until you’re drowning in tech debt. How’s your team making sure AI-generated code doesn’t come back to bite you?

"Vibe Coding !== Low Quality Work: a guide to responsible AI-assisted dev" ✍️ My latest free article: https://lnkd.in/gjMdjMWV The allure of "vibe coding" – using AI to "move faster and break even more things" – is strong. AI-assisted development is undeniably transformative, lowering barriers and boosting productivity. But speed without quality is a dangerous trap. Relying uncritically on AI-generated code can lead to brittle "house of cards" systems, amplify tech debt exponentially, and introduce subtle security flaws. Volume ≠ Quality. A helpful mental model I discuss (excellently illustrated by Forrest Brazeal) is treating AI like a "very eager junior developer." It needs guidance, review, and refinement from experienced hands. You wouldn't let a junior ship unreviewed code, right? So how do we harness AI's power responsibly? I've outlined a field guide with practical rules: ✅ Always review: Treat AI output like a PR from a new hire. ✅ Refactor & test: Inject engineering wisdom – clean up, handle edge cases, test thoroughly. ✅ Maintain standards: Ensure AI code meets your team's style, architecture, and quality bar. ✅ Human-led design: Use AI for implementation grunt work, not fundamental architecture decisions. The goal isn't to reject vibe coding, but to integrate it with discipline. Let's use AI to augment our craft, pairing machine speed with human judgment. #softwareengineering #programming #ai

In Vibecoding, we are going 10-20x the regular speed and that means all the regular coding accidents will happen 10-20x faster. Leverage works both ways. Technical debt clearing and refactoring that was required once a month or a quarter is now required everyday. You should plan to get rid about 50% of the code that you wrote the previous day as you fold those into neat packets with strong test cases. LLMs can ofter overengineer or underengineer, thus keeping consistency becomes a key duty of the engineer. If you bring the old bad habits [such as not writing test cases, not raising frequent PRs to keep things consistent, not refactoring consistently] vibe coding can bring you nasty surprises 10x fast.

Vibe coding—where you prompt the AI and go with what it gives you, and just keep nudging it towards where you want to go—is popular because it’s super intuitive, and honestly it actually works… at least for a while. You can generate a lot of code and get something running quickly. That’s great for a blue-sky prototype, or anything where you’re not 100% sure where you’re going to end up. It also makes for great videos and social media posts. But if you need your project to go somewhere specific, it’s really easy to vibe code yourself into a corner and end up with a ton of technical debt. And that’s exactly what happened to this Reddit user: https://lnkd.in/dwMTtfqi I’ve seen this post going around a lot, and I really feel for the guy—because he was able to use AI tools to write enough code that he ran into a problem you don’t usually hit until you’ve written a lot of code on your own: a whole lot of technical debt. What he’s describing is classic shotgun surgery: every change requires editing a dozen places. Anyone who’s been coding for a while cringes when they hear that, because they’ve all been there. The difference is now you can get there way faster, and you don't need any coding experience to do it. The big danger, I think, is that now someone who was curious and interested in coding is really turned off from it. I hate that! _________________________________________________________________ ⚠️ If you're looking to learn more about coding with AI, check out my upcoming O'Reilly live training course, 𝐂𝐨𝐩𝐢𝐥𝐨𝐭 𝐚𝐧𝐝 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐟𝐨𝐫 𝐉𝐚𝐯𝐚 𝐚𝐧𝐝 𝐂# 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫𝐬. 🔗 https://lnkd.in/eu4a5qKX I only run it a few times a year, and I've gotten a lot of great feedback about it. I'd love to see you there!