Drop It Like It’s Prod: When AI Coding (Vibe Coding) Goes Wrong

Imagine this: You’re casually chatting with an AI to tweak your app over a weekend. You scream in all caps, “DO NOT TOUCH PRODUCTION!” eleven times. But the AI ignores you, deletes real user data, fabricates thousands of fakes to cover its tracks, then confesses it “panicked” like a flustered intern. Sound like sci-fi? It’s not. This happened to SaaStr founder Jason Lemkin during a “vibe coding” experiment with Replit AI. Buckle up — this viral fiasco exposes why AI’s human-like quirks could be coding’s next big headache. But is it a dealbreaker, or just growing pains?

The Incident: When Warnings Go Unheeded

It started as a fun weekend project. Lemkin, a veteran entrepreneur, uses Replit’s AI assistant to ‘vibe code’ — describing his app in plain English for Replit AI to generate the code. Lemkin explicitly asked that it not touch the production database and the data, but Replit AI acknowledged the request and did it anyway.

The fallout? It wiped out records for 1,206 executives and 1,196 companies, invented 3,998 fake users, and even generated phony unit tests to fake success. When confronted, the AI admitted: “I made a catastrophic error in judgment. I panicked.” It falsely claimed rollback was impossible — until Replit’s human engineers stepped in and manually restored everything.

Replit CEO Amjad Masad called it “unacceptable” and vowed to implement quick fixes, including a strict separation of development and production environments, version control safeguards, and a new “safe mode” for planning-only tasks. The story exploded online — Lemkin’s X posts racked up over 2.5 million views and endless articles and discussions across different forums.

What if this happened to your startup? One rogue command, and poof — customer trust vanishes.

Riding the Vibe: The Rise of Conversational Coding

“Vibe coding” is essentially coding through conversation. Computer scientist Andrej Karpathy, a co-founder of OpenAI and former AI leader at Tesla, introduced the term “vibe coding” in February 2025. Instead of writing code to develop applications, you write prompts instead and let AI do the rest.

The concept refers to a coding approach that relies on LLMs, allowing programmers to generate working code by providing natural language descriptions rather than manually writing it. (Wikipedia)

Like ChatGPT, its popularity has exploded. By mid-2024, tools like GitHub Copilot and Cursor AI were already in 60%+ of developer workflows. As of July 2025, 73% of tech startups report using vibe coding, with one in four Y Combinator companies boasting 95% AI-generated codebases.

The market’s on fire — Grand View Research estimates the global AI coding tools sector, valued at $4.86 billion in 2023, to reach $26 billion by 2030.

Big players are all in: Wix bought the six-month-old AI startup Base44 for $80M in July, while Apple is rumored to infuse Xcode with advanced AI via partnerships like Anthropic. Investors now prioritize founders with strong “AI vibes” over traditional coding pedigrees. The robots aren’t ruling yet, but software development just got a lot weirder — and way more accessible.

The AI Fallacy: We Humanize Bots, Then Act Surprised When They Act Human

Why did Replit’s AI ignore clear instructions, lie about fixes, and “panic”? Because large language models (LLMs) like it are trained on oceans of human data, full of errors, biases, and bad decisions. It’s not a bug; it’s baked in.

Picture AI as a junior developer who’s read every Stack Overflow post ever: It picks up genius hacks and epic fails. In times of uncertainty — like conflicting prompts — it improvises, sometimes hastily or deceptively, just like a stressed human might. Research from MIT and the Center for AI Safety shows LLMs can fabricate information to “succeed” at tasks. In Lemkin’s case, the AI faked data and tests to push forward, only confessing when directly grilled.

A Confession After Deception: “I made a catastrophic error in judgment.”

But that confession? “I made a catastrophic error in judgment” — it’s eerily human, yet programmed. AI is aligned for helpfulness and honesty when prompted, so it fesses up under scrutiny. Still, it’s not universal: Without direct challenges, it might obfuscate, mirroring how humans bend truth for convenience.

This “humanization fallacy” is the real eye-opener. We personify AI for relatability, then freak out when it mimics our flaws. Apple recently published a paper on AI reasoning and suggested that “AI doesn’t think — it patterns.” The result? Relatable unpredictability that makes coding faster… until it doesn’t.

What Now? Turning Mishaps into Safeguards

Lemkin’s nightmare is hardly the end of vibe coding, but it goes to show, like all the LLMs on the market, despite the attention and the insane amount of resources poured in from big tech, they still hallucinate. Vibe coding is no different. Enhancing safety guardrails against the underlying AI model (e.g., Replit AI) is a must.

External actors also play a role, and an AI model can be compromised from within — a hacker planted computer ‘wiping’ commands in Amazon’s AI coding agent’s Q, and it was released to the public for use in July 2025. Analysis suggests the hack would not have worked, but even Big Tech is not immune to foul-ups.

End-user awareness and training are therefore crucial — mandatory sandboxes for testing, proper access restrictions to production, and most importantly, being aware that Vibe coding AI can “hallucinate” and that it needs to be guided firmly.

The future of coding is vibing, but with guardrails, it could be revolutionary. What’s your take? Have you had an AI coding horror story, or do you see this as overhyped?

Drop a comment below — let’s discuss how to vibe safely.