The Vibe Coding Hangover: How to Stop AI From Ruining Your Codebase

Source: Dev.to

The Problem

You know the feeling.

You spend three hours on a Saturday night with Claude or Cursor. You’re in the flow. You prompt, it generates, you paste. The app works. You show your non‑technical friends who think you’re a genius, and you feel like you’ve unlocked a superpower. Life is good.

Then the hangover hits.

You notice a bug, or you want to add a “quick” feature. Or worse, you pushed to production and users start noticing issues. Suddenly you’re staring at thousands of lines of code you didn’t really write and, let’s be honest, don’t really understand. You beg the AI to “fix it,” but since it has no memory of why it made those decisions three days ago, it just adds more spaghetti on top of the sauce. You go around in circles, stuck in an endless AI loop.

This is the uncomfortable truth of “Vibe Coding.” It’s magical for prototypes and hackathons and genuinely incredible for getting from zero to something usable. But for apps you actually need to operate, debug, and extend over months, vibe coding turns into a massive maintenance headache. You can’t vibe‑prompt your way out of technical debt; at some point an actual human has to own the code.

The Solution: Give the AI a Handbook

The problem isn’t the AI; it’s the lack of constraints and memory.

When we code manually, we (hopefully) have internal standards: “Don’t repeat yourself,” “Clean up dead imports,” “Document the why.” When we use AI, we tend to drop those standards in favor of speed.

To fix this, stop treating the AI like a magic wand and start treating it like a very fast, very forgetful junior developer. Give it a strictly enforced employee handbook.

Whether you use Claude (see claude.md), Cursor (see .cursorrules), or a CLI tool (see AGENTS.md), you need a system prompt that enforces hygiene and, most importantly, external memory.

The “Senior Engineer” Prompt

I’ve been iterating on a specific instruction set that solves two massive problems:

• Code bloat – forces the AI to refactor as it goes.
• Amnesia – forces the AI to keep a journal (DEVLOG.md) of what it did, so the next context window knows what happened.

Copy‑paste the following into your AI instruction file:

# Project Guidelines & Philosophy

## 1. Code Quality: The Boy Scout Rule
Every session should improve the codebase, not just add to it. Actively refactor code you encounter, even outside your immediate task scope.

- **Don't Repeat Yourself (Rule of Three):** Consolidate duplicate patterns into reusable functions only after the 3rd occurrence. Do not abstract prematurely.
- **Hygiene:** Delete dead code immediately (unused imports, functions, variables, commented code). If it's not running, it goes.
- **Leverage:** Use battle‑tested packages over custom implementations. Do not reinvent the wheel unless the wheel is broken.
- **Readable:** Code must be self‑documenting. Comments should explain *why*, not *what*.
- **Safety:** If a refactor carries high risk of breaking functionality, flag it for user review rather than applying it silently.

## 2. Persistent Context & Memory
Since our context resets between sessions, we use files to track our brain.

**The Dev Log (`DEVLOG.md`)**  
At the completion of a task, you must check if `DEVLOG.md` exists. If so, propose an append summarizing:
1. **The Change:** High‑level summary of files touched.  
2. **The Reasoning:** Why we made specific structural decisions.  
3. **The Tech Debt:** Any corners we cut that need to be fixed later.

**Goal:** If a new developer (or a new AI session) joins tomorrow, they should be able to read `DEVLOG.md` and understand the state of the project immediately.

**Operational Rule**  
- After every interaction that includes a code change, you must append an entry to `DEVLOG.md` before finishing. Do not just suggest it. If you truly cannot write to the file (permissions/conflicts), provide the exact snippet the next person should paste. This is mandatory and should be treated as a checklist item for every task.

Why This Works

1. The “Rule of Three” Guardrail

AI models love to abstract. By enforcing the Rule of Three (don’t DRY until it happens three times), you stop the AI from over‑engineering simple tasks and creating unnecessary helper functions.

2. The DEVLOG.md Anchor

AI models have short‑term memory loss. By forcing the AI to write a summary of its decisions into a markdown file at the end of every session, you create an external hard drive for the project’s brain. When a new session starts, the AI can read DEVLOG.md and immediately know, for example:

• “We switched to date-fns last Tuesday.”
• “We left that API endpoint half‑finished.”

Summary

Vibe coding is fun, but engineering is about longevity. If you don’t constrain the model, it will prioritize “making it work right now” over “making it maintainable for later.” Use the prompt above to force the AI to respect the codebase as much as you do.

Do you have a specific system prompt you use to keep your AI in check? Let me know in the comments.