Vibe coding is the idea of writing software in a flow state, guided by instinct and experimentation rather than rigid plans. The term originated from a post by Andrej Karpathy in X:

Some seasoned developers dismiss vibe coding as sloppy or unserious, but it’s proving to be incredibly powerful. The reality is that people like me and countless others are shipping personalized apps, rapid prototypes, and even production-grade systems through this approach. Builders like David Baird (https://www.mysalt.ai/) and Austin Starks are proof of its legitimacy… Austin said in one of his articles, “I vibe-coded over 160,000 lines of code. It IS real.” (article linked below). Whether you love or hate the term, vibe coding is making serious waves in how software gets created today.

10 Top Tips for Getting Started on the Right Foot

1. Know Your Datasources

When prototyping, it’s easy to let tools or AI assistants spin up new databases on a whim, possibly without you realizing it.

Suddenly you’ve got SQLite handling auth caching while Postgres sits idle, and no one knows which is the “real” source. Data silos and sync problems appear overnight. The cure is simple: commit to one datasource unless you’ve deliberately planned for more. That’s how you avoid spaghetti pipelines before they start.

2. Manage Dependencies Early

The vibe encourages grabbing packages left and right just to keep the momentum flowing. That works fine until you revisit your project two weeks later and half of it doesn’t run because versions drifted. Pin dependencies once something is working. This small discipline will save you from hours of debugging dependency hell down the road.

3. Avoid Hidden State

Avoid Hidden State. Hidden state is like black ice: invisible until you’re already sliding. Caches, local DBs, and temp files feel harmless in the moment, but they turn into landmines when a teammate tries to run your code. Always externalize or document your state. If it’s needed, it should be obvious. Don’t make future-you reverse-engineer your own prototype.

4. Check for Duplication

AI can be brilliant at generating solutions, but it doesn’t always recognize context. It may try to solve the same problem twice in slightly different ways, or generate fragmented code that overlaps with what already exists. This leads to multiple competing implementations and confusion down the line. Always review generated code with a critical eye and unify duplicated logic. Consistency matters more than quantity when you’re building toward something real.

5. Guardrails for Security

Shortcuts are tempting when vibing. Hardcoding secrets or skipping validation feels fine because it “just works.” But those shortcuts linger much longer than you expect. Secrets end up in repos, and insecure code slips into production. Treat credentials like toxic waste. Don’t hardcode them. Ever. Not even in throwaway demos.

6. Logging & Observability

Debug prints work until they don’t. When the system grows, you’ll wish you had structured logs. Add lightweight logging from the start. Errors, warnings, and key actions should always leave a trail. This practice pays off when you hit unexpected behavior, especially in collaborative projects.

Practical Examples

• Python Instead of print("User created"), use:

  import logging
  
  logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
  
  logging.info("User created successfully")
  logging.warning("API response time exceeded threshold")
  logging.error("Database connection failed", exc_info=True)
  

  ✅ Gives you timestamps, log levels, and error traces automatically.

• Node.js Replace console.log() spam with pino (lightweight and fast):

  const pino = require('pino');
  const logger = pino();
  
  logger.info("User created successfully");
  logger.warn("API response time exceeded threshold");
  logger.error({ err }, "Database connection failed");
  

  ✅ Produces structured JSON logs that are easy to parse and ship to monitoring tools.

Small Project Hack Even if you don’t wire up full observability, just:

• Use log levels (info, warn, error) instead of plain prints.

• Include context (which user? which request?).

• Redirect logs to a file if the app runs longer than a demo.

Scaling Up When vibe code evolves, plug into tools like:

• Log aggregation: ELK stack (Elasticsearch + Logstash + Kibana), Graylog, or Loki.

• Hosted options: Datadog, Logtail, Papertrail. These let you search and visualize your logs when the prototype becomes a real app.

7. Performance Landmines

Vibe code runs fine on small inputs but dies on scale. The classic mistakes: loading giant files into memory, running unindexed queries, or blocking async calls. These aren’t theoretical… they will bite you. Before walking away from a session, quickly scan the code for performance time bombs. You can and should also have AI scan your code for these issues as well. It doesn’t take long, but it will save you later.

You are a coding assistant reviewing code for "vibe coding" pitfalls. 
Scan the provided code for the following issues and explain any findings clearly:

1. Performance landmines: 
   - Loading entire files or datasets into memory instead of streaming/iterating
   - Unindexed or inefficient database queries
   - Blocking async calls or mixing sync/async improperly
   - Excessive nested loops or unnecessary complexity

2. Hidden state and duplication: 
   - Any caching, temp files, or local DBs not documented
   - Duplicate or fragmented solutions to the same problem (often from AI-generated snippets)

3. Security guardrails: 
   - Hardcoded secrets, API keys, tokens, or credentials
   - Missing validation or error handling that could be exploited

4. Dependency chaos: 
   - Unpinned dependencies or unused imports
   - Conflicting versions that may cause runtime errors

For each issue, suggest a specific and practical fix. 
Format your answer as a checklist with examples if possible.

8. Respect the Cleanup Pass

No prototype survives untouched. The difference between a demo and usable code is the cleanup pass. Rename variables, restructure folders, remove dead code. It feels tedious compared to the high of creation, but it’s necessary. Without cleanup, prototypes rot fast. With cleanup, they can evolve into production systems.

Bonus: Keep a production_changes.json (or similar log) that records what was auto-changed. That way, you track technical debt reduction over time.

EXAMPLE CLEANUP PROMPT (Chain-of-Thought with Human in the Loop)

You are a coding assistant tasked with helping clean up code.
 
DO NOT change functionality. Focus on readability, structure, and maintainability.

Follow an iterative approach to reduce the risk of breaking working code.

Step 1: Identify
- List all unused imports, variables, and routes. 
- Highlight any files or components that look redundant or fragmented. 
- Provide this list first, without making changes.

Step 2: Verify
- Ask me to confirm which items should be removed or refactored. 
- Double-check your suggestions by scanning the code again to ensure no active references are missed. 
- If uncertain, mark items as "needs human review" instead of deleting.

Step 3: Cleanup
- Remove the confirmed unused code safely.
- Rename variables, functions, and classes for clarity and consistency.
- Add minimal inline comments where intent may not be obvious.
- Ensure formatting follows common style guides (PEP8, ESLint/Prettier, etc.).

Step 4: Log
- Create or update a `production_changes.json` file that records what was removed, renamed, or reorganized.
- Summarize all cleanup actions clearly so I can track technical debt reduction over time.

Rules:
- Think longer
- Run this cleanup process in multiple passes if needed (imports first, then routes, then dead code).
- Do not add new features.
- Preserve all existing behavior.
- Explain your decisions before the end of each step and before making any changes

EXAMPLE RESPONSE (Step 1 shown)

9. Write Down the Decisions

The flow state erases memory. You won’t remember why you picked Option A over Option B. Future-you will curse past-you for leaving no breadcrumbs. Keep a NOTES.md or a simple log of decisions. Even short bullets help. Decision documentation is a multiplier, it saves time for you and anyone else touching the project.

10. Extreme Version Control

We’re in an era of extreme code generation. AI can spit out entire files, frameworks, and systems in seconds. Without version control discipline, your history will become a blur of changes you can’t track. Practice extreme version control. Commit frequently. Branch with intention. Document merges. When the code is flying fast, version control is your anchor.

BONUS TIP

Rules are only useful if they’re visible. Create a RULES.md in your project (or team repo) and update it whenever you add or refine rules. This isn’t about dogma; it’s about preserving clarity when the vibe takes over. Treat it like your compass. When the project feels chaotic, read the rules. When you learn a new lesson, update the rules. This practice turns ephemeral flow into long-term wisdom.

✅ Suggested Structure

At minimum:

• README.md (entry point)

• AGENTS.md (newer standard, like a README, but for robots 🤖)

• RULES.md (true north vibe coding rules)

• ARCHITECTURE.md (system design)

• NOTES.md

Optional as repo grows:

• DECISIONS.md (or ADR directory)

• OBSERVABILITY.md

Tools like replit and Claude code are already doing this automatically. Claude writes to claude.md and replit to replit.md. Reviewing these files can help you understand the guidance AI tools are using and committing to drive itself forward. We’re even seeing an emergence of AGENTS.md , which I think will become more common as we move forward.

Closing Thoughts

Vibe coding is joy. It’s how we capture ideas at their most raw and creative. This guide is meant to help you ensure it doesn’t collapse under its own weight.

Flow hard, but stay aligned. That’s the way to keep building without burning out!

What’s your take? Let me know [email protected]

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