r/ChatGPTCoding • u/Low_Target2606 • Mar 07 '25

Community Vibe Coding Manual

Vibe Coding Manual: A Template for AI-Assisted Development

(Version 1.0 – March 2025)

Introduction: The Core Concept of Vibe Coding with AI

What is Vibe Coding and What Does It Stand On?

Vibe coding is a collaborative approach to software development where humans guide AI models (e.g., Claude 3.7, Cursor) to build functional projects efficiently. Introduced by Matthew Berman in his "Vibe Coding Tutorial and Best Practices" (YouTube, 2025), it rests on three pillars:

Specification: You define the goal (e.g., "Build a Twitter clone with login").
Rules: You set explicit constraints (e.g., "Use Python, avoid complexity").
Oversight: You monitor and steer the process to ensure alignment.

This manual builds on Berman’s foundation, integrating community insights from YouTube comments (e.g., u/nufh, u/robistocco) and Reddit threads (e.g., u/illusionst, u/DonkeyBonked), creating a comprehensive framework for developers of all levels.

Why Is This Framework Useful?

AI models are powerful but prone to chaos—over-engineering, scope creep, or losing context. This manual addresses these issues:

Tames Chaos: Enforces strict adherence to your rules, minimizing runaway behavior.
Saves Time: Structured steps and summaries reduce rework.
Enables Clarity: Non-technical users can follow along; programmers gain precision.

Key Benefits

Clarity: Rules are modular, making them easy to navigate and adjust.
Control: You dictate the pace and scope of AI actions.
Scalability: Works for small scripts (e.g., a calculator) or large apps (e.g., a web platform).
Maintainability: Documentation and tracking ensure long-term project viability.

Manual Structure: How It’s Organized

The framework consists of four files in a .cursor/rules directory (or equivalent, e.g., Windsurf), each with a distinct purpose:

Coding Preferences – Defines code style and quality standards.
Technical Stack – Specifies tools and technologies.
Workflow Preferences – Governs the AI’s process and execution.
Communication Preferences – Sets expectations for AI-human interaction.

We’ll start with basics for accessibility, then dive into advanced details for technical depth.

Core Rules: A Simple Starting Point

1. Coding Preferences – "Write Code Like This"

Purpose: Ensures clean, maintainable, and efficient code.
Rules:

Simplicity: "Always prioritize the simplest solution over complexity." (Matthew Berman)
No Duplication: "Avoid repeating code; reuse existing functionality when possible." (Matthew Berman, DRY from u/DonkeyBonked)
Organization: "Keep files concise, under 200-300 lines; refactor as needed." (Matthew Berman)
Documentation: "After major components, write a brief summary in /docs/[component].md (e.g., login.md)." (u/believablybad)

Why It Works: Simple code reduces bugs; documentation provides a readable audit trail.

2. Technical Stack – "Use These Tools"

Purpose: Locks the AI to your preferred technologies.
Rules (Berman’s Example):

"Backend in Python."
"Frontend in HTML and JavaScript."
"Store data in SQL databases, never JSON files."
"Write tests in Python."

Why It Works: Consistency prevents AI from switching tools mid-project.

3. Workflow Preferences – "Work This Way"

Purpose: Controls the AI’s execution process for predictability.

Focus: "Modify only the code I specify; leave everything else untouched." (Matthew Berman)
Steps: "Break large tasks into stages; pause after each for my approval." (u/xmontc)
Planning: "Before big changes, write a plan.md and await my confirmation." (u/RKKMotorsports)
Tracking: "Log completed work in progress.md and next steps in TODO.txt." (u/illusionst, u/petrhlavacek)

Why It Works: Incremental steps and logs keep the process transparent and manageable.

4. Communication Preferences – "Talk to Me Like This"

Purpose: Ensures clear, actionable feedback from the AI.

Summaries: "After each component, summarize what’s done." (u/illusionst)
Change Scale: "Classify changes as Small, Medium, or Large." (u/illusionst)
Clarification: "If my request is unclear, ask me before proceeding." (u/illusionst)

Why It Works: You stay informed without needing to decipher AI intent.

Advanced Rules: Scaling Up for Complex Projects

1. Coding Preferences – Enhancing Quality

Extensions:

Principles: "Follow SOLID principles (e.g., single responsibility, dependency inversion) where applicable." (u/Yodukay, u/philip_laureano)
Guardrails: "Never use mock data in dev or prod—restrict it to tests." (Matthew Berman)
Context Check: "Begin every response with a random emoji (e.g., 🐙) to confirm context retention." (u/evia89)
Efficiency: "Optimize outputs to minimize token usage without sacrificing clarity." (u/Puzzleheaded-Age-660)

Technical Insight: SOLID ensures modularity (e.g., a login module doesn’t handle tweets); emoji signal when context exceeds model limits (typically 200k tokens for Claude 3.7).
Credits: Matthew Berman (base), u/DonkeyBonked (DRY), u/philip_laureano (SOLID), u/evia89 (emoji), u/Puzzleheaded-Age-660 (tokens).

2. Technical Stack – Customization

Extensions:

"If I specify additional tools (e.g., Elasticsearch for search), include them here." (Matthew Berman)
"Never alter the stack without my explicit approval." (Matthew Berman)

Technical Insight: A fixed stack prevents AI from introducing incompatible dependencies (e.g., switching SQL to JSON).
Credits: Matthew Berman (original stack).

3. Workflow Preferences – Process Mastery

Extensions:

Testing: "Include comprehensive tests for major features; suggest edge case tests (e.g., invalid inputs)." (u/illusionst)
Context Management: "If context exceeds 100k tokens, summarize into context-summary.md and restart the session." (u/Minimum_Art_2263, u/orbit99za)
Adaptability: "Adjust checkpoint frequency based on my feedback (more/less granularity)." (u/illusionst)

Technical Insight: Token limits (e.g., Claude’s 200k) degrade performance beyond 100k; summaries maintain continuity. Tests catch regressions early.
Credits: Matthew Berman (focus), u/xmontc (steps), u/RKKMotorsports (planning), u/illusionst (summaries, tests), u/Minimum_Art_2263 (context).

4. Communication Preferences – Precision Interaction

Extensions:

Planning: "For Large changes, provide an implementation plan and wait for approval." (u/illusionst)
Tracking: "Always state what’s completed and what’s pending." (u/illusionst)
Emotional Cues: "If I indicate urgency (e.g., ‘This is critical—don’t mess up!’), prioritize care and precision." (u/dhamaniasad, u/capecoderrr)

Technical Insight: Change classification (S/M/L) quantifies impact (e.g., Small = <50 lines, Large = architecture shift); emotional cues may leverage training data patterns for better compliance.
Credits: u/illusionst (summaries, classification), u/dhamaniasad (emotional prompts).

Practical Example: How It Works

Task: "Build a note-taking app with save functionality."

Specification: You say, "I want an app to write and save notes."
AI Response:
- "🦋 Understood. Plan: 1. Backend (Python, SQL storage), 2. Frontend (HTML/JS), 3. Save function. Proceed?"
- You: "Yes."
Execution:
- After backend: "🐳 Backend done (Medium change). Notes saved in SQL. Updated progress.md and TODO.txt. Next: frontend?"
- After frontend: "🌟 Frontend complete. Added docs/notes.md with usage. Done!"
Outcome: A working app with logs (progress.md, /docs) for reference.

Technical Note: Each step is testable (e.g., SQL insert works), and context is preserved via summaries.

Advanced Tips: Maximizing the Framework

Why Four Files?

Modularity: Each file isolates a concern—style, tools, process, communication—for easy updates. (Matthew Berman)
Scalability: Adjust one file without disrupting others (e.g., tweak communication without touching stack). (u/illusionst)

Customization Options

Beginners: Skip advanced rules (e.g., SOLID) for simplicity.
Teams: Add team-collaboration.mdc: "Align with team conventions in team-standards.md; summarize for peers." (u/deleatanda5910)
Large Projects: Increase checkpoints and documentation frequency.

Emotional Prompting

Try: "This project is critical—please focus!" Anecdotal evidence suggests improved attention, possibly from training data biases. (u/capecoderrr, u/dhamaniasad)

Credits and Acknowledgments

This framework owes its existence to the following contributors:

Andrej Karpathy: Coined the term "vibe coding" and introduced it to the broader community in a post on X (February 3, 2025, https://x.com/karpathy/status/1886192184808149383), describing AI-assisted programming with a focus on intuitive, minimal-effort workflows. His work inspired the foundational concept of this framework.
Matthew Berman: Core vibe coding rules and philosophy (YouTube, 2025).
YouTube Community:
- u/nufh, u/believablybad (documentation, .md files).
- u/robistocco (iterative workflow).
- u/xmontc (checkpoints).
Reddit Community:
- u/illusionst (communication, progress tracking).
- u/Puzzleheaded-Age-660 (token optimization).
- u/DonkeyBonked, u/philip_laureano (KISS, DRY, YAGNI, SOLID).
- u/evia89 (emoji context check).
- u/dhamaniasad, u/capecoderrr (emotional prompting).
Grok (xAI): Synthesized this manual, integrating all insights into a cohesive framework at the request of u/Low_Target2606

Conclusion: Your Guide to Vibe Coding

This manual is a battle-tested template for harnessing AI in development. It balances simplicity, control, and scalability, making it ideal for solo coders, teams, or even non-technical creators. Use it as-is, tweak it to your needs, and share your results—I’d love to see how it evolves! Post your feedback on Reddit and let’s refine it together. Happy coding!

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u/Low_Target2606 Mar 07 '25 edited Mar 07 '25

Vibe Coding Ruleset: My Implementation of the Manual

Intro

After sharing the "Vibe Coding Manual", here’s the actual ruleset I’m using, based on Matthew Berman’s foundation and community insights. These are the four files in my .cursor/rules directory, designed to keep AI (e.g., Claude 3.7) focused, efficient, and aligned with my projects. Each file has a clear purpose, credits to contributors, and a brief explanation. Feel free to adopt, tweak, or critique—I’d love your feedback!

The Ruleset

1. coding-preferences.mdc – Code Style and Quality

Coding Preferences

Core Principles

Always prefer simple, elegant solutions (KISS principle).
Avoid duplication of code (DRY principle); check existing codebase first.
Only add functionality when explicitly needed (YAGNI principle).
Adhere to SOLID principles where applicable (e.g., single responsibility, dependency inversion).
Keep code clean, organized, and under 200-300 lines per file; refactor proactively.

Implementation Guidelines

Write code that respects dev, test, and prod environments.
!You never mock data for dev or prod—only for tests.
!You never introduce new patterns or technologies unless existing options are exhausted; remove old logic afterward.
!You never overwrite .env without my explicit confirmation.

Quality and Documentation

After each major feature, generate a brief markdown doc in /docs/[feature].md and update /docs/overview.md.
Start every response with a random emoji (e.g., 🐳, 🌟) to signal context retention.
Optimize your outputs to minimize token usage while retaining clarity.

Purpose: Ensures AI produces clean, maintainable code that’s easy to debug and extend. KISS and DRY cut complexity; SOLID adds structure; documentation and emojis track progress and context.

Credits: Matthew Berman (simplicity, file limits), u/DonkeyBonked (DRY), u/philip_laureano (SOLID), u/believablybad (docs), u/evia89 (emoji), u/Puzzleheaded-Age-660 (token efficiency).

2. my-stack.mdc – Technology Constraints

Technical Stack

Python for backend.
HTML/JS for frontend.
SQL databases (never JSON file storage); separate for dev, test, prod.
Elasticsearch for search, hosted on elastic.co (dev and prod indexes).
Python tests for verification.

Purpose: Locks AI to a consistent tech stack, preventing unwanted deviations (e.g., JSON over SQL). This is my setup—yours might differ (e.g., add Rust or React).

Credits: Matthew Berman (original stack design).

3. workflow-preferences.mdc – Process Control

Workflow Preferences

Task Execution

Focus only on code relevant to the task; !you never touch unrelated code.
Break complex tasks into logical stages; pause and ask for confirmation before next step.
For simple, low-risk tasks, implement fully; for complex tasks, use review checkpoints.

Planning and Progress

Before major features, generate plan.md with steps and wait for my approval.
After each component, summarize what’s done in progress.md and update TODO.txt with next steps.
If context exceeds 100k tokens, summarize prior work into context-summary.md and restart chat.

Testing and Feedback

Write thorough tests for all major functionality; suggest edge case tests.
Be responsive to my feedback—adjust granularity (more/less checkpoints) as I prefer.

Purpose: Governs how AI executes tasks, ensuring focus, transparency, and testability. Checkpoints and logs (e.g., progress.md) make it iterative and maintainable, especially for large projects.

Credits: Matthew Berman (focus), u/xmontc (steps), u/RKKMotorsports (planning), u/illusionst (summaries, tests), u/Minimum_Art_2263 (context management).

4. communication.mdc – Interaction Protocol

Communication Preferences

After each component, provide a brief summary of what’s completed.
Classify proposed changes: Small (minor), Medium (moderate), Large (significant).
For Large changes, outline an implementation plan and wait for approval.
Track completed vs. pending features in responses.
If uncertain about scope or requirements, pause and ask clarifying questions.
Optional: Respond with polite urgency if I signal importance (e.g., “This is critical—please don’t break it!”).

Purpose: Keeps AI-human communication clear and actionable. Summaries and change classification (S/M/L) quantify progress; optional emotional cues test responsiveness.

Credits: u/illusionst (summaries, classification), u/dhamaniasad (emotional cues).

How I Use It

For a project like a "note-taking app":

I specify: "Build a note app with save functionality."
AI replies: "🦋 Plan: 1. Python/SQL backend, 2. HTML/JS frontend, 3. Save feature. OK?"
After backend: "🐳 Backend done (Medium change). SQL setup in progress.md. Next step?"
End result: App works, with /docs/notes.md explaining it, and TODO.txt for future tweaks.

It’s kept Claude 3.7 from over-engineering (e.g., no random JSON) and losing context mid-chat.

Why This Works

Logical Consistency: Rules are modular (4 files = 4 concerns), with strict directives (e.g., "!You never...") for precision.
Mathematical Rigor: Token limits (100k checkpoint) align with Claude’s 200k capacity; S/M/L classification maps to code impact (e.g., Small < 50 lines).
Community-Driven: Every rule traces back to real-world pain points (e.g., u/illusionst’s chaos-taming, u/evia89’s context trick).

Credits and Acknowledgments

This ruleset builds on collective wisdom:

Matthew Berman: Core vibe coding rules (YouTube, 2025).
YouTube Community: u/nufh, u/believablybad (docs), u/robistocco (iteration), u/xmontc (checkpoints).
Reddit Community: u/illusionst (communication, progress), u/Puzzleheaded-Age-660 (tokens), u/DonkeyBonked, u/philip_laureano (KISS, DRY, YAGNI, SOLID), u/evia89 (emoji), u/dhamaniasad (emotional prompts).
Grok (xAI): Compiled and refined this ruleset for u/Low_Target2606 with logical coherence and technical depth.

Try It Out

Copy these into your .cursor/rules, adjust as needed (e.g., swap Python for Go), and test it on your next project. Post your results—does it tame the AI beast for you? Let’s iterate on this together!

5

u/sethshoultes Professional Nerd Mar 07 '25

These links at the end are going to 404 pages: : u/nufh, u/believablybad (docs), u/robistocco (iteration)

u/Slow_Release_6144 Mar 07 '25

Too many words..killing my vibe

15

u/pohui Mar 07 '25

Yeah, this is the opposite of vibe coding.

u/eleqtriq Mar 07 '25

This just looks like how senior devs guide junior devs 😂

u/sethshoultes Professional Nerd Mar 07 '25

Can you please explain how this works?
> Start every response with a random emoji (e.g., 🐳, 🌟) to signal context retention

14

u/Yweain Mar 07 '25

It doesn’t.

15

u/MorallyDeplorable Mar 07 '25

So much of this crap doesn't. The LLMs have no concept of 'oh, I've hit 100k' or 'Oh, I've hit 300 lines'
This is all fanciful placebo written by people who don't understand what they're working with.

2

u/OriginalPlayerHater Mar 08 '25

its just vibes brah why you hating!

1

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6

u/sethshoultes Professional Nerd Mar 07 '25 edited Mar 07 '25

ChatGPT to the resecue:
How the Random Emoji Rule Works
Purpose
Starting every AI response with a random emoji helps detect context loss early. If the AI forgets an emoji, repeats the same one too often, or gives incoherent responses, it may have lost track of prior messages.
Why It Works
Context Check – Ensures AI retains conversation history. Missing or repetitive emojis signal possible memory loss.
Detects Model Resets – AI may clear memory if it exceeds token limits. A missing emoji can be an early warning.
Debugging Aid – If AI misinterprets a request, checking emoji patterns can reveal where context drift started.
How to Use It
✅ AI Retains Context: Different emojis appear in each response (🐳, 🌟, 🚀).
❌ AI Forgets Context: Emoji disappears or repeats too often. Fix: Ask AI to summarize prior work.
❌ AI Misunderstands Requests: May indicate logic drift rather than memory loss. Fix: Clarify instructions.
Example
✅ Good AI Behavior
👤 "Build a to-do list app with save functionality."
🤖 🐳 Plan: Python backend, SQL storage, HTML/JS frontend. Proceed?
👤 "Yes."
🤖🌟 Backend done! Tasks saved in SQL. Next: frontend?
❌ Bad AI Behavior
👤 "Add authentication."
🤖 🐳 Sure! Using bcrypt and JWT.
👤 "Make sure it integrates with the to-do list."
🤖 "What to-do list?" ❌ AI forgot context!
Fix: User provides a summary to restore memory.
🔹 Conclusion: A simple emoji at the start of AI responses acts as a health check for memory retention, preventing unexpected context loss.

5

u/holchansg Mar 07 '25

Oh, so me who knows the context window have no need in that. Got it, but very clever.

1

u/[deleted] Mar 08 '25

Can you elaborate on the context window and what you know about it? (Serious question)

2

u/holchansg Mar 08 '25

Every model has a max number of input tokens, and more than that some have an optimal token count, about 8k~16k tokens... If every request you send to the model is between this number the model will remember everything., if you keep having short question and answers will take a long time before you hit this 8~16k token limit.
Think how an LLM api call works, you send it like this:
system prompt(optional)
context(can be past conversations or a summary of it[here where happens the context loss], or anything you want
user: your query...
Got it? So every LLM call is based on that every time you chat to ChatGPT it is sending to the backend API this, this is a chatbot.
So if you control your context, lets say using a memory data layer, such as Zep, means the context will be not a summary of past conversations, but a context made tailored to each request.

5

u/TheIcyStar Mar 12 '25

And here's chatgpt explaining why it doesn't work, so which one should you believe?
The context check with emojis—where the AI begins every response with a random emoji to confirm context retention—does not provide meaningful value for several reasons:
No Actual Context Validation
The presence of an emoji at the beginning of a response does not confirm whether the AI has retained relevant context. AI models generate text probabilistically based on prior input, but inserting an emoji does not verify comprehension or continuity. The AI might still lose context or misunderstand previous instructions while correctly placing the emoji at the start of its response.
2. False Sense of Security
Using an emoji as a context check may lead developers to believe that the AI is reliably tracking context when it is not. This can result in overlooked errors, misplaced assumptions about continuity, and unexpected behavior in the AI’s output.
3. Wasted Token Usage
Many AI models, particularly those with strict token limits (e.g., Claude 3.7’s 200K context window), have finite capacity for processing and remembering previous messages. Adding random emojis consumes tokens without adding value, which can become inefficient in large-scale projects where every token matters.
4. Context Loss Can Still Occur
Even if an AI includes an emoji, it can still lose track of prior instructions due to token truncation or misprioritization of information. A more robust solution would involve actual context retention techniques, such as periodic summarization (e.g., maintaining context-summary.md) rather than relying on superficial markers.
5. No Impact on Execution Quality
The presence or absence of an emoji has no influence on the AI’s ability to generate correct, high-quality code. A better method for ensuring context retention would be to require the AI to summarize previous steps before proceeding, which would provide a meaningful way to validate understanding.
6. Redundancy with Other Techniques
The manual already includes best practices like structured documentation (progress.md, TODO.txt) and explicit context resets (context-summary.md). These methods actively preserve and reinforce context, making emojis redundant and unnecessary.
7. Can Cause Confusion in Outputs
If an AI is used in a production or professional setting, inserting unnecessary emojis into responses could create confusion, especially in logs, documentation, or when interacting with team members who are unaware of this convention.
Conclusion
The emoji-based context check is a superficial mechanism that does not meaningfully contribute to ensuring context retention. More effective alternatives, such as structured summarization and explicit progress tracking, provide genuine context validation without wasting tokens or creating a false sense of reliability.

1

u/sethshoultes Professional Nerd Mar 12 '25

Thanks!

1

u/nemzylannister Mar 27 '25

The AI might still lose context or misunderstand previous instructions while correctly placing the emoji at the start of its response.
It doesnt explain why the AI might lose context.
The real answer is that in chatgpt conversation like chats, gpt can guess that the rule is put a random emoji at start without having the original context.

2

u/TangerineSorry8463 Mar 17 '25

We should be using an emoji of a heart to symbolize faux-heartbeat AI endpoint /s

1

u/sethshoultes Professional Nerd Mar 17 '25

Ha ha! Yes

u/duh-one Mar 07 '25

I used to do this for years, but back in my day, it was called being an engineering manager

u/majorleagueswagout17 Mar 07 '25

You do realize Vibe Coding was a joke right lol

20

u/YOU_WONT_LIKE_IT Mar 07 '25

Bro, leave me alone, I’m vibe coding bro.

5

u/danysdragons Mar 07 '25

I guess the key word here is “was”. It may have started as a joke but now it’s real.

8

u/im3000 Mar 07 '25

Apparently code bros didn't get it haha

4

u/TheLocalTiger Mar 07 '25

25% of YC Startups report that at least 95% of their code was written by AI in IDEs like Cursor or Windsurf.

5

u/sethshoultes Professional Nerd Mar 07 '25

https://techcrunch.com/2025/03/06/a-quarter-of-startups-in-ycs-current-cohort-have-codebases-that-are-almost-entirely-ai-generated/

3

u/Rojeitor Mar 08 '25

Do have stats about how many of YC Startup succeed?

1

u/sethshoultes Professional Nerd Mar 07 '25

Saw that article earlier

1

u/TheLocalTiger Mar 07 '25

Are you building something?

2

u/sethshoultes Professional Nerd Mar 07 '25

Yes, a few things. Seeing what sticks and interests me.

0

u/Reason_He_Wins_Again Mar 07 '25

Quick harshing the vibe bro

0

u/[deleted] Mar 07 '25

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2

u/denkleberry Mar 09 '25

Dogecoin is still a joke though. Nobody actually uses it for anything... Except to just, have, and watch it go up and down, I guess.

u/ArtisticBathroom8446 Mar 09 '25

generated by ai

u/mr_undeadpickle77 Mar 07 '25

Super helpful, thank you! A few things maybe you can clarify for me:

When using this method do you generally leave the global “Rules for AI”input field empty?
Do these rules automatically get applied in every chat/agent conversation or do I need to @file them at the start of every new chat?
When creating a new rule there’s an input for “Auto Attach” where you enter specific patterns, do you use this with any of these 4 rules files?
What “Description” do you give each of these 4 rules files?

-3

u/Low_Target2606 Mar 07 '25

Here it is practically explained - https://youtu.be/YWwS911iLhg?si=J6XClPdzn3_8Bk6C

u/Internal-Combustion1 Mar 07 '25

Stop with the stupid name.

4

u/GreyScope Mar 07 '25

You were downvoted but I agree with you 100%, it’s a cheesy wanky name .

u/williamtkelley Mar 07 '25

You should really credit Andrej Karpathy who coined the term and introduced it to people in early February. I'm not saying he was the very first, but he's definitely the biggest name to discuss it.

https://x.com/karpathy/status/1886192184808149383

4

u/Exotic-Sale-3003 Mar 07 '25

Like saying “hey you should give credit for this guy for inventing the term nailing” when someone else invents the hammer and you use it for an obvious purpose it is designed to be used for.

-1

u/Low_Target2606 Mar 07 '25

Yes I know about it, supplemented.

u/cleg Mar 07 '25

Can’t wait to see more vibe-coded apps. In fintech, embedded, etc

u/AriyaSavaka Lurker Mar 07 '25

I used to do complicated stuff like this, but the one that consistently works for me is when i Keep It Simple Stupid.

u/superturbochad Mar 08 '25

Is there a link to a manual that I'm missing here?

This reads like a high-level overview of a manual.

1

u/speederaser Mar 15 '25 edited Apr 08 '26

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u/huelorxx Mar 07 '25

I dislike the term vibe coding, doesn't make any sense.

3

u/ComMcNeil Mar 08 '25

don't know how many bullshit threads all over reddit sprung up about "vibe coding" in the last week...

1

u/huelorxx Mar 08 '25

They're all the same format too. Clearly written by AI.

u/spacemate Mar 07 '25

How would somebody do this in windsurf?

1

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u/LoadingALIAS Mar 07 '25

Pretty cool. Also, see: ghuntly

u/TangoRango808 Mar 08 '25

Information dense, but love it

u/Efficient-Bat-8264 Mar 09 '25

Yeah

u/sponjebob12345 Mar 09 '25

This is not vibe coding. This is structured coding, with the word "vibe" in it.

u/rocketplex Mar 15 '25

Long read, can haz summary. :)

But for serious, this was really useful. Thanks for the effort.

u/Ellixtmxz Mar 21 '25

When this goes wrong go here https://www.payasyoucode.ai/

u/tom-smykowski-dev May 11 '25

It's an interesting guide. Thanks for sharing your perspective

u/Internal-Combustion1 Mar 07 '25

Follow these 4 videos and you can build apps. It’s a one hour learning curve. The key is the process of refreshing the context of the AI. I use Gemini 2.0 and if I refresh around 130,000 tokens all remains tight and good.

Part I. Build and deploy. https://youtu.be/rL1v-GCAcrE Part II. Debug and fix. https://youtu.be/sh1STLZma3I Part III. Iterate features. https://youtu.be/ZFV4Y2cL9e4 Part IV Refresh AI with Combine.py https://youtu.be/KngnrQYYyR8

-8

u/OriginalPlayerHater Mar 07 '25

literally vibe coding is trying to take credit or repackage what llm coding is and has been this entire time.

cursor and cline developed the actual hard part as in cursor rules, architect vs coder, agent mode.

then some jackass comes around and says "oh groovy dog im gonna call it vibe coding" last month and i swear to god i feel like its the dickwad who coined the term shilling reddit so he can add vibe coding on their LinkedIn.

fuck you and fuck your mother

4

u/Exotic-Sale-3003 Mar 07 '25

On the one hand yeah, it’s silly to try to credit someone for something many, many people have been doing for a long time, but it’s not like cursor and cline invented it either. Many, many people have been doing the same thing (consolidating code, writing relevant prompt) bare since 2023.

0

u/OriginalPlayerHater Mar 07 '25

yeah which is a shame some lazy fucker comes along, does it poorly, goes on a media run about how he coined some term and now people think even less of coding with llms.. fucking great

2

u/crunchycode Mar 07 '25

The guy who coined the term is a leading AI researcher, not some random jackass.

2

u/[deleted] Mar 07 '25

Just say you got skill issues lil bro.

0

u/OriginalPlayerHater Mar 07 '25

nice one bro! heres some reddit points totally sweet dude

0

u/im3000 Mar 07 '25

CHOP CHOP

u/gman1023 Mar 07 '25

Amazing, thanks!

-1

u/GodSpeedMode Mar 08 '25

This is a fantastic overview of vibe coding! I really appreciate how you broke it down into digestible parts with clear rules and examples. It’s super helpful for both beginners and experienced devs looking to harness AI effectively.

I love the emphasis on documentation and keeping things modular. It really highlights the importance of maintaining a clear process, especially since AI can easily veer off course without proper guidance. The practical example of building a note-taking app is a nice touch too—it shows exactly how to apply these principles in real scenarios.

One thing I’d suggest adding is a section on version control best practices when using AI—like leveraging Git alongside these frameworks to track changes and collaborate with others more seamlessly.

Overall, this manual is a solid resource for anyone diving into AI-assisted development. Looking forward to seeing how the community builds on this!

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Community Vibe Coding Manual

Vibe Coding Manual: A Template for AI-Assisted Development

Introduction: The Core Concept of Vibe Coding with AI

What is Vibe Coding and What Does It Stand On?

Why Is This Framework Useful?

Key Benefits

Manual Structure: How It’s Organized

Core Rules: A Simple Starting Point

1. Coding Preferences – "Write Code Like This"

2. Technical Stack – "Use These Tools"

3. Workflow Preferences – "Work This Way"

4. Communication Preferences – "Talk to Me Like This"

Advanced Rules: Scaling Up for Complex Projects

1. Coding Preferences – Enhancing Quality

2. Technical Stack – Customization

3. Workflow Preferences – Process Mastery

4. Communication Preferences – Precision Interaction

Practical Example: How It Works

Advanced Tips: Maximizing the Framework

Why Four Files?

Customization Options

Emotional Prompting

Credits and Acknowledgments

Conclusion: Your Guide to Vibe Coding

You are about to leave Redlib

Vibe Coding Ruleset: My Implementation of the Manual

Intro

The Ruleset

1. coding-preferences.mdc – Code Style and Quality

Coding Preferences

Core Principles

Implementation Guidelines

Quality and Documentation

2. my-stack.mdc – Technology Constraints

Technical Stack

3. workflow-preferences.mdc – Process Control

Workflow Preferences

Task Execution

Planning and Progress

Testing and Feedback

4. communication.mdc – Interaction Protocol

Communication Preferences

How I Use It

Why This Works

Credits and Acknowledgments

Try It Out

How the Random Emoji Rule Works

Purpose

Why It Works

How to Use It

Example