{"id":5367,"date":"2025-03-13T14:39:38","date_gmt":"2025-03-13T14:39:38","guid":{"rendered":"https:\/\/servicesground.com\/blog\/?p=5367"},"modified":"2025-03-13T14:59:39","modified_gmt":"2025-03-13T14:59:39","slug":"ai-powered-coding-vibe-coding-development","status":"publish","type":"post","link":"https:\/\/servicesground.com\/blog\/ai-powered-coding-vibe-coding-development\/","title":{"rendered":"A Practical Guide to AI-Assisted Coding (Vibe Coding)"},"content":{"rendered":"

AI is changing the way we write code. Instead of just assisting with small snippets, AI can now take on an entire project\u2014writing, debugging, and even testing the code while developers guide the process. This approach, often called <\/span>Vibe Coding<\/b> or <\/span>Agentic Coding<\/b>, allows AI to handle most of the heavy lifting, enabling developers to focus on refining and directing the project.<\/span><\/p>\n

This guide summarizes key insights on how to make the most of AI-powered coding<\/a>, particularly in <\/span>Cursor and WindSurf IDEs<\/b>, while ensuring the results are reliable and maintainable.<\/span><\/p>\n

Choosing the Right AI Model<\/h2>\n
Different AI models excel at different tasks. Here\u2019s how they compare for Vibe Coding:<\/span><\/p>\n
\n
Claude 3.7 Sonnet<\/a> (Thinking mode)<\/b> \u2013 Best for structured coding, <\/span>function calling<\/b>, and <\/span>tool integration<\/b>.<\/span><\/li>\n
Grok 3<\/b><\/a> \u2013 Useful for generating <\/span>detailed project specifications<\/b> before coding begins.<\/span><\/li>\n
GPT-4<\/a>, DeepSeek, LLaMA, Mistral<\/b> \u2013 Alternative models that work well for AI-assisted coding, but may vary in reliability and context handling.<\/span><\/li>\n<\/ol>\n
Using Custom AI Models in Cursor<\/b><\/h3>\n
Cursor IDE allows <\/span>custom AI model integration<\/b>, meaning you can:<\/span><\/p>\n
\n
Override the <\/span>OpenAI API Key<\/b> in settings.<\/span><\/li>\n
Use alternative models like <\/span>Grok<\/b><\/a>, which supports OpenAI\u2019s API format.<\/span><\/li>\n
Experiment with different models to find the best fit for your coding style.<\/span><\/li>\n<\/ol>\n
The Importance of AI Coding Rules<\/b><\/h2>\n
A key lesson from using AI for coding is that <\/span>AI needs clear guidelines<\/b> to ensure high-quality output. Without structured rules, AI can:<\/span><\/p>\n
\n
Use the wrong technologies<\/b> (e.g., switching from SQL to JSON storage unexpectedly).<\/span><\/li>\n
Introduce duplicate code<\/b> instead of reusing existing functions.<\/span><\/li>\n
Break unrelated parts of the project<\/b> while fixing bugs.<\/span><\/li>\n
Generate too much mock data<\/b>, making production unreliable.<\/span><\/li>\n<\/ul>\n
To prevent these issues, developers can define <\/span>specific AI coding rules<\/b>.<\/span><\/p>\n
$\"$ <\/a><\/h2>\n
Key AI Coding Rules for Better Code Quality<\/b><\/h2>\n
By setting clear rules, developers can ensure AI follows correct development patterns.<\/span><\/p>\n
General Code Quality Guidelines<\/b><\/h3>\n
\n
Favor simple solutions<\/b> over unnecessary complexity.<\/span><\/li>\n
Avoid code duplication<\/b>\u2014make sure AI <\/span>reuses existing functions<\/b>.<\/span><\/li>\n
Check for existing logic<\/b> before adding new code.<\/span><\/li>\n<\/ol>\n
Environment-Specific Rules<\/b><\/h3>\n
\n
Keep <\/span>separate environments<\/b> for development, testing, and production.<\/span><\/li>\n
AI should <\/span>not modify <\/b>.env<\/b> files<\/b> to prevent accidental resets of API keys.<\/span><\/li>\n
Ensure <\/span>database configurations remain stable<\/b> across environments.<\/span><\/li>\n<\/ol>\n
AI Behavior Rules<\/b><\/h3>\n
\n
AI should <\/span>only make requested changes<\/b>\u2014no unnecessary refactoring.<\/span><\/li>\n
Avoid introducing <\/span>new technologies or patterns<\/b> unless absolutely necessary.<\/span><\/li>\n
Large files should be <\/span>refactored before exceeding 200\u2013300 lines<\/b> for maintainability.<\/span><\/li>\n<\/ol>\n
Data Handling Rules<\/b><\/h3>\n
\n
Mock data should be <\/span>limited to test environments<\/b> only.<\/span><\/li>\n
AI should <\/span>use SQL databases<\/b> rather than storing data in JSON files.<\/span><\/li>\n
The AI should <\/span>strictly follow the chosen tech stack<\/b>.<\/span><\/li>\n<\/ol>\n
Setting Up Rules in Cursor<\/b><\/h2>\n
If you’re using Cursor IDE, you can configure AI coding rules in a few steps:<\/span><\/p>\n
\n
Open Cursor IDE.<\/span><\/li>\n
Go to <\/span>Settings \u2192 Rules<\/b>.<\/span><\/li>\n
Create a <\/span>cursor\/rules\/<\/b> folder<\/b> to define project-specific guidelines.<\/span><\/li>\n
AI will now follow your coding preferences and workflow.<\/span><\/li>\n<\/ol>\n
$\"AI$ <\/a><\/h2>\n
AI-Driven Coding: Step-by-Step Process<\/b><\/h2>\n
1. Generate a Detailed Project Specification<\/b><\/p>\n
Start by using <\/span>Grok 3<\/b> or <\/span>Claude 3.7<\/b> to create a comprehensive project specification. A good spec includes:<\/span><\/p>\n
\n
Tech stack<\/b><\/li>\n
Database schema<\/b><\/li>\n
API endpoints<\/b><\/li>\n<\/ul>\n
2. Load the Specification into Cursor<\/b><\/h3>\n
\n
Open a new <\/span>Cursor project<\/b>.<\/span><\/li>\n
Paste the specification into the <\/span>AI chat window<\/b>.<\/span><\/li>\n
Let AI generate the code based on the provided details.<\/span><\/li>\n<\/ul>\n
3. Monitor AI\u2019s Code Generation<\/b><\/h3>\n
\n
AI will generate <\/span>entire files and features<\/b>.<\/span><\/li>\n
Apply <\/span>rules<\/b> to ensure the AI follows best practices.<\/span><\/li>\n
Keep AI\u2019s <\/span>context window small<\/b> to avoid performance slowdowns.<\/span><\/li>\n<\/ul>\n
4. Testing & Quality Assurance<\/b><\/h3>\n
\n
End-to-end testing<\/b> is more effective than unit tests.<\/span><\/li>\n
After every change, <\/span>run tests<\/b> to prevent regressions.<\/span><\/li>\n
AI should <\/span>automatically generate test cases<\/b> for all new functionality.<\/span><\/li>\n<\/ul>\n
Optimizing the AI Coding Workflow<\/b><\/h2>\n
Choosing the Right Execution Mode<\/b><\/h3>\n
\n
Manual Mode<\/b> \u2013 AI requires approval for every change.<\/span><\/li>\n
Auto Mode<\/b> \u2013 AI decides which actions need approval.<\/span><\/li>\n
YOLO Mode<\/b> \u2013 AI executes all changes automatically (<\/span>not recommended for production<\/b>).<\/span><\/li>\n<\/ol>\n
Speed & Efficiency Tips<\/b><\/h3>\n
\n
Run <\/span>multiple branches in separate Cursor windows<\/b> to develop features in parallel.<\/span><\/li>\n
Claude 3.7 (Thinking mode)<\/b> provides <\/span>more accurate<\/b> results but can be slower.<\/span><\/li>\n
Use <\/span>lighter models<\/b> for quick refactoring and small fixes.<\/span><\/li>\n<\/ol>\n
Common Pitfalls & How to Avoid Them<\/b><\/h2>\n
Here are some common challenges and their solutions:<\/span><\/p>\n
AI Breaks Other Features While Fixing Bugs<\/b><\/h3>\n
\n
Solution:<\/b> Clearly instruct AI to <\/span>only modify the requested section<\/b>.<\/span><\/li>\n
Solution:<\/b> Run tests to ensure existing features remain unaffected.<\/span><\/li>\n<\/ul>\n
AI Overwrites <\/b>.env<\/b> Files or API Keys<\/b><\/h3>\n
\n
Solution:<\/b> Explicitly define rules to prevent AI from modifying environment variables.<\/span><\/li>\n<\/ul>\n
AI Generates Unnecessary Mock Data<\/b><\/h3>\n
\n
Solution:<\/b> Restrict mock data usage to <\/span>test environments only<\/b>.<\/span><\/li>\n<\/ul>\n
AI Takes Too Long to Execute Changes<\/b><\/h3>\n
\n
Solution:<\/b> Keep AI <\/span>context size small<\/b> and <\/span>start fresh chats regularly<\/b>.<\/span><\/li>\n<\/ul>\n
Additional AI Tools to Enhance Development<\/b><\/h2>\n
The speaker also mentioned <\/span>Mammoth AI<\/b>, a $10\/month tool that grants access to:<\/span><\/p>\n
\n
Claude, GPT-4, DeepSeek, LLaMA, Mistral, Grok<\/b> for coding.<\/span><\/li>\n
MidJourney, Stable Diffusion, and DALL\u00b7E<\/b> for image generation.<\/span><\/li>\n<\/ol>\n
These models can act as <\/span>coding agents<\/b> within <\/span>Cursor and WindSurf<\/b>, further improving the AI-assisted development process.<\/span><\/p>\n
$\"Ai$ <\/a><\/h2>\n
Final Thoughts<\/b><\/h2>\n
After spending <\/span>over 100-150 hours<\/b> coding with AI agents, the speaker concluded:<\/span><\/p>\n
\n
AI-powered coding is highly effective<\/b> when paired with well-defined rules.<\/span><\/li>\n
It works best for full projects<\/b>, rather than small snippets.<\/span><\/li>\n
Success depends on clear workflows and rigorous testing.<\/b><\/li>\n
AI speeds up development but still requires human oversight<\/b> to ensure code quality.<\/span><\/li>\n<\/ol>\n
While <\/span>Vibe Coding isn\u2019t perfect yet<\/b>, it’s evolving quickly. As AI tools improve, mobile-friendly coding agents may become the next big innovation in software development.<\/span><\/p>\n
Key Takeaways<\/b><\/h2>\n
\n
AI can generate entire applications<\/b>, but it needs <\/span>strict rules<\/b> to maintain code quality.<\/span><\/li>\n
Cursor & WindSurf + Claude 3.7 (Thinking mode) offer the best experience<\/b>.<\/span><\/li>\n
Testing, version control, and workflow rules<\/b> are essential for managing AI-generated code.<\/span><\/li>\n
Developers still play a critical role<\/b>\u2014AI can assist, but human oversight ensures success.<\/span><\/li>\n<\/ol>\n
With the right <\/span>tools and strategies<\/b>, AI can transform how we build software, making development faster and more efficient than ever before.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
AI is changing the way we write code. Instead of just assisting with small snippets, AI can now take on an entire project\u2014writing, debugging, and even testing the code while developers guide the process. This approach, often called Vibe Coding or Agentic Coding, allows AI to handle most of the heavy lifting, enabling developers to […]<\/p>\n","protected":false},"author":1,"featured_media":5369,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1625],"tags":[],"yst_prominent_words":[150],"class_list":["post-5367","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence"],"_links":{"self":[{"href":"https:\/\/servicesground.com\/blog\/wp-json\/wp\/v2\/posts\/5367","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/servicesground.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/servicesground.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/servicesground.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/servicesground.com\/blog\/wp-json\/wp\/v2\/comments?post=5367"}],"version-history":[{"count":0,"href":"https:\/\/servicesground.com\/blog\/wp-json\/wp\/v2\/posts\/5367\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/servicesground.com\/blog\/wp-json\/wp\/v2\/media\/5369"}],"wp:attachment":[{"href":"https:\/\/servicesground.com\/blog\/wp-json\/wp\/v2\/media?parent=5367"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/servicesground.com\/blog\/wp-json\/wp\/v2\/categories?post=5367"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/servicesground.com\/blog\/wp-json\/wp\/v2\/tags?post=5367"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/servicesground.com\/blog\/wp-json\/wp\/v2\/yst_prominent_words?post=5367"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}