10 Vibe Coding Tips That Transform How You Build with AI
Transform your AI development workflow with practical strategies that deliver real results
The vibe coding revolution isn’t coming—it’s already here. And it’s not just changing how we write code; it’s democratizing who gets to build software in the first place.
Here’s what nobody tells you: the barrier between idea and execution has collapsed. Anyone who can have a conversation can now build sophisticated applications. But there’s a catch—most people are using AI like a fancy autocomplete when they should be treating it like a collaborative partner.
I’ve spent the last few months building solutions for indigenous communities, social impact projects, and mission-driven organizations. What I’ve learned has fundamentally changed how I approach development. These aren’t theoretical tips—they’re battle-tested strategies from real projects serving real people.
If you’re building in service of others, these techniques will transform your workflow from overwhelming to empowering.
1. Start with Better Prompts, Not More Code
The foundation of effective vibe coding isn’t technical prowess—it’s communication. Your first prompt is rarely your best prompt, and that’s okay.
Most developers jump straight into coding mode, throwing generic requests at AI tools and getting frustrated with mediocre results. But when you’re building in service of communities, mediocre isn’t an option.
Use AI to Improve Your Prompts
Here’s the workflow: instead of going directly to your coding tool with “build a fitness tracker app with black and blue colors,” let the AI expand that into:
”Create a web-based fitness tracker application that helps users monitor workout progress and fitness goals with a sleek black and blue color scheme, featuring core functionalities like workout logging, progress visualization, and goal setting, with visual inspiration from Nike Training Club and Strava’s clean interface design.”
See the difference? The enhanced prompt gives context, specific features, and visual references. It’s the difference between asking someone to “make dinner” versus sharing your dietary needs, favorite flavors, and inspiration photos.
Leverage External AI for Prompt Generation
Here’s my secret weapon: I’ll hop into ChatGPT, Claude, or Gemini and say:
”I want to build a community resource dashboard for indigenous communities. Give me a detailed prompt that will result in a culturally sensitive, accessible web application for supporting a Huni Kuin tribe to manage funds from a community development grant.”
The AI doesn’t just give me technical specs—it considers user experience, accessibility requirements, and cultural considerations I might have missed. This give-first approach to prompting creates better outcomes for everyone.
2. Choose Your Tools Like You Choose Your Community
Not all vibe coding tools are created equal. The one you choose should align with your goals, skill level, and project requirements—not your ego.
The Beginner-Friendly Path
Replit and Lovable are fantastic starting points. They’re intuitive, handle deployment complexity, and let you focus on the problem you’re solving rather than infrastructure headaches. When I’m prototyping community solutions quickly, these are my go-to tools.
Don’t get caught up in tool envy. Pick one, get comfortable with it, then expand your toolkit as your needs grow. Try a few different tools within your budget and don’t get attached.
Intermediate to Advanced Workflows
Bolt.new and v0.dev offer more control and customization—perfect for complex applications. Claude Code is my choice for heavy-duty development work, especially when integrating with existing codebases. Cursor and Antigravity shine when you want an integrated development environment experience for fine-grained edits.
The key: match the tool to your current project needs, not your aspirations. I’ve watched developers struggle with advanced tools for months when a simpler solution would have launched their community impact project immediately.
3. Show, Don’t Tell: The Power of Visual Prompts
Here’s a technique that 10x’d my output quality: stop describing interfaces in words. Start showing them.
AI tools are remarkably good at understanding visual context. Instead of spending paragraphs describing a user interface, attach an image of a similar app and say “build something like this, but for [your specific use case].”
When building a resource-sharing platform for a local indigenous community, I showed the AI examples of successful community platforms. The results were immediately more culturally appropriate and user-friendly than anything I could have described in text.
Reference Real Applications
Always give your AI tool inspiration sources:
Building an e-commerce site? Reference successful sites URLs in your niche
Creating a community dashboard? Point to platforms that handle similar use cases well
Designing a mobile app? Screenshot apps with the user experience you’re targeting
This isn’t copying—it’s learning from proven patterns and adapting them to your specific community needs.
4. Understand Your AI-Built Applications (Before You Need To)
Here’s something critical that many vibe coders miss: you need to understand what’s happening under the hood, even if you didn’t write the code yourself.
I make it a practice to regularly ask my AI tools: ”Explain how this application works in detail.” This isn’t just about technical curiosity—it’s about being a responsible builder, especially when creating tools that communities will depend on.
Ask for Clarity. Continually Refine.
Throughout the development process, pause and ask your agent:
“What technologies are we using and why? Are there any simpler alternatives at our scale?”
“How does the data flow through the application? Can we reduce complexity?”
“What are the potential security considerations? Can you audit before production?”
“How would we scale this if usage grows? Can you cost out the infrastructure?”
This knowledge becomes crucial when you need to maintain, debug, or extend your application. Plus, it builds your overall development understanding over time—you’re learning while building.
5. Iterate in Small Steps, Not Giant Leaps
Here’s where most vibe coders sabotage themselves: they try to do too much at once.
The AI can handle complex requests, but that doesn’t mean it should. I’ve learned the hard way that feature creep kills momentum and introduces bugs you’ll spend hours tracking down.
One Feature, One Prompt
Instead of saying “add dark mode and remove this button and improve the navigation and fix the mobile layout,” break it into separate, focused requests:
“Add dark mode support with smooth transitions”
“Remove the ‘Subscribe’ button from the header”
“Improve navigation by consolidating menu items”
“Fix mobile layout for screens under 768px”
This leads to cleaner implementations, fewer bugs, and code that’s easier to maintain.
Use Spec-Driven Development! 👈
Task-master, SpecKit, or even a simple checklist keeps you focused and in control. Each feature gets its own conversation, its own testing, its own modular code. This is how complex systems are built
Small steps compound. Giant leaps stumble.
6. Let AI Suggest Features (Then Filter Ruthlessly)
One of my favorite techniques: ask the AI to suggest new features for your application. It often comes up with ideas you hadn’t considered, especially around accessibility and user experience improvements.
Try this prompt: ”Based on this application’s current functionality, suggest 10 features that would improve user experience, with focus on accessibility and mobile usability.”
You’ll get ideas ranging from obvious improvements you missed to innovative features you never would have thought of.
But Here’s the Key
Just because the AI suggests a feature doesn’t mean you should build it. Stay ruthlessly focused on your core mission. When building for communities, every feature should serve your users’ actual needs—not just sound cool.
I use this test: “Would this feature directly help someone accomplish their goal faster or better?” If not, it’s a distraction.
7. Maintain a Prompt Journal (Your Secret Weapon)
This might sound old-school, but keeping a log of prompts that worked (and ones that didn’t) has been invaluable for my workflow.
I maintain templates for:
Community dashboard builds
Accessibility-focused applications
Mobile-responsive layouts
Payment processing integrations
Over time, this becomes your personal library of proven approaches. When starting a new project, I reference successful prompts from similar builds, adapting them for the new context.
8. Think Like a Designer, Not a Coder
This shift in mindset is huge: describe the outcome you want, not the technical implementation.
Instead of this:
“Use React with TypeScript, implement a REST API with Express, use PostgreSQL for the database, and create authentication with JWT tokens.”
Try this:
“Create a user-friendly dashboard where community members can easily share and discover local resources. Users should be able to log in securely, post resources with photos and descriptions, search by category, and save favorites.”
Let the AI choose the technical stack based on your requirements. You’ll often be surprised by the solutions it suggests—sometimes simpler, sometimes more robust than what you would have chosen.
But Watch for Over-Engineering
LLMs have a tendency to over-engineer solutions. Always remind the agent what stage you’re at:
“This is an MVP for initial user testing”
“This is production-ready with 50 active users”
“This needs to scale for post-PMF growth in a highly-regulated industry”
Context prevents the AI from building a nuclear reactor when you need a campfire.
9. Use AI to Criticize Its Own Work
Here’s an advanced technique I use religiously: ask the AI to critique its own output.
After it generates code or completes a feature, I prompt:
”Review this code for potential issues, security vulnerabilities, and areas for improvement. What would you do differently? Be brutally honest.”
This catches bugs early and often suggests optimizations I wouldn’t have thought of. It’s like having a senior developer review every piece of code, even when you’re building solo.
Follow-Up Questions That Reveal Issues
“What edge cases have we missed?”
“How would this perform with 1,000 concurrent users?”
“What’s the most likely security vulnerability in this implementation?”
“If you were going to break this code, how would you do it?”
These questions force the AI to think adversarially about its own work. You’ll uncover edge cases and vulnerabilities before your users do.
10. Build with Purpose, Maintain with Pride
Vibe coding isn’t just about writing less code—it’s about building more intentionally and honestly, having more fun.
When you combine these techniques with a service-oriented mindset, you create applications that truly serve communities and solve real problems. But your responsibility doesn’t end at deployment.
Document As You Go
Ask your AI to dispatch a librarian subagent to generate:
User guides for community members
Technical documentation for future maintainers
Troubleshooting guides for common issues
Onboarding materials for new team members
Plan for Maintenance
Before launching, ask your AI:
“What maintenance tasks will this application require?”
“How should we monitor for issues and performance?” (Sentry, etc.)
“What’s our backup plan?”
“How should we we handle user requests, feedback, bugs?”
Building in service of communities means building for the long haul. These applications need to work not just today, but for years to come.
Ready to Build Real Products for Real People?
The key is starting simple, staying curious, and always keeping your end users at the center of your development process.
Whether you’re building for indigenous communities, social impact organizations, or any group that needs technology solutions, these vibe coding principles will help you build better, faster, and with more impact.
Want to dive deeper? I’m offering a free consultation for regenerative leaders, indigenous communities to discuss how these techniques can accelerate your impact-focused projects.
Let’s build something meaningful together.
What’s your biggest challenge with AI-assisted development?
Have you given vibe coding a try?