AI Agent
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Minimum Viable Product.
In the context of product development, especially when you’re talking about guiding AI for screen building (or any software development for that matter), the MVP is the most basic version of your product that has just enough features to be usable by early customers. The goal of an MVP is to gather validated learning about the product and its continued development.
Think of it as the essential core of your idea, stripped down to its most crucial elements. It’s not the final, fully featured product, but rather a stepping stone that allows you to:
- Test your core assumptions: Does your basic idea even resonate with users?
- Gather early feedback: What do users like? What are their pain points?
- Avoid building something nobody wants: By getting feedback early, you can iterate and pivot if necessary.
- Get to market faster: A smaller scope means quicker development and launch.
So, when planning the MVP for “vibe coding,” you’re essentially defining the absolute must-have screens and functionalities that will allow you to validate your concept before investing in more complex features. This focused approach helps you direct the AI effectively and avoid it generating unnecessary or premature elements.
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Most people think vibe coding means casually prompting AI to build random screens. That’s just chaos. Real vibe coding means: • Planning the MVP first • Writing a clear PRD • Using structured prompts • Setting up a system AI can follow If you don’t set the direction, AI will make it up.
You don’t need to learn how to code if your goal is to build MVPs for yourself. AI can handle 80% of the heavy lifting. But you do need to learn how to run code: • Frontend vs backend • How to deploy apps • Supabase, Stripe, GitHub • Auth, storage, structure
That’s the real unlock.
my framework on how to master this:
- Bootstrap from power templates Fork real-world starter kits: – Auth + Payments + DB already wired – Supabase, Stripe, Clerk, Railway baked in cuts your build time before you even think about features.
- Use GPT as a system architect, not a coder Prompt like this: “You are my lead engineer. Analyze this stack. What are the critical failure points? What scale limits will we hit first? How would you modularize this for faster iteration?” I like to use GPT + AI coding tool (cursor, replit etc.)
- Build a Personal Infrastructure Stack Every time you ship and debug a piece (auth flow, checkout, CRUD ops): – Save it in your GitHub – Document it like a mini-SaaS template – Automate your deploy configs (Vercel, Railway, Render)
- Optimize for Speed of Iteration The first version will suck. That’s the point. The leverage comes from: – shipping v1 ugly – getting real user friction – tweaking v2 in a few hours – scaling only after the engine works also been playing around with:
- Simulate Failure Before shipping, prompt GPT: “Act like a QA tester and try to break this product. What are the 10 most likely ways it will fail?”
1/ Start with a sharp project brief Before touching any tool, I always define: What’s the product? A web app that pulls outreach metrics from SmartLead and HeyReach into one shareable dashboard. Who’s it for? Agencies, freelancers, and growth teams running multiple outbound campaigns. What problem does it solve? No more jumping between platforms or exporting data. This makes reporting frictionless. Example Prompt: “I’m building a platform called ColdHub that centralizes outreach campaign metrics from SmartLead and HeyReach. Help me draft a clear project brief.”
2/ Let ChatGPT generate your feature list Once the brief was done, I asked ChatGPT to generate features + tech specs. Prompt: “Using this project brief, generate a full feature list for the MVP including technical suggestions and API usage.” Features identified: - Connect SmartLead + HeyReach with API keys - Real-time dashboard with metrics - White-label branding (logo + color) - Shareable links + PDF exports - Stripe-based subscriptions with trial support
3/ Categorize features with MoSCoW Then I used the MoSCoW method to prioritize: Must-Have: Connect outreach tools, show live metrics, white-labeled dashboard, Stripe integration, custom domain support Should-Have: PDF export, team invites Could-Have: Advanced analytics (phase 2) Won’t-Have: CRM integrations (future scope) Prompt: “Here’s the feature list. Use MoSCoW method to prioritize features for Phase 1.”
4/ Document everything before building Before I write a single line of code, I prep all the documentation: - PRD - Database Design - Design System, etc. You can generate these using ChatGPT, or use
to speed things up and then save these as markdown files. Planning saves weeks of confusion later.
5/ Plan the screens Prompt: “Based on this MVP, what screens should the MVP have? Explain each screen in detail.” I like using o1 for this as the responses are very detailed. Final screens: - Login / Onboarding - Connect Outreach Tools - Dashboard (SmartLead + HeyReach data) - Branding Settings - Stripe Payment + Upgrade - Share Link Preview - and more…
6/ Design + Build UI inside Bolt I opened up UX Pilot and then Bolt, pasted my PRD + screen list, and started building the UI. - Used UX Pilot to generate polished screen code - Imported it into Bolt and converted the designs into code - Customized layouts and structure based on the client’s vision I had a complete frontend ready in under 3 days.
7/ Set up the backend with Supabase Use Bolt to setup Supabase for: - Authentication - DB for storing API keys, user data, branding settings - RLS policies - Edge functions - Strip integration
8/ SmartLead + HeyReach API integration After the 80-90% of the MVP was ready in Bolt, I synced the codebase into Cursor to handle advanced stuff. Inside Cursor, I: - Added API docs for both SmartLead and HeyReach - Implemented caching and debounce techniques to reduce unnecessary API calls - Used Browser MCP to debug faster with live logs and page screenshots - Security Audit Cursor made it easy to structure clean, reusable backend logic without context switching.
9/ Final result Live features: - Real-time outreach metrics from both tools - White-labeled, shareable dashboards - Branded views with client logos - Stripe-powered upgrades and subscriptions All built with Bolt, Cursor, and Supabase.
Final takeaway Building an MVP? - Begin with
- Cursor for advanced logic - Supabase + Vercel to go live - Plan everything with ChatGPT I’m dropping a full series on this inside my AI MVP Builders community.