Welcome to the Proof of Usefulness Hackathon spotlight, curated by HackerNoon’s editors to showcase noteworthy tech solutions to real-world problems. Whether you’re a solopreneur, part of an early-stage startup, or a developer building something that truly matters, the Proof of Usefulness Hackathon is your chance to test your product’s utility, get featured on HackerNoon, and compete for $150k+ in prizes. Submit your project to get started! Welcome to the Proof of Usefulness Hackathon spotlight, curated by HackerNoon’s editors to showcase noteworthy tech solutions to real-world problems. Whether you’re a solopreneur, part of an early-stage startup, or a developer building something that truly matters, the Proof of Usefulness Hackathon is your chance to test your product’s utility, get featured on HackerNoon, and compete for $150k+ in prizes. Submit your project to get started! Proof of Usefulness Hackathon spotlight Proof of Usefulness Hackathon spotlight Proof of Usefulness Hackathon Proof of Usefulness Hackathon $150k+ Submit your project to get started Submit your project to get started In this interview, we sit down with Alex Rai, the creator of HatchIt, an AI-powered website builder that generates production-ready React and Tailwind CSS code. Unlike traditional website builders that trap projects in their ecosystem, HatchIt allows developers to export code directly to their GitHub repositories. HatchIt What does HatchIt do? And why is now the time for it to exist? HatchIt is an AI-powered website builder that gives you production-ready React and Tailwind CSS code—no screenshots, no vendor lock-in. Unlike traditional AI builders that trap your project on their platform, HatchIt exports code directly to your GitHub repository while providing enterprise-grade infrastructure with zero configuration. Now’s a good time for HatchIt to exist because the AI website builder market is projected to reach $1.8B+ by 2028, yet 95% of tools still don't give developers access to the actual code. What is your traction to date? How many people does HatchIt reach? HatchIt currently serves individual developers, small dev agencies, and technical founders who need to rapidly prototype and deploy production-grade websites. Since making the platform public in early January 2026, we've seen strong interest from the developer community on Reddit and GitHub, with developers particularly appreciating the "no vendor lock-in" approach. The platform is actively used by the founder for client work, validating real-world production use. As an early-stage product, we're focused on quality feedback over user count, currently working with select beta testers while refining core features. We're targeting 100-500 active developers within Q1 2026 as we scale based on early adopter insights. Who does your HatchIt serve? What’s exciting about your users and customers? HatchIt is built for three primary audiences: (1) Solo developers and freelancers who need to quickly build client websites while maintaining code ownership and professional quality standards; (2) Small development agencies (2-10 people) who want to accelerate their development workflow without sacrificing control or technical quality; (3) Technical founders building MVPs who need speed to market without getting locked into proprietary platforms. Primary pain point: existing AI website builders don't export real code, force users onto their platforms with subscription fees, and can't handle production requirements like authentication, databases, and custom deployment. HatchIt users benefit from 10-100x faster development while maintaining full code ownership, GitHub version control, and enterprise-grade infrastructure (Vercel, Supabase, Clerk) with zero configuration. Early feedback from the developer community shows particular appreciation for the combination of AI speed with code ownership—developers want velocity without vendor lock-in. What technologies were used in the making of HatchIt? And why did you choose the ones most essential to your tech stack? HatchIt was built using a robust, modern tech stack designed for production-grade web development, incorporating technologies like Algolia, Neo4j, and Bright Data alongside a custom LLM integration. At its core, the platform leverages React 19, Tailwind CSS 4, and TypeScript to ensure accessible, maintainable, and type-safe UI components. For enterprise-grade infrastructure and seamless deployment, we integrated Vercel, Supabase, and Clerk, while utilizing the GitHub API to deliver our core promise: giving developers full ownership of their exported code. HatchIt scored a 56 proof of usefulness score (https://proofofusefulness.com/report/hatchit-ai-website-builder-with-real-code-export) HatchIt scored a 56 proof of usefulness score (https://proofofusefulness.com/report/hatchit-ai-website-builder-with-real-code-export) https://proofofusefulness.com/report/hatchit-ai-website-builder-with-real-code-export What excites you about HatchIt's potential usefulness? Three aspects of HatchIt's potential usefulness excite me most: Three aspects of HatchIt's potential usefulness excite me most: FIRST - Solving Real Vendor Lock-In Problem: I built HatchIt because I was frustrated with existing AI builders that trap your code. Every AI website builder forces you onto their platform with no export—creating a massive problem when you outgrow the tool or want to customize. The AI website builder market is projected to reach $1.8B+ by 2028, yet 95% of tools don't give you the actual code. HatchIt's GitHub-first approach fundamentally solves this, giving developers freedom and control. This isn't theoretical—I personally need this solution for my client work. SECOND - Real-World Production Validation: The most exciting proof of usefulness is that I use HatchIt daily for actual client projects. I spent hundreds of hours and sacrificed Christmas and New Year getting it right because I needed a tool I could trust with paying clients. Every feature exists because I needed it in production. When you build a tool you use yourself for real work, you know it delivers genuine value. This "dogfooding" approach means HatchIt solves real problems, not imagined ones. If it's good enough for my client work, it's production-ready for other developers. THIRD - Developer Empowerment at Scale: By combining AI speed with code ownership, HatchIt enables solo developers to compete with large agencies. A single developer can now ship enterprise-grade websites in minutes instead of weeks, while maintaining professional standards and full control. This democratization is genuinely useful for thousands of developers who want velocity without sacrificing quality or getting locked into platforms. The combination of React 19, Tailwind 4, TypeScript, plus production infrastructure (Vercel, Supabase, Clerk) gives developers enterprise capabilities without enterprise overhead. Most excitingly, HatchIt proves AI tools don't have to trap users in walled gardens. Real code, real infrastructure, real ownership—that's technology serving developers, not extracting from them. The early feedback validating this approach tells me we're solving a problem developers genuinely care about. Meet our sponsors Meet our sponsors Meet our sponsors Bright Data: Bright Data is the leading web data infrastructure company, empowering over 20,000 organizations with ethical, scalable access to real-time public web information. From startups to industry leaders, we deliver the datasets that fuel AI innovation and real-world impact. Ready to unlock the web? Learn more at brightdata.com. Bright Data: Bright Data is the leading web data infrastructure company, empowering over 20,000 organizations with ethical, scalable access to real-time public web information. From startups to industry leaders, we deliver the datasets that fuel AI innovation and real-world impact. Ready to unlock the web? Learn more at brightdata.com. Bright Data: brightdata.com Neo4j: GraphRAG combines retrieval-augmented generation with graph-native context, allowing LLMs to reason over structured relationships instead of just documents. With Neo4j, you can build GraphRAG pipelines that connect your data and surface clearer insights. Learn more. Neo4j: GraphRAG combines retrieval-augmented generation with graph-native context, allowing LLMs to reason over structured relationships instead of just documents. With Neo4j, you can build GraphRAG pipelines that connect your data and surface clearer insights. Learn more. Neo4j: more Storyblok: Storyblok is a headless CMS built for developers who want clean architecture and full control. Structure your content once, connect it anywhere, and keep your front end truly independent. API-first. AI-ready. Framework-agnostic. Future-proof. Start for free. Storyblok: Storyblok is a headless CMS built for developers who want clean architecture and full control. Structure your content once, connect it anywhere, and keep your front end truly independent. API-first. AI-ready. Framework-agnostic. Future-proof. Start for free. Storyblok: Start for free . Algolia: Algolia provides a managed retrieval layer that lets developers quickly build web search and intelligent AI agents. Learn more. Algolia: Algolia provides a managed retrieval layer that lets developers quickly build web search and intelligent AI agents. Learn more. Algolia: Learn more

This story contains AI-generated text. The author has used AI either for research, to generate outlines, or write the text itself. 

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HatchIt Earns a 56 Proof of Usefulness Score by Building an AI Website Builder with Real Code Export

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