Build and deploy apps in minutes
with Bolt
We use Bolt.new by StackBlitz to prototype and ship full-stack web apps at unprecedented speed, AI-generated code, instant browser preview, and one-click deployment. From idea to live URL in minutes.
The best tool for
ai coding / app builder
Bolt.new is an AI-powered full-stack development environment by StackBlitz. It runs entirely in the browser, AI writes and executes code in real time, giving you a working app you can deploy instantly without any local setup.
What we build with Bolt
From MVPs to enterprise platforms, here's how we use Bolt to ship faster.
Rapid Prototyping
From idea to working prototype in under an hour, AI writes the code, you validate the concept.
Full-Stack MVPs
React frontends with Node.js backends, deployed and live, without a local dev environment.
Landing Pages
High-converting landing pages with interactive elements, built and deployed in minutes.
Hackathon Projects
Ship a working, deployable product in the time others spend setting up their environment.
Certified Bolt experts
We don't just use Bolt, we master it. Our team is certified and has shipped dozens of projects with it.
Apps delivered
We've shipped over 50 production apps using Bolt and the broader no-code stack, from seed-stage MVPs to enterprise platforms.
Faster delivery
Bolt lets us build in weeks what traditional dev teams take months to deliver, giving you a decisive speed advantage.
Fixed pricing
Every project comes with a clear scope, fixed price, and weekly demos. No surprises, no scope creep, just results.
Tools we combine with Bolt
We integrate Bolt with the best tools in the no-code ecosystem for end-to-end solutions.
The Complete Guide to Bolt Development
Bolt.new is an AI-powered full-stack development environment that runs entirely in the browser, letting you build, preview, and deploy applications without any local setup.
Bolt.new's Stack: React, Vite, and What That Means for You
Bolt.new is built on StackBlitz's WebContainers technology, which runs a complete Node.js environment directly in the browser. There is no server receiving your code, no VM being spun up, and no local machine doing the work. Your entire development environment, the package manager, the build tool, the development server, runs in browser memory. This is the technical magic that enables Bolt's zero-setup, instant-preview experience. The default generated stack is React with Vite and TypeScript. Vite's fast hot module replacement means you see changes in the preview instantly as the AI writes code. TypeScript provides type safety in the generated code, which is especially important when you are inheriting AI-generated code you did not write line by line. Tailwind CSS is the standard styling choice, and Bolt typically uses shadcn/ui or similar component libraries for pre-built UI elements. Understanding this stack matters for what happens after Bolt. When you export or deploy a Bolt project, you are getting a standard Vite + React application, not a proprietary format. Any frontend developer can open the exported code, install dependencies with npm, and run it locally. The code is not locked into Bolt's infrastructure. This is a meaningful advantage over no-code tools where the output is a database configuration rather than portable code.
Prompting Bolt for Production-Ready Apps
Bolt's AI performs best with prompts that describe the full context upfront rather than iterating in small steps. Before generating any code, describe the complete scope of what you are building: the user flows, the data it needs to store, the pages it needs to have, and any specific technical requirements. A two-paragraph initial prompt that covers all of this produces far better initial code than a one-line description followed by twenty rounds of iteration. Be explicit about non-functional requirements. If you need authentication, say so in the first prompt and specify which provider, Supabase Auth, Clerk, or simple email-and-password. If you need the app to persist data, specify the database, Supabase is the most common choice with Bolt. If there are performance requirements or specific browser support targets, include them. The AI cannot infer these requirements from a description of features; they must be stated. For visual design, paste in a screenshot or describe a reference design explicitly. Bolt can read image attachments and will attempt to match the layout and visual style of a reference. This is dramatically more efficient than describing a UI in words. A Figma screenshot of your intended layout plus a description of the data model is the most powerful combination of inputs Bolt can receive. The resulting code may not be pixel-perfect, but it will be close enough that the remaining gap is a small editing task rather than a complete regeneration.
Bolt vs Lovable: Different Philosophies, Different Results
Bolt and Lovable are both AI code generators built on similar underlying models, but they represent different philosophies about what that tool should be. Bolt is a development environment first, it gives you a code editor, a terminal, a file system, and AI assistance all in one browser tab. The experience is closer to working in an IDE with a very capable AI pair programmer. Developers feel at home immediately. Lovable is a product builder first. The interface hides the code editor by default and focuses your attention on the running app. You describe what you want the product to do, and Lovable handles the implementation details. The experience is closer to working with a developer contractor, you give requirements, they produce output, you give feedback. Non-developers find Lovable more approachable because they do not have to interact with code at all. In practice, the outputs are similar in quality for common application patterns. The choice often comes down to the team's background. Technical founders and developers who want direct code access prefer Bolt. Non-technical founders and product managers who want to stay at the product level prefer Lovable. For agency work, the platform choice often depends on what the client will need to maintain after handoff, if they have a developer who will own the codebase, Bolt's git-exportable output is familiar. If they have no technical staff, Lovable's product-focused interface is more appropriate.
Exporting and Deploying Bolt Apps to Production
Bolt offers multiple paths to production. The simplest is direct deployment to Netlify from within the Bolt interface, one click, authentication with your Netlify account, and the app is live on a Netlify URL within seconds. This is sufficient for prototypes, demos, and early-stage projects. For custom domains, you configure the domain in Netlify after the initial deployment. For more control over your deployment infrastructure, Bolt can push the project to a GitHub repository. Once in GitHub, you can deploy from there to any platform, Vercel, Netlify, Cloudflare Pages, Railway, or a custom server. Connecting GitHub to Vercel or Netlify creates a CI/CD pipeline automatically: every push to the main branch triggers a new deployment. This is the production-grade setup for apps that will be actively maintained and updated. Environment variables need careful handling during export. API keys, database credentials, and service URLs that were configured in Bolt's environment must be recreated in your target deployment platform. Never hardcode secrets in the codebase, always use environment variables. Review the exported code for any hardcoded credentials before pushing to a public GitHub repository. Bolt does not automatically prevent this, so the responsibility is yours. Setting up environment variables correctly in Vercel or Netlify before the first production deployment is the single most important operational step.
Common Bolt Limitations and How to Work Around Them
Bolt's browser-based execution model has real resource constraints. Complex applications with many dependencies can be slow to initialize or run into memory limits in the WebContainers environment. If you notice the environment becoming sluggish or packages failing to install, this is usually the cause. The workaround is to export the project to a local development environment or GitHub and continue development there, using Bolt only for the AI generation steps. Context window limitations affect long coding sessions. As a Bolt project grows larger, the AI has to fit more of the codebase into its context to make accurate edits. Past a certain project size, the AI begins making edits that conflict with other parts of the codebase or miss dependencies. The mitigation is to export to GitHub and use a local AI coding tool like Cursor or Claude Code for continued development once the project reaches significant complexity. Bolt is best for the early, fast-moving phases of a project. Backend capabilities are limited compared to a full server environment. Bolt can generate Node.js backend code, but complex server-side operations, long-running processes, background jobs, file processing, are not well-suited to Bolt's serverless deployment target. For apps that need a robust backend, the recommended approach is to use Bolt for the frontend and connect to a managed backend like Supabase for the database layer and n8n or serverless functions for background processing. Mixing Bolt's frontend generation with external backend services is the pattern that scales most reliably.
When to Hand Off a Bolt Prototype to a No-Code Agency
Bolt excels at producing a working prototype rapidly, but there is a well-defined point at which continuing to develop in Bolt becomes counterproductive. The clearest signal is when the effort to prompt Bolt to make a change equals or exceeds the effort a developer would take to make that change manually in the codebase. At that point, Bolt is adding friction rather than removing it, and a different development model is more appropriate. Handoff to a no-code agency makes sense when the prototype has validated the concept but the production version needs capabilities beyond what Bolt can cleanly generate, complex user permissions, deep third-party integrations, custom design systems, or a backend that scales beyond Supabase's free tier. An experienced no-code agency can take a Bolt prototype as a reference for the UX and requirements, then rebuild it on a more appropriate stack (WeWeb, Bubble, or a hybrid) with production-grade architecture from the start. For founders using Bolt to build an MVP for fundraising or early customers, the handoff conversation should happen before the prototype is in front of serious users who will stress-test it. A Bolt prototype that goes viral before it is production-ready creates a race condition between traction and technical debt. Engaging an agency to either harden the Bolt codebase or rebuild it properly before that moment avoids the painful scenario of having to tell users that the app is down while you refactor it. The prototype phase is for learning; the agency phase is for scaling.
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