Top 13 'Boilerplate-Busting' AI Tools to try for developers building new applications from scratch in 2025 - Goh Ling Yong
As developers, we live for the spark of a new idea. That "aha!" moment when a concept for a new application clicks into place is exhilarating. But what comes next? Often, it's not the exciting core logic or the innovative features. It's the boilerplate. It's setting up the project structure, configuring the linter, writing the basic Express server, creating the React component files, and wiring up the initial API endpoints. It's the necessary, repetitive, and frankly, soul-crushing setup that stands between you and the fun part.
For years, we've relied on project starters and CLIs like create-react-app to ease this pain. They've been a great help, but they're static. They give you a one-size-fits-all solution. But what if you could describe your exact needs—your preferred stack, your data models, your initial UI layout—and have the foundation built for you instantly? This is no longer science fiction. As we head into 2025, AI-powered tools are fundamentally changing how we approach the "blank canvas," transforming hours of tedious setup into minutes of creative direction.
Here on the Goh Ling Yong blog, we're always exploring tools that boost developer productivity. This post is dedicated to the "boilerplate busters"—the AI assistants, code generators, and smart environments that automate the mundane, letting you jump straight to building what makes your application unique. These aren't just about autocompleting a line of code; they're about scaffolding entire features, generating robust test suites, and even architecting systems from a simple prompt. Let's dive into the top 13 AI tools you should have in your arsenal for your next project.
1. GitHub Copilot Chat & Enterprise
We have to start with the one that brought AI code assistance into the mainstream. GitHub Copilot is no longer just a fancy autocomplete. With the integration of GPT-4 and the rise of Copilot Chat, it has become an indispensable partner for project initialization. It lives right in your VS Code (or other JetBrains IDEs) and has a deep understanding of your entire workspace.
Instead of just suggesting the next line, you can now use the chat interface to scaffold entire files and directories. Need a full CRUD setup for a new model in your Node.js API? Just ask. Need a boilerplate Dockerfile and docker-compose.yml for your MERN stack application? Describe it, and Copilot will generate it. Its strength lies in its tight integration with your IDE and its access to the vast knowledge of GitHub's public repositories.
- Pro Tip: Use the
@workspacecommand in Copilot Chat to ask questions or generate code based on the context of your entire project. For example:@workspace create a new React component that uses the same styling conventions as my existing 'Button.tsx' component.
2. v0 by Vercel
Frontend boilerplate is notoriously repetitive. How many times have you created a container div, a flex layout, and a set of cards? v0 by Vercel is a generative UI tool that aims to eliminate this forever. You describe the interface you want in plain English, and it generates the React component code using high-quality, production-ready components built with Tailwind CSS and shadcn/ui.
The magic of v0 is its iterative nature. You can ask for a component, see the result, and then provide feedback to refine it: "Make the buttons blue," "Add a third column," "Use a different icon for the delete action." It's like having a senior frontend developer pair-programming with you on the UI. This is perfect for quickly building out user dashboards, settings pages, and marketing sites, which are often 90% boilerplate UI patterns.
- Example Prompt: "A pricing page with three tiers: Free, Pro, and Enterprise. Each tier should show the price, a list of features with checkmarks, and a call-to-action button. The Pro tier should be highlighted as the most popular."
3. Cursor
While Copilot is a plugin, Cursor is an entire IDE built from the ground up with AI at its core. It's a fork of VS Code, so the experience is familiar, but the AI capabilities are on another level. Cursor allows you to highlight a block of code and prompt changes, debug errors with AI assistance, and, most importantly for our topic, generate entire codebases.
Its "New from Scratch" feature lets you lay out a comprehensive plan for a new application. You can instruct it to create a full-stack app with a specific framework, define the API endpoints, and outline the frontend components. Cursor will then generate the entire file structure and fill it with sensible boilerplate code. It's the closest thing we have to saying, "Computer, build me a social media app for pet owners," and getting a working foundation.
- Pro Tip: Use Cursor's "Codebase Chat" to get a high-level understanding of the code it just generated. Ask it questions like, "Where is the database connection configured?" or "Explain the authentication flow you've created."
4. FigJam AI
Boilerplate isn't just about code; it's also about the planning and architecture that come before it. FigJam AI, from the creators of Figma, helps automate the "diagramming boilerplate." Instead of manually dragging and dropping shapes to create a user flow or a system architecture diagram, you can just describe it.
This is a game-changer for the initial brainstorming phase of a new project. You can instantly generate flowcharts to map out user journeys, mind maps to organize features, and sequence diagrams to plan API interactions. Getting your architecture right from the start saves countless hours of refactoring later, and FigJam AI makes that initial step faster and more collaborative.
- Example Prompt: "Create a sequence diagram for a user signup process that includes the client, an API gateway, an authentication service, and a user database."
5. CodiumAI
Testing is critical, but writing test boilerplate is a drag. Setting up mocks, writing simple "does it render" tests, and covering all the edge cases for a simple utility function can take more time than writing the function itself. CodiumAI is an AI-powered test-generation tool that integrates with your IDE to solve this exact problem.
It analyzes your code—from individual functions to entire classes—and automatically generates a comprehensive suite of meaningful tests. It doesn't just check for happy paths; it actively tries to find edge cases and potential bugs. By automating the creation of your initial test files and common test cases, CodiumAI ensures your new project starts with a strong foundation of quality and reliability from day one.
- Pro Tip: After generating tests for a function, review them not just as tests, but as documentation. CodiumAI's tests often reveal how your code behaves in unexpected scenarios, giving you deeper insight into your own logic.
6. Tabnine
Tabnine is another major player in the AI code completion space and a powerful alternative to GitHub Copilot. While its core function is similar, Tabnine has carved out a niche by focusing on personalization and privacy. It can be trained on your specific repositories, allowing it to learn your team's coding style, conventions, and custom libraries.
For developers starting a new project within an existing organization, this is huge. Tabnine will generate boilerplate that already conforms to your company's standards. Furthermore, it offers self-hosting options, which is a critical feature for companies with strict security and privacy requirements. Its goal is to provide completions and code generation that feel uniquely tailored to your environment.
- Pro Tip: Connect Tabnine to your organization's GitHub, GitLab, or Bitbucket repositories. The more context it has about your existing projects, the more accurate and relevant its boilerplate suggestions will be for your new application.
7. MutableAI
MutableAI positions itself as an "AI-accelerated development" platform. It goes beyond simple code generation to understand the context of your entire project and help you build features faster. As my colleague Goh Ling Yong and I were discussing, the next frontier for these tools is moving from line-level suggestions to feature-level implementation, and MutableAI is a great example of this.
When starting a new project, you can use it to create a "production-quality backend in a minute." It helps you define your data models and then generates corresponding API endpoints, services, and database schemas. It also excels at refactoring and improving existing code, making it a valuable partner throughout the development lifecycle, not just at the beginning.
- Pro Tip: Use MutableAI's "AI-Code-Style" feature to automatically enforce consistent styling across your newly generated boilerplate. This ensures that all the AI-generated code looks and feels like it was written by a single, meticulous developer.
8. Mintlify Writer
Let's be honest: writing documentation is the one piece of boilerplate that almost every developer dreads. It's tedious, and it's easy to let it fall out of date. Mintlify Writer is a brilliant tool that tackles this head-on by automating the creation of your project's documentation.
It scans your code, understands what your functions and classes do, and generates clear, concise explanations for them. It can create everything from JSDoc-style comments to full-blown documentation websites. Starting a project with good documentation practices is crucial for long-term maintainability, and Mintlify makes it so easy that there's no excuse not to.
- Pro Tip: Integrate Mintlify into your CI/CD pipeline to automatically check for undocumented code. This creates a quality gate that ensures your documentation keeps pace with your development from the very first commit.
9. Warp
The terminal is where so much of the initial project setup happens: running CLI commands, initializing git repositories, installing dependencies. Warp is a modern, Rust-based terminal that supercharges this experience with AI. Its AI Command Search feature lets you describe what you want to do in natural language, and it will suggest the correct shell command.
No more googling "how to find all files larger than 10MB" or "git command to squash last 3 commits." Beyond just search, you can use Warp AI to debug error messages or create complex, multi-step workflows. This drastically lowers the cognitive load of project setup, especially when working with unfamiliar tools or CLIs.
- Example Prompt: Instead of trying to remember the
npxcommand, you can just type:# create a new Next.js project with TypeScript named my-app. Warp will translate this intonpx create-next-app@latest my-app --typescript.
10. Phind
How much time do you spend on Stack Overflow or sifting through blog posts to figure out how to configure a new library or set up a specific authentication strategy? Phind is an AI search engine built specifically for developers that aims to eliminate this "research boilerplate."
When you ask Phind a question, it doesn't just give you a list of links. It provides a direct answer, complete with code examples, synthesized from multiple sources across the web. It's incredibly fast and accurate for questions related to project setup, framework configuration, and library usage. It’s like having a senior developer on call who can instantly give you the "right" way to do something.
- Example Prompt: "How to set up a basic Express.js server with TypeScript, ESLint, and Prettier from scratch." Phind will provide a step-by-step guide with all the necessary commands and configuration files.
11. GPT-Engineer
This open-source tool takes the idea of project scaffolding to its logical conclusion. GPT-Engineer lets you specify what you want to build in a prompt file, and it generates an entire codebase to meet those specifications. It's designed to be highly collaborative and adaptable.
You start by writing your core requirements in a prompt file. Then, you can provide it with identity files (e.g., "I'm a developer who prefers functional programming and uses TypeScript") and even give it access to existing files for context. It then thinks through the problem, clarifies questions, and generates the complete project structure. It's an incredibly powerful way to go from a detailed idea to a working prototype in minutes.
- Pro Tip: Be as specific as possible in your initial prompt file. Don't just say "build a to-do app." Say "build a to-do app using React and Zustand for state management, with a Node/Express backend and a PostgreSQL database. The API should have endpoints for creating, reading, updating, and deleting tasks."
12. Postman (with Postbot)
For backend developers, a significant amount of boilerplate involves creating and testing API endpoints. Postman has long been the tool of choice for this, and its AI assistant, Postbot, makes it even more powerful. Postbot can automate the most tedious parts of API development.
Right after you've created a new endpoint, you can ask Postbot to write tests for it. It will generate scripts to check for successful status codes, validate response schemas, and test for error conditions. It can also automatically generate API documentation and even help you visualize complex JSON responses. This is a massive time-saver when building out the initial API for a new application.
- Pro Tip: Use Postbot to create a full test suite for a new collection. Point it at your API's base URL and ask it to "Add tests for all requests in this collection." It will intelligently generate relevant tests for each endpoint.
13. Replicate
As more applications in 2025 are built with AI features at their core, a new kind of boilerplate has emerged: "ML-ops boilerplate." Setting up the infrastructure to run and scale machine learning models is complex and time-consuming. Replicate is a platform that allows you to run open-source AI models with a simple API call, completely removing the need for this infrastructure setup.
Want to add image generation, audio transcription, or language translation to your new app? With Replicate, you can find a pre-trained model and integrate it in minutes instead of spending weeks configuring GPUs and Python environments. It allows you to focus on your application's unique features, treating powerful AI models as just another API.
- Pro Tip: Browse the Replicate "collections" to get ideas for AI features you can add to your app. You might discover a model for image restoration or music generation that could become a cornerstone of your new project, all without the heavy lifting of ML infrastructure.
The Future is Augmentation, Not Replacement
The rise of these powerful AI tools isn't about making developers obsolete. It's about eliminating the friction that slows us down. The hours we used to spend on repetitive setup, configuration, and boilerplate can now be spent on what truly matters: solving complex problems, designing elegant architectures, and creating delightful user experiences.
By embracing these "boilerplate-busters," we can move faster, build more robust applications, and, most importantly, spend more time doing the creative work we love. The blank canvas is no longer intimidating; it's an invitation to create, with an entire suite of AI assistants ready to handle the heavy lifting.
What are your go-to AI tools for starting a new project? Did I miss any essential boilerplate busters you think will be huge in 2025? Share your favorites in the comments below!
About the Author
Goh Ling Yong is a content creator and digital strategist sharing insights across various topics. Connect and follow for more content:
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