React + Tailwind + TypeScript for AI-First Development

We're witnessing a fundamental shift in how applications are built. AI code generation has evolved from a novelty to a productivity multiplier that's become too significant to ignore. While AI models still require oversight for production backend systems, they excel at generating frontend UIs—compressing development timelines that once took months into days.

The Rise of Vibe Coding​

AI can now generate complete, production-ready UI code. This enables an entirely new development workflow that Andrej Karpathy has termed "Vibe Coding"—where developers iteratively guide AI agents to implement features through natural language instructions, where features can be iteratively prototyped, refined and improved within seconds instead of hours.

This AI-first approach is rapidly maturing, with tools like Cursor, Claude Code, and Codex becoming the preferred platforms for this new paradigm with new tools designed to get maximum effectiveness of AI models with sophisticated planning tools, focused models optimized for code generation and edits and agentic workflows that's able to solidifying each new feature iteration with tests, along with detailed documentation, planning, migrations and usage guides.

React & Tailwind: The AI Development Standard​

React and Tailwind have emerged as the de facto standards for AI-generated UIs. Every major platform for generating applications from prompts has converged on this stack including Replit, Lovable, Google's AI Studio, Vercel's v0 and Claude Code Web.

TypeScript​

Whilst TypeScript is often excluded in one-prompt solutions catering to non-developers, it's still a critical part of the AI development workflow. It provides a type system that helps AI models generate more accurate and maintainable code and TypeScript's static analysis also helps identify errors in the generated code which AI Models have have become really good at correcting—as such it's an integral part in all our React templates.

How ServiceStack Excels in AI-First Development​

Context is king when developing with AI models. The better the context, the higher the quality of generated code and ServiceStack's architecture is uniquely suited for AI-assisted development:

Declarative Typed APIs​

All ServiceStack APIs follow a flat, declarative structure—The contract is explicit and consistent and LLMs don't need to guess what APIs accept or return.

End-to-End Type Safety​

Context quality directly impacts generated code quality. ServiceStack's TypeScript integration provides complete static analysis of what APIs accept, return, and how to bind responses—giving AI models the full context they need. The static analysis feedback also directs models to identify and correct any errors in the generated code.

Zero-Ambiguity Integration​

AI models thrive on consistency. ServiceStack removes guesswork with a single pattern for all API calls:

• One generic JsonServiceClient for all APIs
• Consistent methods used to send all requests
• Consistent Typed Request DTO → Response DTO flow
• Uniform error handling

Intuitive Project Structure​

ServiceStack's physical project structure provides clear separation of concerns, with the entire API surface area contained in the ServiceModel project—making codebases easy for AI models to navigate and understand.

Minimal Code Surface​

Less code means fewer opportunities for errors. ServiceStack's high-productivity features minimize the code AI needs to generate:

• AutoQuery APIs - Flexible, queryable APIs defined with just a Request DTO
• AutoQueryGrid Component - Complete CRUD UIs in 1 line of code
• Auto Form Components - Beautiful, validation-bound forms in 1 line of code

These components are ideal for rapidly building backend management interfaces, freeing developers to focus on differentiating customer-facing features.

Modern React Project Templates​

We're introducing three production-ready React templates, each optimized for different use cases:

Comprehensive React Component Library​

All three templates leverage our new React Component Gallery—a high-fidelity port of our proven Vue Component Library and Blazor Component Library. This comprehensive collection provides everything needed to build highly productive, modern and responsive web applications.

This is enough to generate a complete CRUD UI to manage Bookings in your React App with the React AutoQueryGrid Component. or with ServiceStack's built-in Locode UI:

This will generate an empty MyApp.ServiceModel/<Table>.d.ts file along with stub AutoQuery APIs and DB Migration implementations.

Regenerate AutoQuery APIs and DB Migrations​

After modifying the TypeScript Data Model to include the desired fields, you can re-run the okai tool to generate the AutoQuery APIs and DB Migrations (which can be run anywhere within your Solution):

After you're happy with your Data Model you can run DB Migrations to run the DB Migration and create your RDBMS Table:

Making changes after first migration​

If you want to make further changes to your Data Model, you can re-run the okai tool to update the AutoQuery APIs and DB Migrations, then run the rerun:last npm script to drop and re-run the last migration:

Removing a Data Model and all generated code​

If you changed your mind and want to get rid of the RDBMS Table you can revert the last migration:

Which will drop the table and then you can get rid of the AutoQuery APIs, DB Migrations and TypeScript Data model with:

AI-First Example​

There are a number of options for starting with an AI generated Application, with all the Instant AI App Generators like Google's App Studio able to provide a great starting point. Although currently Professional Developers tend to use Cursor, Claude Code or Codex as their day-to-day tools of choice.

Use GitHub Copilot when creating a new Repository​

If you're using GitHub Copilot you can also use it to generate a new App from the Vite React template :

- React 19, TypeScript, TailwindCSS v4
- Persistence in IndexedDB/localStorage
- Recharts
- Vitest with React Testing Library

## Features
Dashboard
- Overview of total income, expenses, and remaining budget
- Monthly summary chart (line graph)
- Expense categories (pie chart)

Transactions
- Add/Edit/Delete income or expenses
- Date filtering/sorting

Budgets
- Set monthly budget goals per category
- Progress bars for spending vs. budget

Reports
- View past months
- Export

Implement Category Auto-Tagging

Allow specifying tags when creating a new transaction.
When users add a transaction, try to predict the tag from the Description, e.g:

Input: “Starbucks latte” → Suggests category: Food & Drinks
Input: “Uber to work” → Suggests category: Transport

Implementation:

Maintain a small local list of common keywords + categories.
Pre-fill category in the transaction form as the user types in the Description.