Download. Start. Point Claude at it. Ship features that actually work.
Most boilerplates fail with AI agents. The AI generates code that doesn't fit, types that don't match, patterns that conflict. You spend more time fixing than building.
AgentReady Stack is different. It's architected from the ground up for AI-assisted development:
1. Download the stack
2. Run `pnpm dev`
3. Point your AI agent at the codebase
4. Describe the feature you want
5. AI writes code that follows the architecture
6. Tests verify it works
7. Ship itThe secret is two things working together:
When the agent reads your codebase, it learns from both the documentation and the working examples. "Build something like the organizations module" actually works because there's a complete organizations module to learn from.
| Problem with typical codebases | How AgentReady Stack solves it |
|---|---|
| AI doesn't know where code belongs | Clear module structure with explicit patterns |
| AI creates duplicate types | Single source of truth with code generation |
| AI ignores your patterns | AGENTS.md documents every pattern explicitly |
| AI-generated code breaks tests | Test patterns included, AI follows them |
| AI fights your architecture | Architecture is AI-readable by design |
| Layer | Technology | Why It Works with AI |
|---|---|---|
| Backend | NestJS | Decorator patterns are explicit and learnable |
| Frontend | React Router v7 | Loaders/actions have clear boundaries |
| CLI | Oclif | Command structure is predictable |
| Database | MongoDB + MikroORM | Schema in code, not hidden in migrations |
| Types | OpenAPI + Orval | Generated client = zero type drift |
You're not starting from zero. These features are production-ready:
Your AI agent can study these implementations and extend them. Want to add a new feature? Point your agent at the organizations module and say "build something similar for projects."
The monorepo architecture means you're not locked into one frontend. Need an admin dashboard? Add apps/admin. Building a mobile app? Add apps/mobile with React Native—it imports from the same @platform/api-client. Your proven auth, organizations, and API all work across every new app you add.
One payment. Lifetime access. Ship unlimited products.
Skip weeks of setup. Start prompting your AI agent today.
Two things work together: AGENTS.md explains the architecture, patterns, and conventions. The production-ready code (auth, organizations, CLI) provides working examples to learn from. When you prompt your AI agent to "build something like the organizations module," it reads the documentation and studies the actual implementation.
Yes. AgentReady Stack works with Claude, Claude Code, Cursor, GitHub Copilot, ChatGPT, and any AI that can read context files. The patterns are explicit enough that any capable AI can follow them.
You should be comfortable with TypeScript. You don't need to be an expert—the AI handles much of the complexity—but you should understand async/await, types, and REST APIs.
React Router v7's loader/action pattern creates clear boundaries that AI agents understand well. Next.js blurs client/server lines in ways that confuse AI (and many developers). The explicit patterns mean fewer hallucinations.
With the right architecture, yes. The key is giving AI clear patterns to follow and tests to verify the output. AgentReady Stack provides both. You still review the code—but you're reviewing working code, not debugging broken code.
Yes. Lifetime access includes all future updates. As AI tools evolve, we update the guidance. Buy once, receive updates as soon as they're available.