Key takeaways
- YC-backed (W24) with 33K GitHub stars on GPT Pilot — pioneered multi-agent approach with specialized roles
- 14 specialized agents handle planning through deployment — Architect, Tech Lead, Developer, Debugger, etc.
- VS Code/Cursor extension is primary product now — open source repo archived in favor of commercial platform
FAQ
What is Pythagora?
Pythagora is an AI development platform with 14 specialized agents that handle planning, coding, debugging, and deployment of full-stack web apps.
What is the difference between Pythagora and GPT Pilot?
GPT Pilot is the open-source project (now archived). Pythagora is the commercial platform built on that technology with VS Code/Cursor integration.
What tech stack does Pythagora support?
React frontend with Node.js backend and database integration. Everything runs on AWS infrastructure. Python support is coming.
How much does Pythagora cost?
Free tier available. Pro and Premium plans start at $49/month. Enterprise options available for larger teams.
Executive Summary
Pythagora is a Y Combinator-backed (W24) AI development platform built on the GPT Pilot open-source project.[1] With 33K+ GitHub stars, GPT Pilot pioneered the multi-agent approach using specialized roles (Architect, Developer, Debugger) that work together to build production-ready applications. The commercial platform now delivers this via VS Code and Cursor extensions.
| Attribute | Value |
|---|---|
| Company | Pythagora |
| Founded | 2023 |
| Funding | YC W24 |
| GitHub Stars | 33K+ (GPT Pilot) |
| Headquarters | N/A |
Product Overview
Pythagora positions itself as "the first all-in-one AI development platform" with 14 specialized agents handling everything from planning to deployment.[2] Unlike single-agent approaches, Pythagora mimics a real development team with distinct roles.
The platform runs on top-tier language models from OpenAI, Anthropic, and others, accessible through VS Code or Cursor extensions.
Key Capabilities
| Capability | Description |
|---|---|
| 14 Specialized Agents | Each handles a distinct part of development |
| Security Layer | Built-in security analysis and fixes |
| Full-Stack Building | Frontend (React), Backend (Node.js), Database |
| One-Click Deployment | Deploy to AWS infrastructure |
| Live Dashboards | Generate dashboards from MongoDB, PostgreSQL, MySQL |
Agent Roles (from GPT Pilot)
| Agent | Role |
|---|---|
| Product Owner | (Joke: "like in real life, does nothing") |
| Specification Writer | Clarifies requirements via questions |
| Architect | Selects technologies, checks installations |
| Tech Lead | Breaks work into development tasks |
| Developer | Writes human-readable implementation plans |
| Code Monkey | Implements actual code changes |
| Reviewer | Reviews each step, sends back if wrong |
| Troubleshooter | Helps provide feedback when stuck |
| Debugger | Fixes issues when things go wrong |
| Technical Writer | Documents the project |
Technical Architecture
Pythagora's architecture is built around the key insight that AI can write most code (maybe 95%), but developers are still needed for the remaining 5%.[1] The system works step-by-step like a human developer, debugging as issues arise.
Key Technical Details
| Aspect | Detail |
|---|---|
| Deployment | VS Code/Cursor extension + AWS |
| Models | OpenAI, Anthropic, Groq, others |
| Stack | React frontend, Node.js backend |
| Infrastructure | AWS (dedicated or local) |
| Open Source | GPT Pilot archived; platform is commercial |
Differentiation from Other Tools
From GPT Pilot's README, comparing to Smol Developer and GPT Engineer:[1]
- Step-by-step development — Builds incrementally like a human, debugging as issues arise
- Scale capability — Not limited to simple apps; works at any codebase size
- Context filtering — Shows LLM only relevant code for current task, not entire codebase
Strengths
- Multi-agent architecture — Specialized roles mirror real development teams
- Step-by-step debugging — Catches and fixes bugs during development, not after
- YC backing — Credibility and network from Y Combinator
- Large community — 33K+ GitHub stars, active Discord
- Real debugging tools — Error logs, breakpoints, step-through debugging
- Full ownership — Complete code ownership, VS Code access, Git history, deploy anywhere
- Enterprise features — "Secure Spaces" for team and business security requirements[2]
Cautions
- GPT Pilot archived — Open source repo no longer maintained; commercial focus
- Limited tech stack — Only React/Node.js currently (Python coming)
- AWS lock-in — Deployment tied to AWS infrastructure
- New commercial product — Platform still maturing
- Unclear differentiation — Many competitors now offer similar multi-agent approaches
Pricing & Licensing
| Tier | Price | Includes |
|---|---|---|
| Free | $0 | Limited usage |
| Pro | $49/mo | More capacity |
| Premium | Custom | Higher limits |
| Enterprise | Custom | Team features |
Licensing model: Freemium SaaS with enterprise options
Hidden costs: LLM usage (OpenAI, Anthropic) billed separately or included in tiers
Competitive Positioning
Direct Competitors
| Competitor | Differentiation |
|---|---|
| Lovable | Both no-code app builders; Pythagora has IDE integration, Lovable is web-only |
| Bolt | Similar positioning; Pythagora emphasizes debugging tools |
| Devin (Cognition) | Devin is autonomous engineer; Pythagora is human-in-the-loop development platform |
| Tembo | Tembo orchestrates existing agents; Pythagora is its own integrated system |
When to Choose Pythagora Over Alternatives
- Choose Pythagora when: You want IDE integration (VS Code/Cursor) with specialized agents and real debugging tools
- Choose Lovable when: You prefer web-based no-code approach without IDE
- Choose Devin when: You want a fully autonomous agent for enterprise scale
- Choose Tembo when: You want to orchestrate multiple different agent tools
Ideal Customer Profile
Best fit:
- Full-stack developers building React/Node.js applications
- Teams wanting AI assistance with debugging capabilities
- VS Code/Cursor users seeking IDE-integrated AI development
- Developers who need to own their code and deploy anywhere
Poor fit:
- Teams using Python backend (support coming but not yet)
- Developers needing non-AWS deployment
- Organizations wanting fully autonomous agents without human oversight
- Enterprise requiring air-gapped deployment
Viability Assessment
| Factor | Assessment |
|---|---|
| Financial Health | Healthy — YC-backed with active development |
| Market Position | Challenger — Strong open source heritage, competing against well-funded rivals |
| Innovation Pace | Active — Regular updates, expanding tech stack |
| Community/Ecosystem | Large — 33K+ stars, active Discord |
| Long-term Outlook | Promising — Clear product vision, YC backing |
Pythagora has a strong foundation from GPT Pilot but faces stiff competition from well-funded rivals like Cognition (Devin), Bolt, and Lovable.
Bottom Line
Pythagora brings the multi-agent architecture of GPT Pilot to a polished commercial platform. The 14-agent approach with real debugging tools differentiates from simpler single-agent systems. However, the limited tech stack (React/Node.js only) and archived open-source repo may concern some users.
Recommended for: Full-stack developers building React/Node.js apps who want IDE integration with sophisticated debugging.
Not recommended for: Python developers, teams needing non-AWS deployment, or organizations requiring fully autonomous agents.
Outlook: Strong YC backing and large community provide a solid foundation. Success depends on expanding tech stack support and competing effectively against well-funded rivals.
Research by Ry Walker Research • methodology