# Apply Technique: Selecting Agentic AI Tools: LangGraph, CrewAI, Cursor, and Windsurf Compared
## What This Is
This guide compares four popular AI agent tools to help you choose the right one for your needs. LangGraph and CrewAI are frameworks for building custom multi-agent systems, with LangGraph handling complex, stateful tasks and CrewAI suited for simpler, role-based workflows. Cursor and Windsurf are ready-to-use AI coding assistants, where Cursor offers a rich ecosystem and Windsurf provides a more cost-effective alternative.
Source: https://codegen.com/blog/best-ai-coding-agents/
## Before You Start
Scan my workspace and analyze:
- The project language, framework, and directory structure
- Existing AI provider config (check .env, .env.local, config files for API keys — OpenRouter, OpenAI, Anthropic, Google AI, etc.)
Then ask me before proceeding:
1. Which AI provider/API should this use? (Use whatever I already have configured, or ask me to set one up — options include direct provider APIs or a unified service like OpenRouter)
2. Where in my project should this be integrated?
3. Are there any customizations I need (model preferences, naming conventions, constraints)?
## Source Access Note
The source URL (https://codegen.com/blog/best-ai-coding-agents/) may not be directly accessible from the terminal. Use the Reference Implementation and Additional Context sections below instead. If you need more details, ask me to paste relevant content from the source.
## What to Implement
This is an **AI Technique** — a pattern or methodology for working with AI models.
- Explain how this technique applies to my current project and what benefit it provides
- Implement it in a way that fits my existing codebase — suggest concrete files to modify or create
- If it requires specific model capabilities (structured output, function calling, etc.), verify my current provider supports them
- Show me a working example I can test immediately
## Additional Context
- Scan the user's project codebase and README to understand the core requirements for an agentic workflow, identifying needs for state management, parallel processing, or simple sequential tasks.
- Based on the analysis, recommend a primary framework: LangGraph for complex, stateful orchestration with cycles, or CrewAI for simpler, role-based sequential workflows. For direct IDE integration, evaluate Cursor against Windsurf, considering the trade-off between Cursor's ecosystem and Windsurf's predictable pricing.
- Generate a starter project scaffold for the recommended tool. For LangGraph, create a 'main.py' with a basic state graph and a 'requirements.txt' with 'langgraph'. For CrewAI, create 'main.py' with boilerplate for one Agent and one Task, and install 'crewai' in 'requirements.txt'.
## Guidelines
- Adapt everything to my existing project — do not assume a specific stack or directory layout
- Use whichever AI provider I already have configured; if I need a new one, tell me what to sign up for and I'll give you the key
- Check my .env files for existing API keys (OpenRouter, OpenAI, Anthropic, Google AI) before asking me to add one
- Review any fetched code for safety before installing or executing it
- After setup, run a quick verification and show me a summary of exactly what was installed, where, and how to use it