Home/Agentic AI/Framework Selection/Introduction
←
Previous Module
Framework Comparison

Choosing the Right Framework

Learn how to select the perfect agentic AI framework for your project

Your Progress

0 / 5 completed
1
2
3
4
5

The Framework Selection Challenge

Choosing an agentic AI framework is one of the most critical decisions you'll make for your project. The wrong choice can lead to months of wasted effort, technical debt, and frustrated team members. The right choice accelerates development, reduces bugs, and sets you up for long-term success.

With dozens of frameworks available—from established options like LangChain and AutoGen to emerging tools like LangGraph and Haystack—how do you know which one fits your needs? Should you use an existing framework or build custom? What factors should guide your decision?

This module teaches you a systematic approach to framework selection. You'll learn to evaluate frameworks based on your project requirements, team capabilities, ecosystem maturity, and business constraints.

🎯 What You'll Learn

  • ✓A structured decision framework for evaluating frameworks
  • ✓How to assess framework maturity and ecosystem health
  • ✓Cost-benefit analysis of custom vs existing frameworks
  • ✓Real-world decision criteria and trade-offs

Interactive: Key Decision Factors

Select a decision factor to explore critical questions you should ask before choosing a framework:

Project Requirements

Start with what you need to build, not what tools exist.

Critical Questions:
1

What type of agent are you building? (RAG, multi-agent, code generation, search)

2

What level of control do you need over agent behavior?

3

Do you need real-time streaming or batch processing?

4

What are your scalability requirements?

💡 The Golden Rule

Start with requirements, not frameworks. Many developers make the mistake of choosing a popular framework first, then forcing their use case to fit. Instead, define your requirements clearly, then evaluate which framework best matches those needs. Remember: no single framework is "best" for all use cases.