Roadmap

AI Agent Developer Roadmap

A step-by-step guide to becoming an AI agent developer — frameworks, protocols, memory, sandboxing, observability, and deployment.

All-in-one document to learn AI agent development, stay updated, build real agents and more

A step-by-step guide to becoming an AI agent developer — the frameworks, protocols, memory systems, and infrastructure that separate a real production agent from a demo.

Roadmap (Things to Learn)

  • Biblography
  • Programming Languages & Foundations
  • LLM Providers & APIs
  • Agent Frameworks & SDKs
  • Tool Use, Function Calling & MCP
  • Browser Automation & Computer Use
  • Memory & Context Engineering
  • Vector Databases & RAG
  • Sandboxing & Execution Environments
  • Observability, Evals & Compliance
  • Deployment & Cost Management
  • Version Control

Projects & Preparation

YouTube learning

Core concepts from video walkthroughs:

Threads in the same domain as this chapter — go deeper on iHateReading without leaving the roadmap.

AI Agent cover

AI Agent

What agents are and how they differ from a single chat completion.

Agent harnessing: the part of building AI agents nobody talks about cover

Agent harnessing: the part of building AI agents nobody talks about

Loop, tools, memory, sandbox, and tracing live in your code — not the model weights.

Python AI agent SDKs in 2026: OpenAI vs Pydantic-AI vs smolagents vs Strands cover

Python AI agent SDKs in 2026: OpenAI vs Pydantic-AI vs smolagents vs Strands

Same three-tool agent in four frameworks — pick by execution model and testing needs.

Smallest AI Agent cover

Smallest AI Agent

Minimal file-reading agent to learn LLM tool loops without framework magic.

AI agent system that researches 100 blogs a day cover

AI agent system that researches 100 blogs a day

RSS, Reddit, YouTube transcripts, and URL hashing for a research pipeline.