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AI Agentic Design Patterns with AutoGenvsFunctions, Tools and Agents with LangChain

Side-by-side comparison on level, duration, pricing, instructor, tier. Editor verdict on which course wins for which buyer.

DL.AI
DeepLearning.AI

AI Agentic Design Patterns with AutoGen

AutoGen takes a different angle than LangGraph and crewAI — agents talk to each other in structured conversations rather than executing a state graph. The course teaches the four design patterns (reflection, tool use, planning, multi-agent collaboration) at a conceptual level you'll find useful even if you never ship AutoGen. Take it for the patterns, not necessarily for the framework.

DL.AI
DeepLearning.AI

Functions, Tools and Agents with LangChain

The middle-of-the-curriculum short course bridging from prompt patterns to full agent loops. Covers OpenAI function calling, LangChain tools, OutputParsers, and the conversational-agent loop. Free, 90 minutes, taught by Harrison Chase. Take this after the LangChain for LLM App Development short course and before the LangGraph one — they form the canonical 3-course LangChain sequence.

Side-by-side

DimensionAI Agentic Design Patterns with AutoGenFunctions, Tools and Agents with LangChain
ProviderDeepLearning.AIDeepLearning.AI
Editorial tierCuratedHands-on reviewed
LevelIntermediateIntermediate
Formatself pacedself paced
Duration~1.5 hours~1.5 hours (5 lessons)
PricingFreeFree
InstructorChi Wang & Qingyun Wu — Co-creators of AutoGen, Microsoft ResearchHarrison Chase — Founder, LangChain
RatingNo public ratingNo public rating
Topicsbuild ai agents, ai engineeringlangchain, build ai agents, prompt engineering
Last verified2026-05-242026-05-24

Pros & cons

AI Agentic Design Patterns with AutoGen
Pros
  • +Concept-first teaching — the patterns transfer to any agent framework
  • +Free, ~90 minutes, taught by the framework creators
  • +Microsoft-backed — more production-ready than crewAI in regulated environments
Cons
  • −AutoGen has less community momentum in 2026 than LangGraph
  • −Conversational pattern feels heavier than role-based or graph-based alternatives
Functions, Tools and Agents with LangChain
Pros
  • +By LangChain's founder — most authoritative source possible
  • +Bridges the gap between API-level prompting and full agentic loops
  • +Free, 90 minutes, fits in a single sitting
Cons
  • −Assumes prior LangChain basics — not a starting point
  • −Function-calling examples are OpenAI-flavored; patterns transfer to Anthropic

Which course is for whom?

AI Agentic Design Patterns with AutoGen
Best for
  • · Engineers wanting the conceptual map of agentic design patterns
  • · Microsoft-stack teams considering AutoGen for production
Not ideal for
  • · Anyone deciding "which framework to commit to" — start with LangGraph or crewAI first
Functions, Tools and Agents with LangChain
Best for
  • · Engineers shipping their first LLM-with-tools app
  • · Anyone in the middle of the LangChain learning path
Not ideal for
  • · Complete beginners — start with LangChain for LLM App Development first

Editor's short verdict

These cover different primary topics — AI Agentic Design Patterns with AutoGen focuses on build ai agents while Functions, Tools and Agents with LangChain focuses on langchain. Take the one matching your current goal first; the other can come later if your interests expand.

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AI Agentic Design Patterns with AutoGen vs Functions, Tools and Agents with LangChain (2026): which course wins? · AI Agent Rank