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Agent Foundations and LangChain Basics
What an AI agent actually is (vs chains, vs workflows); the LangChain ecosystem in 2026 (LCEL, Hub, Smith); building your first chains with LCEL; tools, toolkits, and tool calling.
Module Content
What an AI Agent Actually Is
A practical definition. Strip away the hype: agents are LLMs that decide what to do next. FIND_VIDEO: search 'what is an AI agent definition explained' — recommended channel: LangChain / AI Engineer / Harrison Chase. Aim for 10 min or under.
Recap — Agents vs Chains vs Workflows
The terminology is muddy. Here's the distinction that actually matters when you're building.
LangChain in 2026 — What's Changed, What's Stable
LangChain has evolved fast. Here's what's current, what's deprecated, and where to put your effort. FIND_VIDEO: search 'langchain 2026 LCEL latest version' — recommended channel: LangChain / Sam Witteveen / James Briggs. Aim for 11 min or under.
Recap — The LangChain Ecosystem (LCEL, Hub, Smith)
LangChain isn't just one library. The ecosystem has four pieces; you'll use all of them.
Building Your First Chain with LCEL
The pipe-based composition pattern. Once you see it, every LangChain example becomes readable. FIND_VIDEO: search 'LCEL LangChain Expression Language tutorial' — recommended channel: LangChain / Sam Witteveen. Aim for 10 min or under.
Recap — LCEL Patterns You'll Use Constantly
Five LCEL patterns cover 90% of chain-building. Master them; everything else is variations.
Tools, Toolkits, and Tool Calling in LangChain
The @tool decorator and bind_tools API. The foundation for agentic behavior in LangChain. FIND_VIDEO: search 'langchain tools tool calling tutorial' — recommended channel: LangChain / Sam Witteveen / Greg Kamradt. Aim for 11 min or under.
Recap — Designing Tools for Agent Use
Tools turn LLMs into action-takers. Design them well — the LLM decides which to call based on the descriptions.