Agent Builder- Build Agents with Langchain

What is Agent Builder?

A 6-week intensive program where you go from writing Python scripts to building, deploying, and monitoring multi-agent AI systems that run in production. Not theory. Not demos. Real systems.

What you'll actually learn:

You start where it matters - the orchestration layer. LangGraph teaches you how agents actually work under the hood: state management, graph execution, persistence, streaming, and human-in-the-loop patterns. Most courses skip this. We don't.

Then you move to LangChain v1.0 - the latest agent framework built on top of LangGraph. You'll build agents with tools, middleware, guardrails, RAG pipelines, structured output, long-term memory, and multi-agent coordination. You'll integrate external services through the Model Context Protocol (MCP) and deploy on the LangGraph Platform.

In the final week, you go deeper - literally. Deep Agents gives you harness-level control with subagent delegation, sandboxed execution, and filesystem backends. LangSmith gives you the observability layer: tracing every agent decision, evaluating output quality, and monitoring costs and latency in production.

How the course works:

12 live sessions. 2 per week. 2 hours each. Every session is followed by a mandatory assignment that gets graded with detailed written feedback. Your attendance, submission rate, code quality, and engagement are tracked and ranked against the cohort - transparently.

The course ends with a capstone: you build an enterprise-grade agent platform and present it live in front of a panel. It's recorded. It's evaluated. It goes on your portfolio.

What's included:

Lifetime access to all session recordings. Study notes and cheat sheets for every session. Starter code and full solution repositories. A private community that continues after the course. A certificate of completion. And a resume review to help you land the role.

Who is this for:

You can write Python. You understand what an API call is. You want to build AI systems that actually work in production - not just notebook demos that impress nobody. No ML background needed. No prior LangChain experience needed.

The stack:

LangGraph (orchestration) → LangChain v1.0 (agents) → Deep Agents (advanced harness) → LangSmith (observability).

Four frameworks. One logical sequence. The complete production agent stack.