AI Test Architect LangChain, LangGraph, RAG & MultiAgent QA

Master LangChain, LangGraph, RAG & ChromaDB in TS. Build an autonomous AI agent that write & heals Playwright tests
What you'll learn

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Build production-grade AI applications in TypeScript using LangChain and Anthropic's Claude models
Master LCEL (LangChain Expression Language) to compose chains, run steps in parallel, and stream responses
Generate reliable, type-safe structured output using Zod schemas and Claude's tool-calling API
Create custom tools that let an LLM read files, call APIs, run shell commands, and drive a browser
Build complete RAG pipelines with document loaders, chunking strategies, embeddings, and ChromaDB
Improve retrieval quality with metadata filtering, multi-query retrieval, re-ranking, and compression
Debug, trace, and cost-monitor every LLM call using LangSmith
Run automated evaluations on prompts - regression testing for AI, using skills you already have as a QA engineer
Prototype AI workflows visually with Langflow and export them as working APIs
Integrate Playwright with LangChain to generate specs and self-heal broken selectors
Understand why simple agents fail - and use LangGraph to build stateful, cyclic, multi-actor systems instead
Implement human-in-the-loop approval gates, checkpointing, and durable agent state
Build a full Autonomous QA Agent: explores an app, plans tests, writes Playwright specs, runs them, diagnoses failures, and heals itself in a loop
Requirements

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Experience with any test automation framework (Playwright, Selenium, Cypress) is helpful but not required
Typescript basics is covered from the scratch in the course
Free accounts for LangSmith and ChromaDB (local install, no cost)
No prior AI, machine learning, or Python experience needed
Description

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Every QA automation engineer is asking the same question right now: how do I move into AI before AI moves past me?
This course is the answer - and it's built specifically for you, not for Python data scientists.
You already understand test frameworks, assertions, CI pipelines, and debugging flaky systems. Those are exactly the skills AI engineering needs. What's missing is the LangChain layer - and that's what you'll build here, entirely in TypeScript, using Anthropic's Claude models.
We start from absolute zero on LangChain. Your first API call. Your first chain. Your first tool. Then we go all the way to a multi-actor autonomous agent with cycles, persistent state, and human approval gates.
What makes this course different
Most LangChain courses stop at a chatbot. This one ends with anAutonomous QA Agent - a real, working LangGraph system that
Explores a live web app using Playwright
Proposes a test plan and pauses for your approval
Writes Playwright specs
Runs them and captures failures
Diagnoses whether each failure is a real bug, a flaky test, or a broken selector
Rewrites the test and loops back to try again
That's not a toy. It's a portfolio piece that gets interviews.
You'll also master the tools teams actually pay for
LangSmith isn't an afterthought here - you'll use it from Section 8 onward to trace every agent decision, catch failures, and run prompt evaluation suites. As a QA engineer, you'll recognize it immediately: it's regression testing for LLMs.
VectorDBpowers a real RAG project - a searchable knowledge base over your own test suite, so you can ask "do we already have a test for this?"
Multi-Agent systems, Orchestration & Guardrails and many more practical concepts
Honest expectations
You'll see agents fail. We walk through what breaks, why it breaks, and how to build guardrails around it. Non-determinism is uncomfortable for testers - we address that directly instead of pretending it away.
By the end, you'll have shipped multiple working projects and one capstone that very few engineers can demo.
Enroll now and start building.
Who this course is for

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Anyone who wants to learn LangChain and build autonomous AI Agents
SDETs who want to build AI-powered testing tools
QA automation engineers transitioning into AI/ML engineering
TypeScript/JavaScript developers learning LangChain without switching to Python
Test leads evaluating AI agents for their team
Anyone who knows TypeScript and wants to build real autonomous agents, not chatbot demos
Homepage

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