Cohort Program

Build Production AI Apps with LangChain and FastAPI

Six weeks to production-ready LLM applications, from API to deployed endpoint

About this cohort program

Building AI demos is easy. Building AI applications that survive real users, real data, and real scale is where most teams fail. This course gives you the full production stack, from API integration to deployment, using patterns from teams at Anthropic, Google, and Stripe.

What you will learn

  • Structure a full LangChain application with proper separation of chains, tools, and memory
  • Build a production-grade FastAPI backend that serves LLM calls with streaming, auth, and rate limiting
  • Implement conversation memory, document retrieval, and tool use in a single unified agent
  • Deploy your AI app to production with observability, error handling, and cost monitoring built in

Who this is for

  • Software engineers ready to go beyond simple API calls and build real, production-grade AI applications
  • Full-stack developers who want to add LLM capabilities to their existing products and services
  • Technical founders building AI-first products who need a complete engineering foundation

By the end

Before

Simple API calls that break under real load

After

Production-grade apps with auth, rate limiting, and monitoring

Before

Demos that do not survive real users

After

Deployed applications with streaming and full observability

Before

LangChain tutorials that stop at hello world

After

Full RAG agents with memory, tools, and FastAPI serving

Syllabus

  1. Session 1 · Wednesday, June 10, 2026

    LangChain Architecture and Your First Application

  2. Session 2 · Wednesday, June 17, 2026

    Chains, Memory, and Working with Prompts and Output Parsers

  3. Session 3 · Wednesday, June 24, 2026

    Tools, Agents, and LangGraph Stateful Workflows

  4. Session 4 · Wednesday, July 1, 2026

    Document Loading, Embeddings, and Building a RAG Pipeline

  5. Session 5 · Wednesday, July 8, 2026

    FastAPI Integration, Authentication, and Streaming Responses

  6. Session 6 · Wednesday, July 15, 2026

    Production Deployment, Observability, and Capstone

About Aisha

Aisha Okonkwo

Aisha Okonkwo

Full-Stack AI Engineer, ex-Anthropic

Vetted by Maram

Aisha spent three years on the applied engineering team at Anthropic, building production integrations for Claude across enterprise clients. She now runs her own AI engineering studio, shipping AI products for Series A and B startups. Her open-source FastAPI-LangChain starter kit has been cloned over 18,000 times on GitHub.

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What learners say

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