Deploying AI Agents: LLMs, LangGraph, and Production APIs

Overview

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"Take your AI agent skills into production with this hands-on course on building, validating, and deploying LLM-powered agents using LangGraph, LangChain, Pydantic-AI, Mem0, CrewAI, Agno, and FastAPI. You’ll learn to turn prototypes into reliable, enterprise-grade agent systems. Module 1 covers integrating LLMs (OpenAI, Anthropic) into LangGraph reasoning pipelines, designing nodes, control flow, token management, and iterative workflow testing. Module 2 focuses on schema enforcement with Pydantic-AI, structured outputs, and building a Business Workflow Assistant with validated, reliable I/O. Module 3 guides you through full deployment — FastAPI backends, persistent memory with Mem0 and vector stores, and orchestration with Agno and CrewAI in production. Module 4 teaches evaluation: metrics, logging, load testing, benchmarking, and comparing LangGraph, CrewAI, and Agno for enterprise-scale deployment. By the end of this course, you will: - Integrate LLMs into modular LangGraph reasoning pipelines - Validate agent I/O using Pydantic-AI schemas for reliable outputs - Deploy agents via FastAPI with Mem0 and vector-store persistence - Evaluate and benchmark frameworks to justify production choices"

Syllabus

Foundations of Multi-Agent Collaboration

This 4-hour module introduces learners to the transition from single-agent to collaborative multi-agent systems, emphasizing teamwork dynamics, communication strategies, and distributed reasoning.

Designing Role-Based Multi-Agent Workflows

This 4-hour module has learners design and simulate a functional, role-based workflow demonstrating structured collaboration between multiple agents using CrewAI's orchestration tools.

Shared Memory and Context Coordination

This 4-hour module explores shared memory integration in multi-agent systems, focusing on context continuity, communication efficiency, and memory optimization strategies using Mem0.

Orchestrating and Evaluating Multi-Agent Systems

In this final 4-hour module, learners orchestrate multi-agent collaboration using Agno, simulate a real-world Customer Support workflow, and conduct comparative evaluations of leading frameworks.