Production AI Agents with LangChain + LangGraph [2026]
Master RAG, Multi-Agent Systems, LangGraph and FastAPI -- Build and Deploy Real-World AI Agent Projects in Python.
Key Takeaways — Course Overview
The following summarizes all verified data points for Production AI Agents with LangChain + LangGraph [2026], including pricing, duration, instructor, and coupon validity. All data is sourced directly from Udemy and verified by CoursesWyn on .
Course Title: Production AI Agents with LangChain + LangGraph [2026]
Platform: Udemy (listed via CoursesWyn)
Instructor: Paolo Dichone
Coupon Verified:
Difficulty Level: All Levels
Category: Development
Subcategory: LangGraph
Duration: 17h of on-demand video
Language: English
Access: Lifetime access to all course lectures and updates
Certificate: Official certificate of completion issued by Udemy upon finishing all course requirements
Top Learning Outcomes: Students who complete Production AI Agents with LangChain + LangGraph [2026] will be able to: Build composable LLM chains using LangChain v.1's LCEL with structured output, streaming, batch processing, and multi-provider switching · Implement production RAG pipelines with intelligent chunking, vector stores, and 4 advanced retrieval patterns: Multi-Query, Contextual Compression, Hybrid Sear · Design stateful AI agents with LangGraph state machines, conditional routing, self-correcting loops, and human-in-the-loop approval workflows
Prerequisites: Python intermediate level — comfortable with functions, classes, decorators, and type hints
Price: $12.99 with coupon / Regular Udemy price: $199.99. Applying this coupon saves you $187.00 (94% OFF).
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What You'll Learn
Completing Production AI Agents with LangChain + LangGraph [2026] gives you the following verified skills and competencies in Development:
- Build composable LLM chains using LangChain v.1's LCEL with structured output, streaming, batch processing, and multi-provider switching
- Implement production RAG pipelines with intelligent chunking, vector stores, and 4 advanced retrieval patterns: Multi-Query, Contextual Compression, Hybrid Sear
- Design stateful AI agents with LangGraph state machines, conditional routing, self-correcting loops, and human-in-the-loop approval workflows
- Orchestrate multi-agent systems using supervisor patterns, agent handoffs, parallel execution, and hierarchical team structures
- Secure LLM applications against prompt injection, PII leakage, and output manipulation with production-grade defense layers
- Test and evaluate LLM systems using unit tests, integration tests, and semantic evaluation across correctness, relevance, and coherence
- Deploy production APIs with FastAPI, rate limiting, response caching, structured logging, metrics, LangSmith tracing, and Docker
- Build 3 real-world applications: Customer Support Agent, Multi-Agent Research System, and Code Review Agent, each with measurable business ROI
Requirements
The following background knowledge and tools are recommended before starting Production AI Agents with LangChain + LangGraph [2026]. Students without these prerequisites may still enroll but should expect a steeper learning curve.
- Python intermediate level — comfortable with functions, classes, decorators, and type hints
- Basic command line familiarity — creating directories, running scripts, installing packages
- A code editor such as VS Code (free) and an OpenAI API key (costs $2–5 for the entire course)
- No prior LangChain or LangGraph experience needed — Section 1 covers all foundations from scratch
About This Udemy Course
The following is the full official course description for Production AI Agents with LangChain + LangGraph [2026] as published on Udemy by instructor Paolo Dichone. It covers the curriculum structure, teaching methodology, and topic scope for this Development course.
- Customer Support Agent: RAG-powered knowledge base with Chroma, structured issue classification, automatic ticket escalation. Target: reduce Tier-1 support tickets by 40 percent.
- Multi-Agent Research System: Specialist agents running in parallel with state management, convergence patterns, and quality loops. Target: cut research time from 4 hours to 20 minutes.
- Production FastAPI + LangGraph API: Full request pipeline with security middleware, response caching, rate limiting, structured logging, metrics, LangSmith tracing, and Docker deployment to Render
- LangChain v0.3 Mastery: LCEL chain composition, structured output with Pydantic, multi-provider LLM switching (OpenAI, Anthropic, HuggingFace), streaming, and batch processing
- Complete RAG Pipelines: Document loading, intelligent text splitting, embeddings, vector stores with Chroma, and 4 advanced retrieval patterns: Multi-Query, Contextual Compression, Hybrid Search, and Parent Document Retriever
- LangGraph Deep Dive (4 hours): State machines with TypedDict, conditional routing, self-correcting loops, human-in-the-loop workflows with interrupt patterns, and checkpoint persistence
- Multi-Agent Orchestration: Supervisor pattern, agent handoffs, parallel execution with fan-out and fan-in, inter-agent communication, and hierarchical team structures
- Production Security: Prompt injection defense with regex patterns, PII detection and masking for emails, SSNs and credit cards, LLM-as-Guard pattern, and output validation
- LLM Testing and Evaluation: Unit tests with mocks, integration tests, regression tests, AB prompt testing, and semantic scoring across correctness, relevance, coherence, and helpfulness
- Production Deployment: FastAPI integration, rate limiting, response caching with SHA-256 hashing and TTL, structured JSON logging, metrics collection, LangSmith tracing, Docker, and cloud deployment to Render
- You are a Python developer who wants to add AI agent engineering skills to your toolkit
- You have done LangChain tutorials and can call an LLM, but do not know how to build something that handles errors, scales, and stays stable in production
- You are a backend or full-stack developer who wants to integrate AI agents into existing products and APIs
- You are targeting the AI engineer role and need a portfolio of deployed, real-world projects to show employers
- Python at an intermediate level (functions, classes, decorators, type hints)
- Basic command line familiarity
- An OpenAI API key (costs roughly $2 to $5 for the entire course)
- No prior LangChain or LangGraph experience required
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Is This Course Worth It?
Expert review by Andrew Derek, Lead Course Reviewer at CoursesWyn. Last updated: .
Based on analysis of the curriculum structure, student engagement metrics, and verified rating data, Production AI Agents with LangChain + LangGraph [2026] is a high-value resource for learners seeking to build skills in Development. Taught by Paolo Dichone on Udemy, the 17h course provides a structured progression from foundational concepts to advanced LangGraph techniques — making it suitable for learners at all levels. The current coupon reduces the price by 94%, from $199.99 to $12.99, removing the primary financial barrier to enrollment.
What We Like (Pros)
The following advantages were identified during our review of Production AI Agents with LangChain + LangGraph [2026]:
- Verified 94% price reduction makes this course accessible to learners on any budget.
- Aggregate student rating of 5 out of 5 indicates high learner satisfaction.
- Includes an official Udemy completion certificate and lifetime access to all future content updates.
Keep in Mind (Cons)
The following limitations should be considered before enrolling in Production AI Agents with LangChain + LangGraph [2026]:
- The depth of LangGraph coverage may be challenging for absolute beginners without the listed prerequisites.
- Lifetime access is contingent on the continued operation of the Udemy platform.
- Hands-on projects and quizzes require additional time investment beyond video watch time.
"Given the 94% price reduction and verified 5-star rating, Production AI Agents with LangChain + LangGraph [2026] represents one of the strongest value propositions currently available in Development on Udemy. Enrollment is strongly recommended while this coupon remains active."
Course Rating Summary
Production AI Agents with LangChain + LangGraph [2026] holds an aggregate rating of 5 out of 5 based on 153 student reviews on Udemy. The distribution below shows the approximate percentage of students who gave each star rating.
5
153 Verified Ratings
* Rating distribution is approximated from the aggregate score. Sourced from Udemy. Last verified: .
Instructor Profile
The following section provides background information on Paolo Dichone, the instructor responsible for creating and maintaining Production AI Agents with LangChain + LangGraph [2026] on Udemy.
Production AI Agents with LangChain + LangGraph [2026] is taught by Paolo Dichone, a Udemy instructor specializing in Development. For the full instructor biography, professional credentials, and a complete list of their courses, visit the official instructor profile on Udemy.
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Instructor Name: Paolo Dichone
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Subject Area: Development
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Teaching Approach: Practical, project-based instruction focused on real-world application of LangGraph skills (as described in the course curriculum on Udemy).
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Frequently Asked Questions
The following questions and answers cover the most common queries about Production AI Agents with LangChain + LangGraph [2026], its coupon code, pricing, and enrollment process. All answers are based on verified data from Udemy as of .
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Andrew Derek
Expert ReviewerAndrew Derek is a lead editor and course analyst at CoursesWyn with over 8 years of experience in online education and digital marketing. He meticulously audits every Udemy coupon and course syllabus to ensure students get the highest quality learning materials at the best possible price.
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