Build Production-Ready AI Agents for the Enterprise
Doug Turnbull
Agentic Search Expert
Hugo Bowne-Anderson
AI Builder/Educator (6 Million Students)
Real agents don’t just chat: they find, organize, and act.
Your company sits on endless reports, documents, and files. Agents leverage your company’s rich volumes of data to support customers and make business decisions.
In this course agentic search expert Doug Turnbull partners with AI expert Hugo Bowne-Anderson to create agents that actually work.
At the foundation of production agents sit an LLM, a reasoning loop, an agent harness, and a layer of context engineering + retrieval.
Research consistently shows AI answer quality depends more on the underlying search than any other factor. We’ll go from the ground up - building an agent from scratch, giving you what you need to make them actually useful with accurate search + retrieval.
You will leave with a working e-commerce agent, a retrieval pipeline, a starter eval set, and a deployment-ready architecture you can adapt to your own company data.
Coding along is optional. All examples are in the workshop repository, so you can focus on the session and try them afterwards. To run the code live, bring an OpenAI API key with approximately $10 of credit.
Very early bird: $750 USD through October 18. Early bird: $850 USD from October 19 through November 15. Full price: $950 USD from November 16.
What you’ll learn
Build and reason about enterprise agents grounded in your team's knowledge base
Learn how agents really work: LLM calls, tools, state, and reasoning loops.
Build an agent in Python before moving to higher-level SDKs and frameworks.
Know when to use simple LLM calls, workflows, or full agentic reasoning.
Connect agents to company docs, reports, files, and knowledge bases.
Go beyond basic RAG with multi-step search, retrieval, filtering, and synthesis.
Use MCP and retrieval tools to help agents find the right context before acting.
Design the prompts, tool schemas, memory, and context that guide agent behavior.
Build context engineering patterns that keep agents focused, grounded, and useful.
Add guardrails, structured outputs, and error feedback for more predictable systems.
Improve retrieval with BM25 baselines, recall-first search, reranking, and filtering.
Use evals and LLM judges to test whether your agent is actually working.
Deploy a cloud-based customer service agent with async jobs, hooks, and automation.
Learn directly from Doug & Hugo
Doug Turnbull
Led teams at Shopify, Reddit, Wikipedia
Hugo Bowne-Anderson
AI & data engineer, consultant, educator of 6+ million students (ex-Yale)
Who this course is for
Data scientists, machine learning engineers who are sick & tired of seeing and building prototypes & want to ship reliable LLM applications
Software engineers who want to learn how to build Generative AI systems and learn the LLM software development lifecycle.
Search technologists who connect enterprise knowledge with AI systems with RAG + Agentic Serach
What's included
Live sessions
Learn directly from Doug Turnbull & Hugo Bowne-Anderson in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
$500 in cloud + compute credits
$500 in Modal credits to deploy your applications
Maven Guarantee
Your purchase is backed by the Maven Guarantee.
Course syllabus
4 live sessions • 31 lessons
Week 1
Dec
13
Workshop 1: Build Agents From First Principles
When to use LLM calls, workflows, or agents
Build an e-commerce agent loop
Introduce SDKs and MCP
Engineer the agent harness
Local e-commerce agent
Week 2
Dec
15
Office Hours: Agent Architecture Review
Dec
17
Workshop 2: Ground, Evaluate, and Deploy Enterprise Agents
Dec
20
Capstone project show + tell
Agent loops, setup, SDKs, and debugging
Connect product catalogs, policies, order data, and support knowledge bases
Modern retrieval for agentic systems
MCP and context engineering
Evals, automation, and deployment
Project: Retrieval-grounded e-commerce agent
Schedule
Live sessions
4 hrs / week
2 live workshops • 1 office hour • 1 capstone project
Sun, Dec 13
11:00 PM—2:00 AM (UTC)
Tue, Dec 15
11:00 PM—12:00 AM (UTC)
Thu, Dec 17
11:00 PM—2:00 AM (UTC)
Sun, Dec 20
11:00 PM—12:00 AM (UTC)
Projects
3 hrs / week
Async content
3 hrs / week
December cohort pricing
Very early bird: $750 USD through October 18.
Early bird: $850 USD from October 19 through November 15.
Full price: $950 USD from November 16.
Frequently asked questions
Maven for Teams
Reimbursement
Get your company to pay
Everything L&D needs: email template, receipts, and certificate of completion.
Get reimbursedTeam discount
Learn with your teammates
Save 20%+ when 2 or more teammates enroll in the same cohort.
Save 20%+ with a teamPrivate cohort
Run a cohort for your org
A dedicated cohort with a custom schedule and curriculum, tailored to your team.
Book a private cohort$750
USD