Building Gen AI Agents for Enterprise: Beyond the Hype
Hamza Farooq
Founder | Ex-Google | Instructor Stanford Continuing Studies & Adjunct UCLA
Build Production-Ready SaaS Agents that work
You're drowning in AI vendor promises and overlapping tools, wondering: "Which of these actually solves our problems?"
After working with organizations across fintech, supply chain, and manufacturing, we've seen the same pattern: businesses know AI matters but can't identify use cases that deliver measurable ROI.
This course cuts through the noise. You'll build production-ready GenAI SaaS Agents using no-code and low-code approaches—without needing a programming background.
You will build full-scale websites with an AI backend.
Two-Part Approach:
No-code tools for building AI agents
Low-code approaches for complex agent systems
What Makes This Different
We focus on the "what" before the "how"—use case identification, business value assessment, and strategic deployment over technical implementation.
7 Modules: From Concept to Demo
Module 1: GenAI landscape and Industry impact
Module 2: No-code agent building blocks (loveable & n8n)
Module 3: Enterprise RAG with production guardrails
Module 4: Vertical AI Agents and Orchestration
Module 5: Deploying a production-ready website with an AI backend
Module 6: Capstone workshop with peer feedback
Module 7: Demo day—present your working system
What you’ll learn
Master the what, why, and how of Generative AI by building Enterprise-Grade Agents that go beyond the basics and actually move the needle
Get hands-on with use case identification workshops and business value scorecards
Analyze real case studies from fintech, manufacturing, and consulting to recognize patterns of successful vs. failed implementations
Use No-Code tools to build your first AI Agent
Master AgentPro and similar platforms to create multi-step agent workflows with memory, reasoning, and tool integration
Implement guardrails and safety controls that meet enterprise compliance standards
Deploy agents that can handle customer inquiries, data analysis, and document processing at scale
Apply advanced chunking strategies and embedding techniques to optimize information retrieval accuracy
Build RAG systems with feedback loops that continuously improve relevance and user satisfaction
Configure monitoring dashboards that track system performance, costs, and user satisfaction metrics
Implement multi-layered safety controls, including content filtering, output validation, and escalation protocols
Design deployment architectures that scale efficiently while maintaining response quality
Structure presentations using the Problem-Solution-Impact framework to communicate clearly to non-technical executives
Develop implementation roadmaps with timeline, resource requirements, and success metrics for organizational buy-in
Demo live systems during our capstone showcase, receiving feedback from peers and industry mentors
Who this course is for
Product Managers looking to integrate GenAI into their roadmaps with clarity and confidenceYou want to cut through the jargons and actually
Technical Leaders and Architects who want to build scalable and safe GenAI systems
Startup Founders & Innovation Teams aiming to create competitive GenAI-powered products
Prerequisites
Just be willing to learn, we will take of the rest
If you haven't written code before, no worries at all. We will provide you with everything you need to get started.
What's included
Live sessions
Learn directly from Hamza Farooq 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.
$25k production-ready SaaS templates
RAG systems, agent orchestration, fine-tuning, guardrails, semantic caching, and production deployment verified through real enterprise use cases
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Syllabus
5 live sessions • 37 lessons • 3 projects
Week 1
Oct
2
Session 1
Module 1: The GenAI Revolution—Introducing AI Agents
Week 2
Module 2: Building Blocks for no Code Agents with RAG
Oct
9
Session 2
Featured lesson
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Design Vertical AI Agents That Deliver Results
Empowering Decision-Making with AI Agents
Multi-agent systems automate workflows, enhance collaboration, and provide real-time support for complex tasks.
Streamlining Knowledge Access with Enterprise RAG
RAG breaks down data silos, enabling seamless access to Enterprise Knowledge for smarter, faster decision-making.
Explore Practical Applications of AI Agents
Get hands-on insights into building AI agents from scratch, understanding their architecture, and deploying them.
Schedule
Product & Technical Lectures: 2 hours per week
Live Class
Office Hours (optional): 1 hour per week
Come say hi, ask questions (not recorded)
Core sessions
- Oct 2Thu2:00 AM—3:45 AM (UTC)
- Oct 9Thu2:00 AM—3:45 AM (UTC)
- Oct 16Thu2:00 AM—3:45 AM (UTC)
- Oct 23Thu2:00 AM—4:00 AM (UTC)
- Oct 30Thu2:00 AM—3:45 AM (UTC)
Success stories
- The course was great! It was full of great content, a very active cohort, and I feel I learned many methods for putting Large Language Models (LLM) into production. The course was very well-structured, starting with the basics of NLP and building up towards analyzing and describing documents using NLP techniques, all the way to deploying an API
Victor Calderon
Senior Machine Learning Engineer - Amazing! I am leaving this course feeling empowered and equipped with the skills to leverage LLMs to build and deploy applications. I was able to implement the knowledge I learned immediately at work and with personal projects. Hamza is an awesome instructor. He is passionate about this topic and was able to simplify the concepts
Tiffany Teasley
Data Scientist & Career Coach at Data Sistah - Prof Hamza Farooq is a far-sighted, application oriented AI Researcher and a great Professor. Working under him was full of learnings and practical knowledge
Darshil Modi
Cohort 1 - Hamza provided several excellent projects to learn from, showcasing quite a few ML practices and options in each. Learned a ton that I continually go back to!
Tony Dupre
Cohort 1 - Hamza's class was among my favorites of my Master's program! He makes the tools of machine learning accessible and his teaching skills are on point.
Nicole Lovold-Egar
Beta Cohort - Hamza was an excellent instructor. He was able to explain various machine learning techniques in ways that were easy to understand and apply them to real world problems
Dan Kellen
Beta Cohort
Students from all over the world
Proud to have served to 1500+ students!
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Various events and conferences, I have been teaching
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