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This track is about the gap between a demo and a service people rely on. It covers retrieval-augmented generation, agents and MCP, but the stronger thread is operations: deployment, security, monitoring, cost awareness and continuous delivery across several clouds.
Each week moves to a new stage. An early week ships a full-stack SaaS application, followed by serverless AI infrastructure written as code with CI/CD pipelines. Later weeks extend into multi-cloud GenAI deployment, model inference and vector data ingestion, and finish with a multi-agent system built on managed databases and queues.
This is the course that more of my students have asked for than any other course — put together.
One student called it:
“The missing course in AI.”
This course is for:
Entrepreneurs
Enterprise engineers
…and everyone in between.
It’s not just about RAG — although we’ll work with RAG.
It’s not just about Agents — but there will be many Agents.
It’s not just about MCP — but yes, there will be plenty of MCP too.
This course is about:
RAG, Agents, MCP, and so much more… deployed to production.
Live.
Enterprise-grade.
Scalable, resilient, secure, monitored — and explained.
You’ll ship real-world, production-grade AI with LLMs and agents across Vercel, AWS, GCP, and Azure, going deepest on AWS.
Across four weeks you’ll take four products to production:
Week 1
You’ll launch a Next.js SaaS product on Vercel and AWS,
with AWS App Runner and Clerk for user management and subscriptions.
Week 2
You’ll become an AI platform engineer on AWS,
deploying serverless infrastructure using:
Lambda, Bedrock, API Gateway, S3, CloudFront, Route 53
Write Infrastructure as Code with Terraform
Set up CI/CD pipelines with GitHub Actions
— for hands-free deployments and one-click promotions.
Week 3
You’ll gain broad industry skills for GenAI in production:
Deploy a Cyber Security Analyst agent with MCP to Azure & GCP
Stand up SageMaker inference
Build data ingest to S3 vectors
Deploy a Researcher Agent using OpenAI OSS models on Bedrock + MCP
Week 4
You’ll go fully agentic in production:
Architect multi-agent systems with:
Aurora Serverless, Lambda, SQS
JWT-authenticated CloudFront frontends
LangFuse observability
Overview of AWS Agent Core
By the end, you’ll know how to:
Pick the right architecture
Lock down security
Monitor costs
Deliver continuous updates
Everything needed to run scalable, reliable AI apps in production.
Course sections (Weeks & Projects)
Week 1
SaaS App Live in Production with Vercel, AWS, Next.js, Clerk, App Runner
Project: SaaS Healthcare App
Week 2
AI Platform Engineering on AWS with Bedrock, Lambda, API Gateway, Terraform, CI/CD
Project: Digital Twin Mk II
Week 3
Gen AI in Production with Azure, GCP, AWS SageMaker, S3 Vectors, MCP
Project: Cybersecurity Analyst
Week 4
Agentic AI in Production: Build and deploy a Multi-Agent System on AWS (Aurora Serverless, Lambda, SQS),
with LangFuse and Bedrock AgentCore
Capstone Project: SaaS Financial Planner
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Tracking since 15 Nov — not enough history yet to tell you whether today's price is any good. Watch the course and we'll tell you when it drops.
This is what we recorded in US pricing — not every price this course has ever had, and prices differ by country.
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