AI Engineer Production Track: Deploy LLMs & Agents at Scale

About this course

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 1You’ll launch a Next.js SaaS product on Vercel and AWS,with AWS App Runner and Clerk for user management and subscriptions. Week 2You’ll become an AI platform engineer on AWS,deploying serverless infrastructure using:

Lambda, Bedrock, API Gateway, S3, CloudFront, Route 53Write Infrastructure as Code with TerraformSet up CI/CD pipelines with GitHub Actions— for hands-free deployments and one-click promotions.

Week 3You’ll gain broad industry skills for GenAI in production:

• Deploy a Cyber Security Analyst agent with MCP to Azure & GCPStand up SageMaker inference
• Build data ingest to S3 vectors
• Deploy a Researcher Agent using OpenAI OSS models on Bedrock + MCPWeek 4You’ll go

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