Build AI Agents That Actually Work

Most AI agent tutorials stop at a chatbot that can call a tool.

This course goes further.

You’ll learn how to design and build production-grade AI agents that can work with real data, execute real tasks, stream responses in real time, recover from failures, and actually run in production.

We’ll build a real AI application from scratch and use it to understand the engineering problems that appear when you move from an LLM prototype to a reliable product.

What you'll build

A production-style AI agent that can:

• Understand natural-language requests
• Reason through multi-step tasks
• Use tools and external systems
• Work with real databases and data
• Generate and execute SQL safely
• Stream progress and results in real time
• Maintain context and conversation state
• Handle long-running tasks
• Recover from failures and disconnected sessions
• Run asynchronously using queues/workers
• Be monitored, debugged and deployed

What you'll learn

AI Agent Architecture

• Agent vs workflow
• Tool calling
• Planning and execution loops
• Structured outputs
• Context management
• Memory

Data & Backend Engineering

• LLM → SQL → Database pipelines
• Query validation and safety
• PostgreSQL
• Redis
• Async workers and queues
• Caching
• Rate limiting

Real-Time AI Systems

• WebSockets
• Streaming events
• Long-running agent sessions
• Reconnection
• Session persistence
• Background execution

Production Engineering

• Failure handling
• Retries and fallbacks
• Observability
• Logging and tracing
• Latency optimization
• LLM cost optimization
• Security
• Deployment

Who is this for?

This course is designed for software engineers, backend engineers, data engineers and AI/ML engineers who already know the basics of programming and want to learn how real AI systems are engineered.

You don't need to be an AI researcher.

You do need to be comfortable writing code.

What this course is NOT

This is not a prompt-engineering course.

You won't spend hours learning how to write clever prompts or building another basic chatbot.

The focus is on the engineering behind reliable AI products.

By the end

You won't just understand how AI agents work.

You'll have built one — and more importantly, you'll understand the architecture and engineering decisions required to take an AI system from prototype → production.

Stop building AI demos. Build AI agents that actually work.