A project-based path into applied AI

Learn AI by building things that work.

Choose a path, follow a guided project, and leave with a working artifact instead of another course you merely watched.

The role

Who is an AI engineer?

An AI engineer builds dependable software with models and agents.

They connect AI to data, tools, interfaces, and real workflows. Then they evaluate the system, constrain its behaviour, and improve it when it fails.

Define the task, what success looks like, and what can go wrong.

Connect models and agents to the context, data, tools, APIs, and interfaces they need.

Test real scenarios, constrain actions, and balance quality, safety, speed, and cost.

Deploy the product, observe failures, and improve it with evidence.

Roadmap

Progress from foundational agent applications to knowledge, orchestration, and production operations through practical projects.

Start here · Foundations
Build Agent Applications
Create focused applications with model APIs, structured outputs, validation, basic tool use, and evaluations.
Coming soon
Next · Knowledge
Connect Agents to Knowledge
Ground applications in trusted information using ingestion, retrieval, RAG, citations, and retrieval evaluation.
Coming soon
Then · Orchestration
Orchestrate Stateful Agent Workflows
Coordinate memory, tools, state, multi-step execution, human approval, and failure recovery.
Coming soon
Finally · Production
Ship and Operate Agent Systems
Run dependable systems with evaluations, observability, security, cost controls, and production feedback loops.
Coming soon

Early access

Join the waitlist for launch updates and early access to new agent engineering projects.