AI Engineering & Agentic AI Architect
From software engineer to production AI engineer and agent architect.
The complete engineering course: LLM applications, RAG, tools and agents, workflow patterns, MCP, memory, evaluation, security, production engineering, AWS architecture, system design and five hands-on labs.
15 lessons · about 4.9 hours
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Write a production system prompt: role, scope, tools, rules, failure behaviour.
Review a retrieval-augmented design for quality, security and cost.
Turn a human procedure into an agent workflow with checkpoints and guardrails.
Fill the full design-doc template from a rough idea.
Imagine the launch failed; list how and what guard stops each failure.
Design tools an agent can use reliably: names, descriptions, parameters, errors.
Define the schema that passes context safely between two agents.
Write the five-part brief a lead agent gives each worker.
Pressure-test whether your task really needs multiple agents.