Skill guide

AI agents

An AI agent is a system that uses a model to choose and execute actions toward a goal within defined tools, context, constraints, and oversight.

Why this capability matters

Agents can help with multi-step work, but they add uncertainty and require stronger evaluation, permissions, monitoring, and escalation design.

What competent practice includes

Agent use-case selection
Tool and memory design
State, orchestration, and approvals
Evaluation and guardrails
Production monitoring
Portfolio evidence

A tool-using agent with a clear architecture, bounded permissions, evaluation set, decision log, and human override.

See public project briefs

Professional applications

These are fields of application, not guaranteed job or income outcomes.

Research assistantsKnowledge workOperations triageMulti-stage drafting and reviewDeveloper workflows

Courses that develop this skill

Agentic Systems
Agentic AI
How to design AI systems that plan, decide, and act across multi-step tasks instead of just answering prompts.
Agentic Systems
Agentic AI Development with LangChain & LangGraph
The production framework stack for building controllable, stateful multi-agent applications.

Connect the skill to a market path

Learn how this capability fits inside a complete problem, proof, service, and delivery journey.

Read the connected guide