Agent engineer

AI Agent Engineering

Agents are principals, not features. Each one needs an identity, a scope, and an audit trail.

Who this is for

Engineers and architects putting autonomous or semi-autonomous agents into a real environment.

What you should be able to do

Run an agent under a named autonomy tier with scoped credentials and an attributable log.

The delivery flow

The order the work actually happens in. Each step is where a decision gets made and written down, not a chapter heading.

Task definition
Agent identity
Scoped credentials
Tool registry
Planner / orchestrator
Autonomy tier gate
Human approval
Audit trail

Reference repository structure

A starting layout that keeps agents, infrastructure, and security policy as first-class directories rather than folders someone adds late.

project/
├── apps/            # web, api, admin surfaces
├── agents/          # planner, researcher, reviewer, orchestrator
├── infrastructure/  # terraform, kubernetes, helm, docker
├── security/        # policies, threat models, IAM scopes
├── monitoring/      # dashboards, alerts, SLOs
├── pipelines/       # CI/CD and evaluation gates
├── tests/
└── docs/

Reading path

12 published guides on this track. Every one is a live page on this site — nothing here is a placeholder.

Reference implementations

Citadel’s open-source repositories for this track — Terraform modules, MCP servers, and reference architectures you can read, fork, and run. Apache/MIT licensed; check each repository for its terms.

Primary sources

The standards, framework documents, and vendor references this track is built against. Go here when you need the authoritative wording rather than a summary — in a security review or an audit, the source is what counts.

Other tracks

Talk through this with an architect