ADVANCED
Introduction to systems, agents, and governance
Advanced is not “more tokens” — it is recurring systems: when to use agents, how Custom GPTs propagate standards, and how governance stays human-scale.
Expected outcomes
You can name when an agent, a Custom GPT, or plain chat is the right shape.
Automation boundaries your firm can defend — owners, logs, and kill switches included.
Governance that scales: pilot metrics, blast radius, and proportionate controls.
Skills you'll learn
Custom GPTs
Agents
Automation boundaries
Human review at scale
Governance thinking
Agent literacy
What agents are
Chained tool use with a goal — useful when steps are bounded, observable, and reversible.
Where they help
Ops with clean inputs (tickets, forms), research packaging with citations hygiene, and internal glue where humans stay on the hook for outcomes.
Risks
Ambiguous goals, silent retries, and silent hallucination at the end of a chain — supervise end-to-end.
Supervision
Require logs, name owners, define kill switches, and rehearse failures before client impact.
Rules of thumb
Automate only after a manual pattern survives three real cycles.
Custom GPT instructions are code — review them like code.
If you cannot explain the blast radius, do not widen connectors.
Measure useful artifacts, not novelty chats.
Resources
Exercise
On one page, design a supervised agent or workflow: goal, inputs, tools, human review gates, failure modes, and what success metrics you would track for a pilot. Share it with a peer who did not build it — if they cannot run it, simplify.
Suggested next step
Roll out adoption signals and admin-ready governance