Who these guides are for
Product and operations teams building agent workflows, and security teams responsible for what those agents can do once they reach real systems.
- Teams automating multi-step work across models, tools, and business systems
- Agents that send messages, change records, approve work, or delegate to other agents
- Workflows that need role-based permissions, approval thresholds, and execution history
- Operators who need to stop a bad run and recover affected state without guessing
Industry guides
Agent workflow and control blogAI governance for mid-size companies (50–1,000 employees)Healthcare Copilot AI governanceLegal firm AI governanceManufacturing AI governanceAccounting firm AI governanceInsurance AI governanceRetail Copilot AI governanceStale CRM contact blockedAI support refund approvalExternal party actions approvalContract amendment wrong vendor contactJira delete blocked (destructive actions)Invoice approval above thresholdPrior auth without audit trailHubSpot write without rollbackMCP tool call without receiptZendesk ticket reply autoStale patient record holdSupplier payment dual approvalEducation AI governance (FERPA)Logistics AI governanceConstruction AI governanceReal estate AI governance
What every guide covers
One real scenario
A specific action AI tried to take in your industry — email, record change, document access — and what went wrong without controls.
What a small team can enforce
Human approval thresholds, access boundaries, and audit trails you can explain to leadership without a PhD in machine learning.
How LoopLabs fits
A workflow and control layer between your agents and the models, tools, data, and systems they use.