Building agents with skills and human approval.
Tick the skills an agent may use. Pause before action. Keep every agent inside the scope of the people allowed to run it.
Skills you tick, not code you write
Agents in SenangAI are assembled from skills you tick. Unticked skills do not exist for that agent. The person who understands the work writes the name, the instructions and the skill list. Engineering is not the bottleneck.
Skills compose into agents. Agents and approval steps compose into workflows. That is how a legal teamspace can hold a contract reviewer and a renewal watch without a custom app for each job. See how agents are built.
Scope follows the people
An agent only sees what the people who may use it are allowed to see: just you, a named team, or the organisation. Nothing can exceed the scope of the space it lives in. A personal agent is not a private path around the platform.
Yukon Labs names the failure that breaks naive agent stacks: if retrieval runs under a service account, every user effectively has the union of all permissions. Identity has to travel with the request. The same boundary holds whether the agent answers a question or prepares a file for sign-off. That sits on Understand and Govern.
Pause before action
Every agent is created paused. Workflows can hold before a consequence begins: a send, a file write, a notification that someone will act on. A person decides what runs.
EU AI Act Article 14 requires high-risk systems to be designed so a person can oversee them while in use. Strac’s 2026 framework note is useful here: for agents in regulated domains, human oversight stops being a best practice and becomes a legal requirement. The opposite pattern showed up this month on Hacker News, where a coding agent defaulted to auto permission mode. Convenience is not a control.
Drafting can stay in chat. Action that changes a record, a client, or a filing should wait. For how that sits next to chat and search, read where SenangAI fits.
Authority in the record
nyk’s note on agent governance for a regulated engineering org makes a point buyers miss: the record must state what the agent was permitted to do, not only what it did. Authority at the time of the run is the part reconstructed least reliably after the fact, because the config has moved on. If the thing being audited can edit the audit, you have a log, not evidence.
Permissions, citations, approval and audit stay on. They cannot be configured away. Cost is visible per request. The trail shows who built the agent, who ran it, what it used, and who approved the step. Job shapes that need that trail are on legal, finance and IT.
When you want us in the room, book a demo and bring one workflow with a real approval step.
Sources and references
- What Is AI Orchestration? Agents and Workflows. Yukon Labs.
- AI Governance Framework Guide: NIST AI RMF, ISO 42001 and EU AI Act (2026). Strac.
- Agent Governance and Traceability for a Regulated Engineering Org. nyk.
- Claude Code: auto mode will be the default permission mode. Reported on Hacker News, 7 August 2026.
- AgentGuardian – Enterprise AI Governance. Glacien, YouTube, 8 August 2026.