Agentic Supervision
glossary intermediate 4 min
Sources verified Dec 27, 2025
Overseeing AI agents that execute multi-step tasks autonomously.
Simple Definition
Agentic Supervision is the practice of monitoring and guiding AI agents when they work autonomously on multi-step tasks. Unlike simple prompts (ask → answer), agents plan, execute, and iterate—requiring a different kind of oversight.
Technical Definition
The discipline of:
- Scoping tasks appropriately for agent capabilities
- Setting guardrails (file access, tool permissions, output constraints)
- Reviewing intermediate outputs during long-running tasks
- Intervening when agents drift off course
- Validating final outputs against original intent
Why It's Different from Regular Code Review
| Traditional AI Use | Agentic AI Use |
|---|---|
| Ask one question, get one answer | Agent runs multi-step workflow |
| Human applies each change | Agent applies multiple changes autonomously |
| Easy to review one diff | Must review cumulative effect of many changes |
| Human in the loop for every step | Human supervises the loop |
Agents can:
- Create files, run commands, make API calls
- Chain multiple operations together
- Make decisions based on intermediate results
This autonomy requires more structured oversight.
Key Takeaways
- Agentic AI runs multi-step tasks autonomously
- Requires different oversight than simple prompt-response
- Key skills: scoping, guardrails, intermediate review, intervention
- Scoped delegation beats open-ended mandates
Sources
Tempered AI — Forged Through Practice, Not Hype
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