Where AI Agents Help, and Where They Should Stop
A practical framework for agentic AI: which tasks suit AI agents, how to set levels of autonomy, and why people should approve consequential actions.
Insights category
Artificial Intelligence
Practical notes on generative AI, AI agents and intelligent automation: where they help, where they need limits and how to put them to work responsibly.
1 essay in Artificial Intelligence
6 min read
Where AI Agents Help, and Where They Should Stop
A practical way to decide how much an AI agent should be allowed to do on its own
What the essay covers:
- What makes an AI agent different
- Tasks where agents genuinely help
- Tasks where agents should stop
- A ladder of autonomy
- The unglamorous engineering that makes agents safe
- Accountability does not transfer to software
- Where to start
About this theme
Why Rohit writes about artificial intelligence
Rohit's first neural network was trained in 2004. Today his work includes AI agents and intelligent automation for organisations. These essays try to separate what AI does well from what it is merely said to do, and to describe the design choices that keep people in control.
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