7 principles to manage AI agents
Comparison of external material with INEMA’s methodology for managing AI agents.
The analysis compares external material on managing AI agents with INEMA’s methodology. Its central ideas are intent, context, reliable data, evaluation, and human oversight. The comparison suggests that concepts used by technology companies connect with practices already present in the INEMA approach.
For people using AI agents, the proposal is to follow a work cycle: define what is expected, provide context, set criteria, delegate tasks, measure results, supervise, and correct. This helps organize the use of agents and track what they deliver.
To get started, check whether the task has a clear intent, enough background information, and criteria for evaluating the result. INEMA’s methodology adds structure, memory, specific skills, and metrics to the general principles. The external material serves as a reference that confirms this direction without changing the stated thesis.
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