The agent loop
Understand goal → action → observation → decision before adding frameworks.
An agent is a loop with boundaries
An agentic system can choose an action, observe the result and decide what to do next. That flexibility is useful, but it also means you need explicit tools, limits and stop conditions.
What outcome is the agent trying to reach?
What actions is it allowed to take?
What result comes back from each action?
Continue, change course, ask for approval or stop?
Maximum steps, cost, scope or time.
Do not give an agent broader permissions than the task needs.
Actions that can publish, spend money, delete data or message people should use explicit limits and human approval.
Agent design is not “make AI autonomous.” It is designing a controlled loop with tools, observations and stop rules.