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AI Agents and Automation
WTF Is an Agent Loop?
Everyone in AI is suddenly saying "loops" and almost nobody explains it. When to automate fully and when to stay in the loop, clear breakdown.
Everyone in AI is suddenly saying "agent loop" and almost nobody explains what it actually means. An agent loop is a cycle where an AI takes an action, observes the result, and decides what to do next, repeating until the task is done. That feedback cycle is what separates agents from chatbots.
How to do it
- 1The four components: Plan (what to do), Act (execute), Observe (what happened), Reflect (what next). An agent cycles through all four
- 2A chatbot runs one turn: you prompt, it answers, done. An agent runs as many turns as needed until the goal is met
- 3Tools give the loop capability: web search, code execution, file access, and API calls are what the agent acts with between reasoning steps
- 4Know when to stay in the loop: financial transactions, irreversible actions, creative decisions, anything with legal or reputational consequences
- 5Know when to let it run: repetitive research, data compilation, content drafts, report generation, lead qualification
- 6Most current AI tools marketed as agents are actually single-turn wrappers. They look like agents but have no loop
Why it works
The loop is not a feature, it is the architecture. Once you understand why it matters, you can immediately see which AI products are worth investing time in and which are just dressed-up chat windows with a marketing budget.
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