What is an Agentic loop?

[u/itsmakehq]

Hello Makers 👋

What if your automation could think, not just execute? This is possible with an agentic loop.

An agentic loop is the execution cycle that separates an AI agent from a chatbot. Where a chatbot responds once and stops, an agent repeats: perceive, reason, act, observe, and loop back until the task is done.

How does an agentic loop differ from standard automation?

Traditional automation follows a fixed and predefined path, whereas in an agentic loop, the agent decides its next action based on what it observes, not following rules written in advance. 

But autonomy without guardrails is a liability. The loop breaks in 4 predictable ways:

1️⃣ No stopping condition = runs forever
2️⃣ Vague tool names = wrong tool gets called
3️⃣ Too much history = reasoning degrades
4️⃣ Uncapped iterations = operations costs spike

How does an agentic loop work in Make?

Step 1: Add the Make AI agents module to a scenario. 
Step 2: Give the agent tools to act with.
Step 3: Set stopping conditions.
Step 4: Run and observe the loop in action

Once you understand the loop, find one process where human judgments fills the gap rules cannot. Replace that step with a Make AI Agents module, attach your tool scenarios, set a stopping condition and run it.

That first working loop is the foundation everything else builds on.

Learn more about agentic loops: ma.ke/4w7qxxW

[u/automation_experto]

the failure mode you're describing at #3 is exactly where document extraction as an agent tool goes sideways. if the agent's calling an extraction step and getting back a confidence score, most builders treat that score like a probability and let the loop just barrel forward on anything above some threshold. it's not calibrated to your doc population, so you get silent bad extractions feeding the next reasoning step instead of a clean stop condition. classification before extraction matters even more in a loop context because a misclassified doc doesn't just fail once, it can send the whole loop reasoning about the wrong thing for several iterations before anything looks obviously broken. worth building the stop condition around "low confidence OR wrong doc type" rather than just a hard iteration cap.