Every Agent Framework Ships the Same Loop

LangGraph. CrewAI. Google ADK. OpenAI Agents SDK. They all ship the same loop.

Think. Act. Observe. Repeat.

LangGraph wraps it in a state graph. CrewAI wraps it in crews and tasks. Google ADK wraps it in agent classes and runners. OpenAI Agents SDK wraps it in agents and handoffs.

Different packaging. Same engine.

Peel back the layers:

→ "Orchestration" is deciding what runs next, and handling when it fails → "Memory" is what persists between iterations → "Planning" is the model reasoning before acting → "Tool use" is act() connecting to external systems

Multi-agent? That's loops coordinating with other loops.

Frameworks add real value such as retry logic, routing, context management, guardrails. I use them daily.

But the teams I see struggle the most are the ones debugging the framework when the problem is in the loop. Sometimes they don't even figure out the issue comes from it because they don't understand it.

A study on coding agents analyzed 9,374 trajectories across 8 frameworks and 14 LLMs. Agents sharing the same LLM produced similar results far more often than agents sharing the same framework. The agents that succeeded most were the ones that gathered context before editing and validated after. Think. Act. Observe.

Choosing the right model matters more than choosing the right framework.

Start with the loop. Understand what breaks it. Add complexity only when the loop demands it.