Tools: Stop Building Reactive Agents: Why Your Architecture Needs A System...

If you’ve built an LLM agent recently, you’ve probably hit the "autonomy wall."

You give the agent a tool to search the web, a prompt to "be helpful," and a task. For the first two turns, it looks like magic. On turn three, it goes down a Wikipedia rabbit hole. On turn ten, it’s stuck in an infinite loop trying to fix a syntax error on a file it never downloaded.

Most developers try to fix this by cramming more instructions into the system prompt: "Never repeat the same action twice! Think step-by-step!"

But the problem isn’t the prompt. It’s the architecture.

You are forcing a single execution loop to do two completely different jobs: talking/acting (which requires low latency and high bandwidth) and planning (which requires slow, deliberative reasoning).

We need to borrow a concept from human psychology—Daniel Kahneman’s Thinking, Fast and Slow—and build Dual-Process Agents.

Most standard agents (like a naive ReAct loop) operate in a flat sequence: Observe -> Think -> Act -> Observe -> Think -> Act

When the agent is "thinking," it is trying to decide what to say to the user and what its long-term strategy should be. Because LLMs are autoregressive, the immediate context (the last thing the user said, or the last API error) overwhelmingly dominates its attention.

If the agent’s only "planner" is the exact same loop that’s doing the work, you get two failure modes:

A dual-process architecture explicitly separates the "doer" from the "planner."

Source: Dev.to