You ask an agent to research three options and recommend one.

It gathers facts. Compares notes. Second-guesses itself. All of that lands in its context window.

Then it has to write the answer, with its attention split across everything it tried along the way.

The agent isn't too dumb. It's too cluttered.

If you've built anything agentic, you've hit this ceiling. Here's how subagents fix it, and how we run them in ByteChef , an open-source workflow automation and AI agent platform built on Java and Spring.

Two problems, one fix

The Spring AI team names both problems in their subagent post :

Context pollution. Intermediate steps cloud the main agent's reasoning.

The generalist bottleneck. One prompt tries to be good at every kind of work.

The fix is delegation. The main agent becomes an orchestrator. It hands focused jobs to subagents and keeps only what they report back.

Each subagent works in its own context, with its own instructions, model and tools.…