๐—ช๐—ต๐˜† ๐— ๐—ผ๐—ฟ๐—ฒ ๐—”๐—ด๐—ฒ๐—ป๐˜๐˜€ ๐—ช๐—ผ๐—ป'๐˜ ๐— ๐—ฎ๐—ธ๐—ฒ ๐—ฌ๐—ผ๐˜‚ ๐—™๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ

Many people scale AI coding setups. They think more agents mean more speed. This is a mistake.

Adding agents without a plan increases chaos. You spend more time switching tasks.

Speed comes from clear rules. Move the handoff out of the chat window.

This keeps agents on track. It stops them from changing unrelated code.

Give agents isolated spaces. Use sandboxes or separate branches. Open SWE uses this method. Agents fail when they share one worktree.

Separate the worker role from the verification role. Google AI Studio uses checkpoints for this. This stops errors.

More agents increase your review cost. You hit a coordination limit long before you run out of compute.

Separate your planning from your implementation. Force agents to read from files.

If your handoff is not a file, you manage chaos.

Source: https://dev.to/hefty_69a4c2d631c9dd70724/why-throwing-more-agents-at-your-code-wont-make-you-faster-3m2o