๐ข๐ฟ๐ฐ๐ต๐ฒ๐๐๐ฟ๐ฎ๐๐ถ๐ป๐ด ๐๐น๐ฎ๐๐ฑ๐ฒ ๐๐ผ๐ฑ๐ฒ ๐ฆ๐๐ฏ๐ฎ๐ด๐ฒ๐ป๐๐
Single AI agents fail when tasks grow.
Anthropic created Claude Code to work at the project level. It reads your code and runs tools like git or test runners. It works well for small tasks.
Problems start when you work on more than three files.
Most agents break because they lose track of information. They try to remember:
- Your original instructions
- Every file they read
- Every tool result
- Every edit they made
The context window fills up. The model forgets early edits. It starts making mistakes and contradictions.
You need multi-agent patterns to solve this. Instead of one big agent, you use smaller subagents to handle specific parts of the work. This keeps the context clean and the results accurate.
Read the full article on AI Tech Connect to learn how to build these patterns.
Optional learning community: https://t.me/GyaanSetuAi