Question about subagents
The user is trying to use subagents to increase their token usage, but is encountering issues with false positives and subagents not having the full picture.
Why it matters
This article highlights the challenges users may face when trying to optimize their token usage through the use of subagents, and the importance of maintaining a holistic view when working with AI assistants.
Key Points
- 1The user is on the Max20 plan and uses Claude Code extensively, but only uses about 50% of their quota
- 2The user created 4 specialized subagents to help with code review, but 90% of the bugs they found were false positives
- 3The user finds that Claude Code performs best when used in the traditional way, with the full picture
- 4The user is looking for ways to harness the power of subagents and burn more tokens while doing real work
Details
The user is an avid user of Claude Code, using it extensively throughout the day. However, they are only using about 50% of their token quota on the Max20 plan. In an effort to increase their token usage, the user has learned about subagents and created 4 specialized subagents to assist with code review. The subagents were each focused on a specific aspect of the code, but the user found that 90% of the bugs they identified were false positives. This is because the subagents only had a partial view of the codebase and lacked the full picture that the user gets when using Claude Code in the traditional way. The user is now looking for ways to effectively harness the power of subagents while still maintaining the accuracy and performance of the traditional Claude Code usage.
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