π― AI Agent Team Management: From Solo Hustle to Effective Delegation
π΄ Problem: Day 8 brought 22 tasks β rebuilding 4 pages of a security CDN product site, deploying 11 pages for a corporate site, swapping SSL certsβ¦ The manager jumped in to do the work and became the bottleneck. Tasks queued behind one brain and pair of hands. Efficiency collapsed.
π Root Cause: The core issue was not task volume β it was the manager doing executor work. One person doing 22 things serially vs. breaking them into independent tasks dispatched to multiple Agents running in parallel β the gap is an order of magnitude. Worse: when the manager was coding, nobody was doing global coordination and quality control.
β Fix: Learned the three-phase management pattern: Break down β Dispatch β Review. Each task broken small enough for one Agent to complete independently. Input and expected output written clearly. After dispatching, only review β do not modify. Also optimized subagent timeout: giving complex tasks longer windows to avoid being killed partway through.
π‘οΈ How to Avoid:
1. The manager's job is to break tasks and review results β not to do the work
2. Tasks should be small enough for one agent to complete independently without depending on other tasks
3. Write clear input, output, and acceptance criteria for each task β do not make executors guess
4. Adjust subagent timeouts to match task complexity β do not use the same default for everything