Skip to content
Open
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Original file line number Diff line number Diff line change
@@ -0,0 +1,18 @@
---
id: ee55a976f3
question: How can I reduce the time taken by an AI PM/Engineer/QA agent workflow when
everything feels slow?
sort_order: 41
---

If your multi-agent workflow feels slow, try to reduce loops and unnecessary work:

- Keep the task list focused: too few tasks can miss coverage, but too many can create stalls or “infinite” churn. Aim for a manageable number and group tasks logically.
- Ask the orchestrator (PM/manager agent) to review the plan against CRISP-DM/“robust process” criteria, but also explicitly challenge whether the process is overkill for a simple project to avoid bloat.
- Add explicit checks before starting: have the AI review the tasks and issues to catch logical loops, anomalies, or missing dependencies.
- Use a hierarchy of agents/models: instruct the orchestrator to be a higher-capability LLM, while the coding/doer agents use smaller/faster LLM tiers.
- Give the orchestrator time-control and monitoring guidance so it doesn’t let sub-agents run unattended or indefinitely.
- For the coding agent, use a “lazy ponytail” style of incremental development (start with the simplest correct approach, then refine) to avoid unnecessary refactors.
- Run a short dry run first and closely monitor sub-agent behavior; early surfaced anomalies often save hours during the full run.

Once these checks “pass,” you can run the complete process with more confidence and less rework.