Optimise Your LLM Workflow with the Chief Wiggum Workflow (etoxin.net)

A new workflow called the WIGGUM Workflow, or Weighted Incremental Grouping for Greater Usage Management, has been introduced to help users optimize their engagement with language models (LLMs) like Claude and GitHub Copilot. Users now face strict limits on request numbers based on their subscription plans, which can lead to exceeding these limits quickly. The WIGGUM Workflow offers a structured way to manage tasks efficiently by utilizing a Markdown file where users can categorize tasks into phases. When prompted, the LLM processes the requests in bulk, marking completed items and acting like a primitive state machine, streamlining task management. This innovation is significant for the AI/ML community as it enhances the practical utility of LLMs in project management and software development, allowing for greater task throughput without exceeding request caps. By dividing work into manageable phases and leveraging LLMs more effectively, developers can maintain productivity over the month while ensuring tasks don’t pile up. The WIGGUM Workflow represents a creative solution to existing limitations, making AI tools more accessible and functional for technical users in a fast-paced development environment.