An open-source Agent Skill for problem framing and assumption testing across coding, debugging, architecture, scientific research, and product decisions.
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Updated
Sep 13, 2026
An open-source Agent Skill for problem framing and assumption testing across coding, debugging, architecture, scientific research, and product decisions.
Cursor skills and harness-oriented workflows for project intake, problem framing, and AI-ready task decomposition.
Free Agent Skills that pressure-test AI project ideas and diagnose running systems. From the AI Problem Framing course.
A well-defined problem comes FIRST. A problem-definition skill that interrogates until the problem is sharp, pins the constraints that channel creativity, and hunts the web for evidence of how others framed and solved it.
AI systems with a focus on NLP: retrieval‑augmented generation (RAG), agentic workflows, evaluation harnesses, and production patterns. This repo is the entry point to my portfolio.
Aperture Lite — frame the right problem before you build the AI. A public, lightweight version of Michael Joseph's Aperture method.
Focus Field: an executable orientation layer for locating the field, deriving the governing question, and keeping the next move valid.
Open research: first test whether energy density is the right problem. Review assumptions, compare alternatives, and reuse AI-readable records.
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