Decision-state diagnostics for applied AI workflows
Decision-PGA is a prototype framework for describing the shape of uncertainty around AI decisions before a workflow acts. This site gathers the article series, a synthetic demo, the agent toolkit, the public code repository, and PDF copies.
What This Site Is For
This site is a compact public entry point for Decision-PGA: the framing article, the Telescoping Decision-PGA companion perspective, the synthetic document-triage demo, the agent toolkit, the open-source prototype repository, and PDF versions of the articles.
Article
The article explains why workflow-oriented AI systems need diagnostics for the shape of decision uncertainty.
Telescoping Decision-PGA
The follow-up perspective shows how broad uncertainty clouds can contain smaller local substructures and cross-document evidence bridges.
Synthetic demo
A document extraction triage fixture shows how probability clouds can map to workflow actions.
Agent toolkit
A five-minute path shows CLI, Python API, MCP launch, and synthetic agent payloads for developers who want to try the diagnostic contract in their own workflow vocabulary.
Public code
The initial Decision-PGA prototype is available at github.com/zmichels/Decision-PGA.
A browser-rendered PDF is included for readers who prefer a document-style copy of the article.
Current Status
- Article series and PDFs: available for public reading and critique.
- Demo: synthetic, non-clinical, and designed to build intuition.
- Toolkit: copy-paste agent examples and a local MCP quickstart.
- Code: public initial research release at https://github.com/zmichels/Decision-PGA.