writing
Open deep hub →Multi-model workflows for writing
Separate planning, canon extraction, drafting, criticism, editing, and final review without producing a pile of unrelated rewrites.
Deep practice hubs
Different work.
One coherent outcome.
Each hub maps a real problem into staged ownership, review, safeguards, authored recipes, relevant roles, and task documentation—without publishing user projects or DecaCap’s proprietary training design.
games
Open deep hub →Multi-model workflows for games
Coordinate narrative, systems, environments, assets, QA, performance, and deployment around one playable slice.
software
Open deep hub →Multi-model workflows for software
Make architecture, implementation, adversarial review, testing, security, operations, and release evidence part of one flow.
research
Open deep hub →Multi-model workflows for research
Use separate evidence, verification, and challenge stages to produce one transparent conclusion instead of model consensus theater.
education
Open deep hub →Multi-model workflows for education
Keep learning objectives, instruction, practice, assessment, answer verification, and accessibility aligned to the same source.
private ai
Open deep hub →Private and local-first AI workflows
Run compatible text models from user-owned hardware, keep local connection details in the browser, and train only through explicit GoldCap actions.