Bounded work
Tasks and AgentJobs
The system narrows work into auditable packets with explicit allowed paths, expected outputs, validators, and claim boundaries.
AI research-agent track
The AI research-agent system is the governed, human-accountable workflow used to plan, check, preserve, and review theoretical physics work. Its workflow evidence can organize research; it does not become physics proof by itself.
System model
The AI system is a research discipline: it makes work inspectable, repeatable, and harder to overstate. Scientific claims still require source artifacts and gates.
Bounded work
The system narrows work into auditable packets with explicit allowed paths, expected outputs, validators, and claim boundaries.
Authority
Roles and skills orient work, but task-local execution records and allowlists decide what a specific transaction may do.
Review
Proposals, stress tests, completions, handoffs, and human gates keep workflow progress separate from physics proof.
Memory
Memory, wiki, registries, and local search help find sources. They do not replace registered source files or authority rows.
Where to go next
The Phase 5 AI research-agent deep-dive routes are available as a coherent first version after source inspection and QA: workflow, roles and skills, memory and registries, and validator/operator workflow.
Phase 5A / implemented
Phase 5B / implemented
Phase 5C / implemented
Phase 5D / implemented
Source authority
This page can describe the AI-assisted workflow. It cannot expand role authority, change routing behavior, promote physics claims, or replace human-gated publication, authorship, and outreach responsibility.