Start with one question.
Practical guides for making AI agent and multi-agent workflows more rollbackable, verifiable, auditable, and lifecycle-governed.
- 01Question index
- 02Applied playbooks
- 03Source routes
- 04Boundary
Choose a question, then follow the evidence.
Each playbook starts from a real agent-work question and routes through governance language, lifecycle objects, and bounded evidence.
- 01External baselineContext and requirements
- 02Control languageInternal interpretation
- 03Lifecycle objectResponsibility and authority
- 04EvidenceTrace, review, acceptance
Applied governance for real agent-work questions.
These playbooks connect Agentic Lifecycle Governance, Missing Regulatory Objects, RCCS-M, ALCS, and MPLP to practical search intents: rollback, verification, auditability, coding agents, human role responsibility, vendor and runtime substitution, Harness Engineering, prompt-vs-harness boundaries, agentic delivery architecture, and insurability / risk-transfer discussion. The auditability and assurance white paper supplies the auditability layer while the insurability and risk transfer white paper supplies the public research edition insurability layer; neither turns these playbooks into published implementation or underwriting guides.
AI Agent Rollback and Verification
A lifecycle governance playbook for making AI agent rollback, verification, evidence chains, accepted outcomes, and remediation closure inspectable.
Open playbookAI Coding Agent Auditability
A lifecycle governance playbook for making AI coding agent work reviewable, reversible, test-evidenced, and accepted by accountable human roles.
Open playbookHuman Role to Multi-Agent Responsibility Mapping
A governance playbook for mapping human roles, delegated authority, accepted outcome ownership, dispute handling, and remediation in multi-agent systems.
Open playbookHarness Engineering for AI Agents
A definition-first playbook for Harness Engineering: wrapping AI agent execution with context boundaries, authority boundaries, evidence capture, plan/confirm/trace records, rollback, remediation, deterministic delivery, and accepted outcome.
Open playbookPrompt Engineering vs Harness Engineering
A lifecycle governance playbook explaining why prompt engineering controls intent expression while Harness Engineering controls execution boundaries, evidence, rollback, and accepted outcome.
Open playbookAgentic Delivery Architecture Checklist
A practical architecture checklist for accountable AI agent workflows: intent, context, authority, tools, evidence, accepted outcome, rollback, substitution, and human responsibility.
Open playbookThese pages are independent lifecycle governance playbooks. They are not official vendor documentation, legal advice, legal compliance proof, certification, regulator-approved guidance, vendor rankings, or procurement recommendations. They define lifecycle governance practice; they do not claim deterministic model outputs or guaranteed delivery.