EXTENDED_ECOSYSTEM_MAPPING: AI CODING AGENT / DEVELOPER WORKFLOW

Cursor / AI Coding Agents

A source-qualified lifecycle governance mapping for Cursor and AI coding-agent workflows, extending the existing AI Coding Agent Auditability playbook.

BOUNDARY_NOTE

Independent lifecycle governance lens.

This page is independent lifecycle governance analysis. It is not Cursor documentation, Cursor affiliation, product scoring, legal advice, certification, legal compliance proof, or procurement guidance.

These pages apply GAIC lifecycle governance concepts to extended ecosystems. They are not GAIC scored assessments, vendor rankings, procurement recommendations, certifications, legal compliance proof, official vendor documentation, or vendor affiliations.

Ecosystem context

Cursor is treated here as an AI coding-agent ecosystem. The mapping focuses on repository scope, autonomous or semi-autonomous edits, command execution, branch or handoff evidence, review state, and accepted outcome.

R3F relies on official Cursor documentation only for the existence of Cursor agent workflow surfaces. It does not score, rank, or evaluate Cursor products.

Lifecycle governance questions

  1. What authority boundary governs consequential work?
  2. What evidence chain survives tool, model, agent, or runtime action?
  3. What accepted outcome state is defined, and who may accept it?
  4. How are rollback, remediation, dispute, and substitution handled?
  5. Which human or organizational role owns lifecycle responsibility?
  6. Which branch, workspace, or machine boundary is used for agent work?
  7. What test, lint, review, and handoff evidence is required before acceptance?

Related Missing Regulatory Objects

These concepts are governance lenses for the mapping. This page does not claim the ecosystem has or lacks a feature unless the statement is supported by an official source.

Authority BoundaryEvidence ChainAccepted OutcomeLifecycle Responsibility ObjectsSubstitution recordDispute objectRemediation closure

RCCS-M / ALCS relevance

RCCS-M is relevant as a governance-coverage lens for lifecycle responsibility objects. ALCS is relevant as a lifecycle-coherence lens across intent, authority, evidence, acceptance, dispute, remediation, and closure. This R3F mapping is author-analytical and source-qualified, not a GAIC-scored assessment.

Harness Engineering relevance

Harness Engineering is central for coding agents because the harness must keep plan, file changes, commands, tests, review, rollback, and accepted outcome connected.

Protocol path

MPLP is one protocol path for expressing lifecycle responsibility semantics around agentic work. It is not required, exclusive, certified, regulator-approved, vendor-affiliated, or already an industry standard.

WHITE_PAPER_SOURCE_TRACE ADJACENT

White paper source trace

Cursor / AI Coding Agents is treated as an adjacent coding-agent workflow mapping with added evidence-validation and remediation-closure source context.

This page is adjacent to GAIC, not a GAIC-scored assessment. It uses MRO, RCCS-M, and ALCS as lifecycle governance lenses for an ecosystem context established by official sources.

Use the trace to ask how tool access, agent delegation, model/runtime substitution, evidence, accepted outcome, rollback, and remediation would survive across the workflow.

This mapping is source-qualified and non-GAIC-scored. It is not vendor documentation, vendor affiliation, product scoring, legal advice, certification, legal compliance proof, procurement guidance, or a claim that MPLP is required.

Official sources consulted