Published and updated 7 September 2026 · Altari Systems

Repository architecture

Git-Native Production for Autonomous AI Software

Abstract

Git-native AI software production treats immutable commits and a customer-owned repository as the durable code record. AI agents work in isolated candidate state, evidence refers to exact SHAs, and one integration authority advances the canonical history. The software remains portable beyond the orchestration platform.

01

The repository is the product record

Agent chats and vendor task logs are useful context, but they are not a portable source tree. Git preserves the code, history and exact identities conventional engineering tools already understand.

Nexus layers orchestration state around Git rather than replacing it.

  • Customer-owned remote
  • Immutable commit identity
  • Standard branches and diffs
  • Exportable history
02

Candidate and canonical state differ

A worker can create a technically valid commit without authority to publish it as the shared product. Review and integration are separate transitions.

This distinction keeps parallel AI agents from pushing competing interpretations directly into the canonical branch.

  • Isolated worktree
  • Evidence bundle
  • Exact-SHA review
  • Canonical integration
03

Failure modes and recovery

Stale baselines, merge conflicts and deleted workspaces are expected distributed-system events. Durable state records which candidate existed and why it was accepted or rejected.

A multi-agent Git workflow should expose conflicts for remediation, not hide them behind forced pushes.

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