Tribloc | Claude Code & Multi-Agent Engineering Workflows

PROBLEM Parallel AI coding needs clear task ownership, bounded access and verification before changes are accepted.

ARCHITECTURE A high-level workflow connects scoped task definitions, isolated agent workspaces, pull requests, automated checks and human release decisions. Claude Code, OpenAI Codex and GitHub support AI-assisted delivery. This public overview omits internal infrastructure and access details.

MY ROLE As Tribloc's founder, I defined requirements, directed architecture, coordinated agents and controlled acceptance decisions. Most implementation code was generated or revised with AI coding tools; design analysis was also AI-assisted.

IMPLEMENTATION Implemented components cover task routing, workflow controls, workspace isolation and review practices. I organised bounded implementation tasks around explicit acceptance criteria and documented handovers.

VALIDATION The October 2026 source-based case study records routing and launch-control code, automated regression checks and versioned review policies. It is a historical documentation review, not a fresh full-suite run or independent audit. Implementation, review, deployment and live verification are separate gates.

OUTCOME A reviewable foundation for coordinating AI-assisted engineering tasks. The persistent autonomous swarm is not established as a fully deployed live service; planned orchestration features remain subject to validation. No productivity or cost-saving percentage is claimed.

MEDIA The workflow diagram is a public-safe conceptual summary of the documented process, not an internal deployment map. The video illustrates orchestration and recovery; it is not a production recording.

CLIENT RELEVANCE Claude Code workflow setup, multi-agent architecture audits, task isolation, review controls and scoped implementation milestones.