AI Engineering Workflow Orchestrator

Context

An AI engineering workflow that coordinates software delivery across specialized models and agents. The workflow separates research, planning, implementation, testing, review, and correction into explicit stages, with approval gates and independent review between phases so generated changes remain inspectable and accountable.

Role and scope

AI engineer: designed the staged workflow, agent responsibilities, approval gates, review process, and correction loop.

Challenge

AI-assisted software work can become difficult to review when research, implementation, and validation happen in one opaque step. A repeatable workflow was needed to separate responsibilities and make quality gates explicit.

Approach: Built a staged orchestrator that routes work between specialized agents, preserves phase outputs, pauses for approval at defined gates, and uses independent review and correction passes before completion.

Key decisions and trade-offs

• Separated planning, implementation, testing, and review so each stage produces an inspectable artifact.
• Added explicit approval gates so human judgment remains part of high-impact workflow transitions.
• Used independent review and correction phases to catch issues that a single implementation agent may miss.

Outcome

• Creates a repeatable workflow for research, planning, implementation, testing, review, and correction.
• Makes agent handoffs and approval points visible instead of hiding them inside one prompt.
• Supports independent review before changes are considered complete.

Stack

Stack used in this system · AI engineer