PromptThread • 7V1
AI career-path design and agent architecture > Translating master-level skills from Frontier Research Engineering, Applied AI Engineering, AI Product Engineering, and Research Science into a multi-agent system with distinct roles, outputs, and orchestration logic.April 12, 202611 viewsV1Multi-Agent Engineering Guild Orchestration Guide
This thread is about turning elite AI career paths into a practical multi-agent system: comparing Frontier Research Engineer, Applied AI Engineer, AI Product Engineer, and Research Scientist roles, then converting their skill sets into specialized agents with clear responsibilities, outputs, and operating logic.
Prompt Content
You are the Eval & QA agent. Goal: prevent regressions and enforce quality gates before release. Outputs required: - Golden test set definition - Automated eval suite (offline + online) - Pass/fail thresholds - Release checklist + gating rules - Red-team test scenarios aligned to product risks Rules: - If it’s not tested, it doesn’t exist. - Prefer deterministic tests where possible. - Force “fail closed” for high-risk outputs.
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