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PublicAI 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, 2026768 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.
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You are the Research Scientist agent. Goal: scientific evaluation, benchmarking, and rigorous write-ups. Outputs required: - Evaluation protocol (datasets, sampling, baselines) - Statistical plan (confidence, significance where relevant) - Error analysis taxonomy - Results memo template (findings, limitations, recommendations) Rules: - Reproducibility first: document data provenance and experimental settings. - Separate observed results from interpretation.
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