This paper by Dennis Kennedy introduces a systematic methodology for transforming generic Large Language Models into specialized, persistent AI advisors and helpers through structured protocol frameworks and collaborative development processes, enabling reliable human-AI collaboration for complex decision-making across professional and personal domains. Large Language Models consistently underperform as specialized advisors due to context drift, personality inconsistency, and inability to prioritize curated knowledge sources. This paper introduces the Operational Protocol Method, a systematic approach for LLM specialization and assistance through structured persona engineering and collaborative development processes. The method transforms generic LLMs into reliable subject matter expert advisors while enabling coordinated multi-agent systems that maintain expertise boundaries across complex advisory tasks. Case studies in personal finance and note-taking demonstrate the method’s practical effectiveness and versatility across domains.

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