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Nurture-First Agent Development: Building Domain-Expert AI Agents Through Conversational Knowledge Crystallization
🤖AI Summary
Researchers propose Nurture-First Development (NFD), a new paradigm for building domain-expert AI agents through progressive growth via conversational interaction rather than traditional code-first or prompt-first approaches. The method uses a Knowledge Crystallization Cycle to convert operational dialogue into structured knowledge assets, demonstrated through a financial research agent case study.
Key Takeaways
- →Traditional code-first and prompt-first AI agent development approaches create mismatches with the tacit, personal, and evolving nature of domain expertise.
- →Nurture-First Development initializes agents with minimal scaffolding and grows them through structured conversations with domain practitioners.
- →The Knowledge Crystallization Cycle periodically consolidates fragmented conversational knowledge into reusable structured assets.
- →The framework includes a Three-Layer Cognitive Architecture organizing knowledge by volatility and personalization levels.
- →A financial research agent for U.S. equity analysis serves as the primary demonstration of the NFD paradigm.
#ai-agents#llm#knowledge-management#conversational-ai#domain-expertise#agent-development#machine-learning#research#financial-ai
Read Original →via arXiv – CS AI
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