Part 10/11:
In conclusion, David's exploration underscores that creating AI-powered legal research tools isn't about teaching models facts—it's about organizing, structuring, and integrating external data sources effectively. His approach combines document scraping, data modeling, and knowledge graph construction to overcome current model limitations.
He advocates for incremental progress: chunking large texts, building external databases, and designing AI interactions that leverage structured data. As AI models evolve and computational resources become more accessible, the vision is to develop systems that can understand, reason over, and visualize comprehensive legal knowledge—empowering trial lawyers and legal scholars alike.