Leonie Monigatti

Agentic Search Needs Specialized Tools and General-Purpose Escape Hatches

Elastic’s Leonie Monigatti argues that context engineering for LLM agents is largely a search-interface problem: the critical question is how an agent decides what to retrieve from files, databases, memory, the web, and other sources before the model answers. In her workshop, she shows why semantic search, database query tools, shell access, and agent skills each solve different parts of that problem and fail in different ways. Her recommendation is to build retrieval stacks that combine easy specialized tools for common tasks with more general tools for ambiguous or complex ones, then use observed failures to refine the stack.