A B2B outbound product successfully replaced an LLM with web search for finding company websites and phone numbers with a deterministic Places API lookup. This change improved website completeness from 34% to 81% and phone number accuracy to 91%, while reducing LLM costs to zero. The LLM's unreliability, including inventing domains and providing inconsistent answers, necessitated this shift. Separately, the concept of a 'Decision Layer' for agentic AI is emerging, distinct from LLM capabilities, with examples like TypeSafe AI's Jev and OpenAI's Decisions API suggesting a new architectural pattern focused on making specific choices rather than general token generation. AI
IMPACT Highlights the need for deterministic solutions over LLMs for specific tasks in B2B products, potentially reducing costs and improving reliability, while also pointing to new architectural patterns for AI agents.
RANK_REASON The cluster discusses practical applications and limitations of LLMs in B2B products and introduces a new architectural concept for AI agents, fitting the 'tool' category.
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