The typical default is one call to one model, and when that gets expensive, we cascade to something cheaper. Both accept the same premise: the input is one question. Usually, it isn't. A single photo, document or utterance carries several distinct questions, and one model answering all of them hands you its weakest answer in its most confident voice, at full price, every time. A cascade only changes the price. This talk makes the case for treating the input as a routing problem. Cheap classifiers decide which question you have, and each question goes to the model genuinely best at it, including the times the honest answer is that no model should answer. In our case we brought token spend under control, took a seventeen second wait down to under a second on the path that can prove its answer, and cut wrong answers from 25% to near zero.
Geoff Niehaus is the founder of Today Mechanic, an AI-powered platform that keeps auto repair shops' bays full by handling the customer conversation before the car ever reaches the lift. He spent the last four years at CVS Health (via Oak Street Health), most recently as Executive Director of Software Development Engineering, where he oversaw a program of 100+ engineers and led delivery of a production applied-AI system (retrieval over millions of clinical documents feeding an LLM) that lifted suspect-finding identification by 30% under HIPAA constraints and human-in-the-loop clinical validation. He also embedded AI-assisted development into the standard SDLC, pairing coding agents with a contract-first "Design First" practice that took code coverage from 40% to 80%+. He's a founding member of the Austin CTO Club and holds a pending patent for multi-tenant medical record access.
