SQL-Shaped Intent: The Engineering Behind AgentQL

Our CEO recently wrote reaffirming an architectural decision ThoughtSpot made when LLMs first emerged: we do not use LLMs to directly generate SQL . My team has spent the better part of a year building AgentQL : a capability that doubles down on our decision. So let me explain what we actually built, why it doesn't just honor that architectural decision but depends on it, and the engineering choices underneath. The Problem We Were Handed: The Expressibility Gap Spotter answers most questions through search tokens : a structured, readable representation of intent that a business user can inspec