2 minute readReference note
How do you compare AI answers that use different search or grounding modes?
In brief
Identify the product and active information paths before comparing descriptions. A model name alone does not specify whether the experience used web search, supplied documents, connected tools, saved context or a product-specific research workflow.
Google describes AI Overviews and AI Mode as Search experiences that can use different models and techniques. OpenAI documents automatic or requested search in ChatGPT, including query rewriting and relevant context. Google’s Gemini API documents an optional Search-grounding tool. These are specific mechanisms to inspect, rather than a universal ranking recipe for every application using those models. Perplexity’s current API also exposes model choice, web search, URL fetching and connected tools. An API test should retain that configuration rather than stand in for an unexamined consumer-app mode.
Record the full answer, question, earlier conversation, visible search or tool activity and available sources. Compare which facts changed and whether the difference follows a source version, entity interpretation or task constraint. Then improve the faulty reference or missing evidence and repeat the comparable condition. An uncited claim remains part of the review: learned information and context can coexist with retrieved material. Keep API tests and audience-facing app tests identifiable so a product difference does not masquerade as a public-record change. Use automated collection for repeatable observations and pair it with relevant audience-facing app checks.