IQ GPT

My work on IQ GPT grew out of a familiar difficulty in crypto research: finding information is only the beginning. A question can lead across documentation, market data, project announcements, and a conversation in which everyone assumes a different amount of background knowledge. The effort of assembling that context can become larger than the question itself.

I worked on bringing relevant information into a conversation that people could use to investigate a topic. The underlying idea was to reduce the distance between asking a question and reaching evidence that helps answer it. That requires attention to what the person means as well as to the material available.

A question about a protocol, for instance, might be asking how it works, how much activity it has, or why something recently changed. Those questions call for different evidence. A broad description can explain a mechanism while leaving a question about current conditions unanswered. Useful assistance starts by identifying the kind of answer being sought.

Financial information also changes with time. A description that was correct at publication can become misleading after a change in a protocol or its market. Even when the facts remain current, two sources may use different definitions for what looks like the same metric. An answer needs to retain enough of that context for the reader to judge whether the information fits the question.

This is why references matter beyond making an answer look well supported. A reader should be able to follow the claim back to its source, examine the original context, and continue the research. When the available material does not settle the question, the answer should leave that uncertainty visible. The conversation is more useful when it helps someone understand the limits of what they have learned.

Working on IQ GPT also made me think about where research happens. People ask questions inside communities and ongoing discussions, often before they know which specialist source to consult. Bringing useful research into those settings can help them get far enough to ask a more precise next question.

That earlier work shaped how I now approach financial AI. I care about whether an answer changes a person’s understanding in a way they can check. A fluent explanation is helpful, but its lasting value comes from connecting the person to the evidence, the meaning of the terms, and the next question worth investigating.