Joel, this is a strong and timely case for something a lot of people still get wrong: AI is not automatically a research system just because it can produce polished language on command.
That distinction matters.
What landed for me is the discipline behind the workflow. Build the knowledge base first. Control the sources first. Then let the model help you think, summarize, organize, and draft from inside that boundary. That is a much more mature framing than the usual “just ask AI better questions” advice.
I also like that you centered credibility instead of convenience. Speed is great. Trust is better. And for anyone publishing research, briefing leaders, or putting their name on a conclusion, that tradeoff is not academic.
Really useful piece. The phrase “anti-hallucination layer” is going to stick with me
Joel, this is a strong and timely case for something a lot of people still get wrong: AI is not automatically a research system just because it can produce polished language on command.
That distinction matters.
What landed for me is the discipline behind the workflow. Build the knowledge base first. Control the sources first. Then let the model help you think, summarize, organize, and draft from inside that boundary. That is a much more mature framing than the usual “just ask AI better questions” advice.
I also like that you centered credibility instead of convenience. Speed is great. Trust is better. And for anyone publishing research, briefing leaders, or putting their name on a conclusion, that tradeoff is not academic.
Really useful piece. The phrase “anti-hallucination layer” is going to stick with me
Very well said! Credibility is so valuable and often valued only once it’s lost