Robert Ta argues founders waste time on user research and shows how AI can speed it up. Record interviews, transcribe them, then run the transcripts through structured frameworks like Opportunity Solution Trees and Jobs-to-be-Done to extract causal structures and generate prioritized experiments.
You could save thousands of hours in research and product work with AI. When you do user research interviews, ask for consent to record, take the transcription afterwards. Use that against a framework like Teresa Torres Opportunity Solution Trees Framework or Bob Moista's Jobs to be Done framework because it provides structure to slightly unstructured data. And so one example with Bob Mwesta's Jobs to Beyond Framework is I have a highly tuned prompt that I use after every interview that takes in an input and it gives me an output with the causal structures that got the user to this struggling moment with their quotes that tie to emotional jobs to be done, social jobs to be done and functional jobs to be done. And then it creates a set of prioritized future experiments to drive the product towards solving those pain points based on the causal structures identified from the interview. If you want this prompt, comment the word prompt and I'll send you a link to my highly tuned prompt.
