Methods, Guides, and Strategic Insights. Evidence-based resources to elevate your research practice.
The biggest mistake teams make with AI is treating it like a magic black box. Here is a complete, reliable workflow for using LLMs as research assistants while maintaining critical human oversight.
Transform interview transcripts and observation notes into actionable themes through systematic coding. The difference between an opinion and a finding is whether two people agree.
AI is fundamentally changing what research roles look like. Some purely executional positions are already disappearing. Understanding what LLMs actually are, and are not, determines whether you use them effectively or get replaced by someone who does.
Beyond basic prompting, there are techniques that dramatically improve AI reliability: structured communication, using notes over transcripts, treating models as a committee of raters, and understanding when RAG or fine-tuning makes sense.
Don't write a report in a vacuum. How to facilitate a workshop that forces your team to own the insights and commit to action.
Good research is not a series of disconnected activities, it is a cohesive process that transforms business questions into actionable insights. This is the map for that journey.
Don't just report averages. How to clean data, visualize distributions, and calculate statistical significance.
Everything we know about running research that actually changes products — packed into one honest, practical guide.
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