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- 🤔 Your Research Tools Got Smarter... Did You? + 🧠 AI Analysis You Can Actually Trust
🤔 Your Research Tools Got Smarter... Did You? + 🧠 AI Analysis You Can Actually Trust
This week: How to Do AI Analysis You Can Actually Trust; Your Research Tools Got Smarter... Did You?; How AI Literacy Shapes GenAI Use. Our video pick this week is This AI Expert's Method Will Change How You Do Customer Research, plus the latest job opportunities in research. And finally — join Research Lunch Club, now live in 10+ cities, before we send out our latest round of matches tomorrow!
People of Research
February 26, 2026
🎤 Community & Newsletter Updates
Two things before we get into this week's reads.
First — we're back to weekly editions. Feels good.
Second — Research Lunch Club sends its next round of matches tomorrow, and there's still time to get in on it. We're matching researchers in trios across 10+ cities for in-person lunches. Real conversations, real connections, no awkward conference nametags.
Last week a group of researchers in Seattle did exactly this. Here's how it looked 👇
If that looks like your kind of afternoon:
📰 Article Picks
🔗 How to Do AI Analysis You Can Actually Trust: Caitlin Sullivan argues that AI analysis of customer data frequently fails due to fabricated statistics and generic outputs — problems she identified across 2,000+ hours of testing AI-powered customer discovery workflows. Sullivan, a user research veteran who has trained hundreds of product and research professionals, outlines four prompting techniques to prevent these failures: understanding and identifying the two main types of AI hallucinations, selecting the right LLM for analytical tasks, structuring prompts to extract specific and grounded insights, and applying a final verification pass to stress-test findings before sharing them. Her core argument is that vague or generic AI outputs are a prompting problem — one that can be solved systematically.
🔗 Your Research Tools Got Smarter… Did You?: Josh LaMar argues that the commodification of research data collection — driven by AI platforms like Maze, Dovetail, Outset AI, and Listen Labs — is not a threat to researchers, but a clarifying moment. LaMar, a product growth strategy and AI advisor with over 40,000 hours of customer research experience, draws on market projections (the AI-based research services market is expected to grow from $8 billion in 2025 to over $35 billion by 2035), a Displayr study showing 85% of researchers report improved workflows from automation, and academic literature warning of the "McDonaldization" of qualitative research. His central argument is that data collection has never been the hard part — strategic synthesis is. He identifies five domains where human researchers remain irreplaceable: cross-input strategic synthesis, stakeholder relationship management, cross-cultural depth, complex qualitative methods, and AI decision advisory. He closes with a three-question self-assessment framework for researchers to diagnose which side of the automation line their work sits on.
🔗 How AI Literacy Shapes GenAI Use: Maria Rosala for Nielsen Norman Group reports findings from an observational study in which participants of varying AI experience were asked to conduct research tasks using both traditional web search and generative AI tools, without being told the study was focused on AI behavior. The article introduces two distinct competencies that determine how effectively people use genAI: prompt fluency (the ability to communicate intent and constraints clearly) and output literacy (the ability to critically evaluate AI responses, spot hallucinations, and know when to independently verify). Key findings include that prompt fluency tends to develop faster than output literacy, and that highly literate users engage with AI more selectively — choosing different models for different tasks and verifying outputs when accuracy matters. The article argues that simply using AI frequently does not equate to using it well, and that output literacy is an underappreciated but critical skill for anyone working with generative AI tools.
🎙️ Video Pick
💼 Job Picks
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