👋 Hasin I. Ahmed

"Qualitative UX is a scientific discipline, and we should treat it with the respect and standards it deserves." - Mohsen Rafiei, Ph.D. I regularly admit to my teams that I am newbie qualitative researcher. I only started conducting qualitative studies 6 years ago and have heavily relied on my colleagues to train, guide, and check my work. Qualitative is a scientific discipline with theory, rigor, and guidelines that deserves its own standing. 👏

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Such a great post, sharing lessons learned by Akshan Ish. For anybody interviewing for senior design roles, or just presenting a great story, take a look. There aren't many resources helping senior / principal / staff designers prepare for interviews, so sharing 10+ experience from both sides of the table, is gold. https://lnkd.in/d4XprbS2

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9 Powerhouse Women Shaping the Future of UX Research + AI After 20 years in UX research, I am optimistic to see how much our field is continuing to evolve. As AI is reshaping our tools, it is also shifting how we think about strategy, ethics, and the role of research. I am most excited about the collective wisdom we can share and learn from each other to move the industry forward together. Here are nine powerhouse women in the UX research space guiding the future of our industry: 1. Andrea Knight Dolan, UX and AI Strategy Consultant, Assistant Professor, University of Toronto Andrea was an early inspiration of mine in the AI and research space. Her groundbreaking work convinced me two years ago that AI would transform the UX research practice. 2. Kyle Soucy, Founding Principal, Usable Interface Kyle is pioneering AI-assisted personas and journey maps and demonstrating that AI innovation is strongest when it's grounded in robust UX practices. Kyle also boosts the UX industry through her must-listen podcast, The UX Consultants Lounge. 3. Fatimah R., Salesforce (ex-Google DeepMind) Fatimah is reimagining UXR as strategy, not just deliverables, championing research at the leadership level. She exemplifies how to bring anthropology, human factors, and AI research together to guide strategy and inclusion. 4. Meena Kothandaraman, Co-Founder, twig+fish twig+fish's NCredible Framework has changed how teams think about framing research questions and aligning stakeholders. Meena consistently reminds us that clarity is the foundation of any strategy. 5. Caitlin Sullivan AI Research Educator and Consultant Through her courses and newsletter, Caitlin helps researchers and teams reduce analysis time and optimize their research processes without losing rigor. I have learned so much about the latest AI research tools from Caitlin's work. 6. Brittany Hobbs, VP of Research and Insights, Huge Brittany is the host of the brilliant podcast, Design of AI, and guides teams in adopting AI. Through her conversations, she shows how AI is transforming products and industries. 7. Sarah Doody, Founder, Career Strategy Lab In addition to her expertise in UX research, Sarah helps UX and Product professionals get unstuck during these messy times and find strategic roles to make a real impact in the industry. 8. Shanae C., Nerdy Diva Shanae has spent her career leading with ethics and inclusion, bringing equity and accessibility into AI and UX work. She ensures teams build products that reflect the people they serve. 9. Angela Craven, UX Strategy and Research Consultant Angela highlights the creative, design-driven side of UX research. Through her talents and expertise, Angela demonstrates how artistry and vision elevate the way we communicate insights. These amazing women are demonstrating how our field is continuing to evolve and grow. ++ Who is inspiring you as we navigate the future of AI and strategy? #leadership #womenintech #AI #UXresearch

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Want real experience in UX, product, or project management — but don’t know where to start? There are communities out there built just for you — places where you can learn, grow, collaborate, and volunteer your way into the industry (and great networking opportunities!). 🙌 Many of you suggested Tech Fleet in my last post, so I highlighted that and another one this time! Thank you for the engagment!! These platforms help early-career professionals gain experience through real-world tech projects and mentorship: 🔁 CareerRipple (https://careerripple.org) A nonprofit connecting volunteers with impactful projects in UX research, product management, UI/UX design, and more. ✨ Bonus: You can join as a volunteer OR submit your nonprofit for help. I’ve found a great UXR project on here recently! 🌱 Tech Fleet (https://techfleet.org) A highly supportive community offering volunteer-based apprenticeship-style team projects in UX, product, research, and agile delivery. They have leadership roles AND mentee roles. You’ll work with mentors, learn how cross-functional teams operate, and walk away with serious resume and portfolio material. These aren’t just “practice projects.” They’re structured, mission-driven, collaborative experiences that mirror the real world — and they’re free to join. 💡 Whether you're transitioning into tech or growing your skills in a new direction, these communities give you: ✅ Project-based learning ✅ Team collaboration experience ✅ Mentorship and feedback ✅ Resume-ready portfolio work ✅ A meaningful way to give back Start where you are. Use what you have. Build as you grow. I’ll add more in my next post, so stay tuned. Know any other programs like these? Drop them in the comments! — let’s make this a resource for all the learners and doers out there. #UXResearch #UXDesign #ProductManagement #ProjectManagement #CareerSwitch #TechForGood #UXCommunity #VolunteerExperience #PortfolioGrowth #LearnByDoing

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If the orienting focus of all your product research, user research, design research, whatever you're all calling it these days -- is simply "The Product" and never shifts to thinking about capturing a holistic enough picture of actual real-world behaviors of people (yes, REAL PEOPLE, not whatever "personas" are dreamed up in rushed socially acceptable planning fever dreams and only allowed to be expressed in the language of pre-existing roadmaps and quarters of groupthink), what you'll be analyzing is the composite bundle of hopes, fears, wishes, dreams, stereotypes, unpacked assumptions and mental models of your organization. Which you know, has value. Some organizations even shift that mental model closer to the real world than others, they're not all bad. You need a collective dream of A Product I think. But how do you update your beliefs with new information? How do you think outside of the box of "a bunch of people deeply commercially motivated to support this product"? What ensures that you're not operating from entrenched groupthink? Personally I've always chosen to try to evaluate whether the products I've built or worked on are fitting into a big enough part of real human behaviors in the world and helping those people achieve their goals. And doing that requires structure. You need to do it in ways that take in human judgment and motivated perceptions, but also are capable of challenging those. Most of us wouldn't take a medicine that was only tested with interviews with five friends of the doctor. But for some reason a lot of product decisions are fine with this. There's a lot of money to waste this way.

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I haven’t read the book but I’ve seen researchers fall into the trap of neutrality and distance…especially quant researchers thrust into interview/moderator roles. Connection drives disclosure and insights. Being and acting like you are genuinely interested in what people experience/do/want is an impprtant factor. Its also partly why research tools that use AI to run interviews don’t claim their tools should replace humans 100% of the time. Its very important to know what types of studies to use which tools for. And unfortunately many companies won’t evaluate that in their rush to AI-ify everything and will wonder why they aren’t getting the depth they want from AI-run interviews. There are ways AI can reduce research work, and situations where AI moderation can be the right choice. This isn’t about being anti-AI, its about AI discernment.

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Why do strong applications still get rejected? Applying to a lot of grants right now and noticing a pattern. Even as I draw on past experience and real professional and academic growth, I’m still asking this. It feels like decisions are shaped as much by timing, context, and institutional logic as by quality itself. Tools like ChatGPT, Claude, and Copilot sharpen thinking, but they don’t capture the hidden dynamics behind outcomes. What are you using to actually navigate this?

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New article from MeasuringU: "What UX Hiring Managers Want and What UX Practitioners Report Doing" -- https://lnkd.in/eZY43_5g Data remarkably consistent with findings we (Lawton Pybus) previously pulled about which method are most common in UXR: https://lnkd.in/eTKp43NA Takeaway for UXRs: This gives you a prioritized list of which methods to learn first AND/OR which methods to add once you're comfortable with the most common methods.

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