Prototyping and Testing Strategies

People teams are always expected to do things perfectly. They’re expected to come up with a preened policy, a polished performance process, a precise career path framework. And this perfection-expectation can be an absolute mare to wrestle with when you’re trying to work like a product team. Especially when it comes to prototyping. Because that’s the messy stuff. The shitty first draft. The first pancake. The scrappy sketch. And it's also gold dust when it comes to getting feedback. “Oh feedback?” you say. “But we have no problem getting feedback from our teams. In fact, when are we not getting feedback of some kind?!” Sure. But I'm guessing most of that feedback is reactive. Not invited, structured, or tied to something you’re testing, am I right?! So how can you confidently share a very-much-not-finished prototype and still feel in control of what you learn from it? Enter: Pitch it, Break it, Build it, Fix it (anyone else hear Daft Punk when they read that out loud?) A simple card to help you capture and test people experience ideas with more confidence, and fewer perfectionist spirals (well, at least we can work our way up to that, eh?!) Here’s how it works: → Pitch it Explain what the idea is and why it matters. Who’s it for? What problem does it solve? What’s the most basic version you could test? → Break it Invite your team to poke holes in it. Where might it fail? What’s unclear? What wouldn’t land, and why? → Build it Now rebuild the idea with them, based on what you’ve learned. What still holds up? What needs to evolve? How could it become more workable, testable, useful? → Ship it Work with your team to get it in front of real users, fast, light, and focused. What’s the smallest, real-world test you could run? How will you know what’s working? Use it in your team retro, a 1-1 session, or when shaping a new idea with stakeholders. It works best when you keep it low-fi, short, and curious. 👇 Grab the card below and give it a spin. Your first pancake is waiting, I can’t wait to see what you cook up. 🥞 #PeopleOps #Prototyping #Innovation ___________ Hi 👋 I'm Alicia, co-founder of The Future Kind. I’m a facilitator, designer & systems thinker working with leaders and people teams to build innovation cultures and make work work. Want to know more? Follow along or DM me, I love to hear form you. 💌

"Getting real customer transcripts changed everything." 📝 Learn how I built my first AI product - an Interview Coach that helps product teams improve their customer interviewing skills. Follow my journey from initial prototype to production, including key lessons on: 🎯 Choosing the right problems for AI to solve: - Start with real customer needs and pain points - Look for opportunities that were previously hard to solve - Focus where you have domain expertise 🔬 Prototyping and testing approach: - Start simple with existing LLM tools - Test with a small, engaged user group - Get real user data early ⚙️ Architecture decisions: - Don't default to chat interfaces - Break complex tasks into smaller AI tasks - Start simple and add complexity as needed - Expect to outgrow your tools 🎯 Getting consistent results: - Build comprehensive evals - Ground evals in error analysis - Continuously monitor performance - Start simple with tools you know 💪 Continuous improvement: - Regular trace review and annotation - Ongoing eval updates - Continuous experimentation - Quick iteration cycles 🔒 Data responsibility: - Be transparent about data collection - Consider compliance requirements early - Partner rather than build infrastructure - Delete data you don't need Check out the comments for a link to the article. 💭 What's been your biggest challenge when building AI products? Share your thoughts in the comments below.

For founders, building a successful product is often less about the idea and more about the process. Knowing when to use a Proof of Concept (PoC), Prototype, or Minimum Viable Product (MVP) can be the difference between scaling up or burning out. 🌱 Proof of Concept (PoC): Testing “Possible” vs. “Impossible” Insight: PoC is about finding limits, not solutions. It’s the stage to test if your concept is even technologically achievable with current resources. This stage isn’t about showing off or impressing; it’s about brutally honest assessments. It’s where you ask, “Are we chasing something we can’t feasibly build?” Use it when: You’re unsure if a novel tech component will work in practice. Example: Is the AI algorithm actually capable of processing data at this scale? Founder's takeaway: Don’t fall in love with the concept just because it’s new. PoC is where you might need to abandon the idea early, saving resources and learning key constraints. 🎨 Prototype: Bringing Ideas to Life, Not to Market Insight: The Prototype phase isn’t about building a working product; it’s about exploring user interactions and design flow. A good prototype reveals what’s broken in the user journey before you commit resources to coding and development. You’re here to answer, “Is this something people will want to use? Is the experience intuitive?” Use it when: You need a vision, not a finished product. Example: How will users navigate the app? Does the layout make sense? Founder's takeaway: Prototyping forces you to confront your assumptions about user behavior and design. A great idea with poor UX is doomed, so listen to feedback carefully and iterate. 🚀 Minimum Viable Product (MVP): Testing If People Actually Care Insight: MVPs are not meant to be “perfect”—they’re meant to be functional enough to test market need. The MVP is your experiment in real-world conditions. The goal isn’t to sell the product but to learn what will make it sell. This is where startups often discover whether they’re solving a problem worth paying for or just building something “cool.” Use it when: You have a clear problem you’re solving and need to validate that users care enough to engage (and hopefully, pay). Founder's takeaway: An MVP is not your “launch” but a learning opportunity. Don’t be afraid to fail or pivot based on real-world feedback—it’s cheaper and easier than overbuilding a product people don’t want. 🔍 Key Takeaway: Not Every Stage Is Necessary Founders often assume they need to go through all three stages, but the reality is that many products don’t need a PoC, and some products might skip a Prototype if the MVP serves that purpose. Final Thought: Think of PoC, Prototype, and MVP as tools for falsifying assumptions. Each stage should help you eliminate uncertainties before moving to the next. #startups #productdevelopment #founderinsights #innovation

🔬 UX Concept Testing. How to test your UX design without spending too much time and effort polishing mock-ups and prototypes ↓ ✅ Concept testing is an early real-world check of design ideas. ✅ It happens before a new product/feature is designed and built. ✅ It helps you find an idea that will meet user and business needs. ✅ Always low-fidelity, always pre-launch, always involves real users. 🚫 Testing, not validation: ideas are not confirmed, but evaluated. ✅ What people think, do, say and feel are often very different things. ✅ You’ll need 5 users per feature or a group of features. ✅ You will discover 85% of usability problems with 5 users. ✅ You will discover 100% of UX problems with 20–40 users. 🚫 Poor surveys are a dangerous, unreliable tool to assess design. 🚫 Never ask users if they prefer one design over the other. ✅ Ask what adjectives or qualities they connect with a design. ✅ Tree testing: ask users to find content in your navigation tree. ✅ Kano model survey: get user’s sentiment about new features. ✅ First impression test: ask to rate a concept against your keywords. ✅ Preference test: ask to pick a concept that better conveys keywords. ✅ Competitive testing: like preference test, but with competitor’s design. ✅ 5-sec test: show for 5 secs, then ask questions to answer from memory. ✅ Monadic testing: segment users, test concepts in-depth per segment. ✅ Concept testing isn’t one-off, but a continuous part of the UX process. In design process, we often speak about “validation” of the new design. Yet as Kara Pernice rightfully noted, the word is confusing and introduces bias. It suggests that we know it works, and are looking for data to prove that. Instead, test, study, watch how people use it, see where the design succeeds and fails. We don’t need polished mock-ups or advanced prototypes to test UX concepts. The earlier you bring your work to actual users, the less time you’ll spend on designing and building a solution that doesn’t meet user needs and doesn’t have a market fit. And that’s where concept testing can be extremely valuable. Useful resources: Concept Testing 101, by Jenny L. https://lnkd.in/egAiKreK A Guide To Concept Testing in UX, by Maze https://lnkd.in/eawUR-AM Concept Testing In Product Design, by Victor Yocco, PhD https://lnkd.in/egs-cyap How To Test A Design Concept For Effectiveness, by Paul Boag https://lnkd.in/e7wre6E4 The Perfect UX Research Midway Method, by Gabriella Campagna Lanning https://lnkd.in/e-iA3Wkn Don’t “Validate” Designs; Test Them, by Kara Pernice https://lnkd.in/eeHhG77j UX Research Methods Cheat Sheet, by Allison Grayce Marshall https://lnkd.in/eyKW8nSu #ux #testing

Marty Cagan dropped a masterclass on AI prototyping. No hype. Just a clear-eyed view: Many people misunderstand the purpose of these tools. They are for discovery, not delivery. In fact... Prototypes are your go-to tools for solution discovery. They help minimize the 4 risks: 1. Value 2. Viability 3. Usability 4. Feasibility But AI prototypes aren't always the right prototype. And even if you go for an AI prototype, it doesn't always need live data. The level of fidelity should match the level of risk. If you don't care about visual fidelity, then getting that right in an AI prototyping tool is overkill. So repeat after me: "The level of fidelity should match the level of risk." Then read the piece yourself: https://lnkd.in/eqiGDRjU If you want to go more into the nuances of this topic, I've put together a bunch of resources: • Guide to AI prototyping: https://lnkd.in/eJujDhBV • Test of the top 5 tools: https://lnkd.in/eEGy9Dri • Podcast with Marty: https://lnkd.in/eb5hbA28 • Exploring Windsurf: https://lnkd.in/eKcpNsCD • Using Cursor: https://lnkd.in/d2pcXD7R • Claude Code: https://lnkd.in/eUyPEAma • What this means for PRDs: https://lnkd.in/eMu59p_z • As well as for AI Strategy: https://lnkd.in/egemMhMF • And vibe coding interviews: https://lnkd.in/e66DrW-h The role of PM is changing fast. Hope this helps you. 📌 Want my view of the AI prototyping tool landscape? Comment 'prototyping landscape' + DM me. What's your take: are folks overhyping AI prototypes?

🚀 Day 7 of 100 Days of Product Management: Elevating Product Discovery ✍ Daily Insight: Effective product discovery goes beyond initial user interviews and explores continuous, iterative exploration and validation. Effective discovery can make or break the success of your product. Here are some actionable tips and strategies to enhance your discovery processes: * Leverage Existing Data: Utilize analytics, customer support logs, and previous research as a starting point to save time and resources. * Dual-Track Agile: Integrate discovery with delivery to keep your development agile and continuously informed by fresh insights. * Prioritize Hypothesis Testing: Formulate and test hypotheses through A/B tests, prototype testing, and concierge MVPs to quickly validate ideas. * Rapid Prototyping: Use tools that facilitate fast prototype creation to gather user feedback early and iterate before deep development. * Continuous User Engagement: Establish a regular feedback loop with users through communities or panels for real-time insights. * Diversify Research Methods: Combine qualitative and quantitative methods to gain a comprehensive understanding of user needs. * Utilize Remote Research Tools: Implement tools like Zoom, Miro, or UserTesting for effective remote user research. * Embrace Storytelling: Use compelling storytelling when sharing insights with stakeholders to better convey user journeys and solution impacts. * Regular Insight Sharing: Hold frequent sessions to keep all team members updated with the latest discoveries, maintaining alignment across functions. * Open-mindedness and Flexibility: Be ready to pivot your product direction based on new insights to truly meet market needs. * Balance Speed with Depth: Ensure rapid progress does not sacrifice a deep understanding of the user problems. * Cross-functional Involvement: Engage diverse team members in discovery to enrich insights and validate across various perspectives. Image Source - https://lnkd.in/g7N47v2p by Productboard | Download the Product Discovery Playbook here - https://lnkd.in/gEUFQUvc ⭐ Tool Highlight: Miro Excellent for collaborative mapping and prototyping, enabling teams to visualize and iterate on feedback quickly. Andrey K. | Steven Chang | Srinath Govindarajan #miro 🙎 PM Spotlight: Meet Amit Garg, who leads product at ace turtle. He is a seasoned professional in retail and e-commerce, excelling in software solutions product development and implementation for both B2B and B2C clients. He has collaborated with over 12 global retailers and brands, including L’Oreal, Crocs, and Loves, across the USA, UAE, and APAC regions. Join the conversation and let's exchange knowledge on refining our product discovery to build products that truly resonate with users! #Day7of100 #ProductDiscovery #ProductManagement #100DaysOfProductManagement

As a founder, it always feels like we’re moving slower than we want to. We ALWAYS have more ideas than bandwidth. So how do we focus on the right thing to solve? Here’s a 5-step breakdown of how to use Google’s Design Sprint to get past the finish line, FAST. What is a Design Sprint? GV (Google Ventures)’s five-day methodology and program for — you guessed it — to take ACTION and test out a new idea. Why should you care? Well, it’s been used by Google, Uber, Medium, Slack, Facebook, Twitter, The New York Times… so, yeah, it might be worth looking into. Here’s the process so you can adapt it for your own climate tech solution: 1. Understand Map the key journeys of users, detail qualities/weaknesses Define one specific problem using “How Might We” questions Finalize the core problem that needs to be solved in the context 2.Sketch Lightning Demos – of inspiring ideas. Explore solutions individually by sketching ideas. Think in terms of storyboards and stakeholder journeys Team members develop diverse, detailed, and viable solutions. 3.Decide Engage with all ideas anonymously – answer: What features will we keep? How can we simplify? Review all sketches and decide on the most promising solution. Create a storyboard/wireframe that outlines the concept and decide precisely what to prototype. 4.Prototype Your team takes a step back as the Design Sprint team handles the prototype. When doing it yourself, keep the prototype simple —only convey the core functionality. Think low-fidelity and act fast - paper prototypes, low-code mockups, or basic landing pages. Remember: it's just for testing — it only needs enough detail for user feedback. 5.User Test Test the prototype with small groups of real users and potential customers. User testing is 1:1 — straightforward, open, and pragmatic. Film tests to observe user behavior and reactions. Schedule multiple short sessions throughout the day & follow best practices for efficiency. Do multiple rounds of sprint to get more specific into your offering. You might not be able to do it exactly the way Google does, or take as little time – but why not try executing your own design sprint? Share with someone interested in firing up their climate tech solution! ---- If you're climate company looking to kickstart your product with seamless UX Design, reach out!

Proof-of-concepts take hours but production-grade reliability still takes months. I’ve lost count of the jaw-dropping demos I’ve seen (and built) in the last 18 months. The Gen-AI era lets us turn an idea into a working prototype before coffee gets cold. But here’s the trap: stakeholders watch that slick demo and instantly expect full-scale, 24×7, enterprise-grade performance. The gulf between the two is where products and reputations can sink. Here are three useful lessons I have learnt 1. Show the demo, but sell the definition of done. Every prototype reveal should end with a single slide titled “What Done Really Means.” List the uptime target, concurrency load, and failure budget. When stakeholders cheer, they’re cheering for that contract, not the GIF they just saw. 2. Separate demo velocity from deployment velocity. Measure prototypes in hours or days, but plan for production hardening in weeks/months. Different clocks, different KPIs, different decision gates. 3. Turn excitement into a transparent roadmap. Follow the wow-moment with a one-pager: reliability targets, scalability milestones, risk mitigations, next checkpoints. Momentum stays high, surprises stay low and everyone sees exactly how the headline demo becomes customer value. How does your team convert demo sparks into production fire? Share your tactics below.

Don't wait until your design is 'finished' to prototype it In design and development, our time is our most valuable asset. We want to get concepts into real world as fast as possible to validate assumptions. Direct access to 3D printing is like a magical superpower. Don't wait until you think you have all the answers to print your design. Print, print, print. The material is not expensive when compared to your time. Print something that you know won't fit together. Start a low-res print overnight, your tomorrow self will thank you. Build and test. Then start over and do it again. We can always make it pretty later, after we solve the technical problems. I'm this pic, I needed to validate an idea for assembly. But I didn't want to wait 2-days for Amazon Prime. So I printed some in 15 minutes. No they won't work for heat transfer. But they'll work as a stand-in to hold the camera sensor in place while I develop the support structure around it. I'm this case, I learned how fragile the ZIF connector on the flex ribbon cable was once removed the heat transfer tape on the back of the sensor. I couldn't have known that without trying it. Everything in CAD is perfect. Get your ideas into the real world for testing ASAP. #rapidprototyping

From idea to prototype in hours, not weeks. That's been my recent experience experimenting with Lovable, and it's completely changed how I approach ideation and product thinking. Turning abstract ideas into clickable, interactive prototypes in no time means less talking about the concept, and more showing. In one recent build, the moment I shared the prototype, the conversation shifted from “What do you mean?” to “Is this how you see it?” That one shift sparked faster clarity, better feedback, and deeper alignment. No more endless meetings trying to describe what’s in everyone’s head. Here’s what I’ve learned along the way: 𝟭. 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝗮 𝗰𝗹𝗲𝗮𝗿 𝗼𝗯𝗷𝗲𝗰𝘁𝗶𝘃𝗲 𝗳𝗼𝗿 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗱𝘂𝗰𝘁. Even with powerful tools doing the heavy lifting, I start by organizing my thoughts on paper—with a clear outline, defined scope, and key user flows. The tool amplifies good product thinking, but it can't replace it. 𝟮. 𝗔𝗹𝗶𝗴𝗻 𝘆𝗼𝘂𝗿 𝘁𝗮𝘅𝗼𝗻𝗼𝗺𝘆 𝗮𝗻𝗱 𝗻𝗮𝘃𝗶𝗴𝗮𝘁𝗶𝗼𝗻 𝗲𝗮𝗿𝗹𝘆. This becomes incredibly clear when you're building a visual prototype. Getting your information architecture right from the start saves significant rework later. 𝟯. 𝗘𝗺𝗯𝗿𝗮𝗰𝗲 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝗱𝗿𝗮𝗳𝘁 𝗳𝗼𝗿 𝗰𝗹𝗮𝗿𝗶𝘁𝘆 𝗮𝗻𝗱 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸. Don't aim for perfection on the first build. Get something clickable in front of people quickly. The real insights come from watching others interact with your prototype, not from endless polishing. You can always go deeper and refine the prototype based on those initial insights. 𝟰. 𝗟𝗲𝘃𝗲𝗿𝗮𝗴𝗲 𝗹𝗼𝗰𝗮𝗹 𝗳𝗶𝗿𝘀𝘁. For initial builds, leverage local browser cache before connecting to databases or other external tools. It speeds things up considerably and keeps you agile. 𝟱. 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗯𝗮𝘀𝗶𝗰𝘀 𝘀𝘁𝗶𝗹𝗹 𝗺𝗮𝘁𝘁𝗲𝗿. A crucial reminder: never store your LLM API keys in plain text, especially if your project is public or remixable. Low-code tools like Lovable don’t just speed up the work—they unlock momentum, clarity, and collaboration. These change the way we think, not just what we build. Been experimenting with Lovable, Replit, v0 dev, or similar tools? I’d love to hear your best practices. ------------------------- P.S Curious about prototyping, product thinking, or AI workflows? I host Sunday brainstorming sessions — DM me if you'd like to join the next one!