Rapid Prototyping Workflows That Boost Team Collaboration

🚀 Level up your prototyping workflow: How to share multiple versions of your vibe-coded prototype Working on a complex prototype and need to show stakeholders different variations? Or running A/B tests with users? Here's a game-changer I just set up for our team: The problem: You're iterating on a prototype but need to keep the "stable" version accessible while testing new ideas. Or you want to run user research comparing two approaches. The solution: Deploy each Git branch to its own unique URL. Now our prototypes live at: main → primary "stable" prototype URL variant-a → /variant-a/ variant-b → /variant-b/ Why this matters for designers: ✅ Stakeholder reviews. Use the Github desktop app to switch between versions — "Here's the current version, and here's what we're exploring" ✅ User research — Run proper A/B tests with different participants seeing different URLs ✅ Iteration without fear — Experiment on a branch without breaking what's already working ✅ Documentation — Each variation has a permanent, shareable link The setup takes minutes using GitHub Actions. Once configured, every time you push changes to a branch, it automatically deploys to its own URL. This setup works particularly well at companies with security restrictions on teams that already use Github. Showing always beats telling. If you're a designer working with code-based prototypes, this workflow is a must-have. Happy to share the technical setup if anyone's interested! Also curious — what tools or workflows have changed how you share work with stakeholders?

As a product leader, I’ve spent years refining product development cycles — from ideation to launch. But AI is forcing all of us to rethink the how. Recently, I’ve been diving into how AI can enhance prototyping, and tools like blot.new or V0.dev have genuinely impressed me. What have I learned? 🔹 Instead of static designs in Figma → we’re using blot.new to turn those into working UIs It accepts plain-text prompts and instantly scaffolds React components styled with Tailwind CSS. The UI output is clean, componentized, and ready to plug into a real product. 🔹 Product managers can write functional prompts directly No need to wait for handoffs. A PM can now write something like: “A form with email/password input and a login button, responsive for mobile” …and blot.new returns the actual code and live UI preview within seconds. 🔹 A/B tests without code deployments We can test variations of user flows or UI layouts directly in blot.new, collect early feedback, and refine before it ever hits the dev backlog. What this changes: ✅ PMs and designers are now more hands-on with execution ✅ Engineers spend less time on throwaway prototypes ✅ Idea-to-feedback loops are dramatically shorter This shift has been energizing. And we’re just scratching the surface. Curious if others are doing the same. How are you integrating AI into your product workflow? #ProductLeadership #AIinProduct #PromptDrivenDevelopment #PrototypingWithAI #blotnew #TailwindCSS #React #RapidIteration #LeanProduct

TL;DR: Slack → GPT → Spec → Prototype 💡 Ever find your best ideas buried in a Slack thread—and the manual process of extracting them slowing you down? 💬 I ran into this often at Bumble Inc., so I built a custom GPT to help. Instead of manually recreating brainstorms or sketching early prototypes, I now take screenshots of the Slack discussion and send them to my GPT. It parses the chat, extracts the key ideas, and formats them into a mini spec—snack-size and ready to drop into Figma for prototyping. ⚡ This includes annotating who talked about which part of the idea, so when we go back to discuss things we can talk to that person and get even more context. It’s essentially “rapid prototyping,” but instead of sketching wireframes, I'm turning entire conversation threads into structured specs. Not only is it faster, but it also helps me spot conversation imbalances—like when we spent too long on one idea and barely touched another. I’m always looking for ways to pull more value out of Slack discussions—what’s working for you? 🤔 #ProductManagementAI

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!

Keep trashing your AI prototypes? Bolt.new changes AI prototypes from outputs to OUTCOMES. It bridges the gap between a quick prompt and a secure/compliant UI. Most AI tools are great for demos but fail the "production test." They ignore brand guidelines and skip security, which means engineering usually ends up rewriting everything from scratch. By creating system aware starter templates or blank slate projects that actually understands your brand guidelines and expectations, engineers can take over quickly and efficiently. Why this workflow is a game-changer for teams: - Design System Integration: Don’t settle for "generic AI layouts." Import your brand tokens and component libraries directly. Bolt forces your brand’s DNA into every button, margin, and hex code from the first prompt. - Dev-Ready: It uses WebContainers to run a full dev environment in-browser, outputting clean, modular TypeScript that’s ready for a PR. - Reusable & Scalable: This isn't just UI; it’s modular React/Next.js code with strict TypeScript interfaces. It scaffolds feature-based structures your engineering team will actually want to use, not delete. - Built-in Compliance: It handles the "boring but critical" stuff—Auth integration and accessibility—right out of the gate. The Developer Edge: Do the work once. Build the backend, save it as a starter kit and let your designers, product and other folks iterate the frontend. Using Plan Mode and WebContainers, you get the speed of an AI agent with the precision of a Senior Architect. You get clean, modular code that scales—running entirely in your browser until you're ready to ship. It’s not just "Vibe Coding." It’s DesignOps at the speed of thought.

Wow. I just built 3 mini-apps for PMs in under 10 minutes: an empathy mapper, a journey analyzer, and a competitive analysis tool with Opal (Google Labs). No PRD. No Figma. No tickets. Just an idea → an experience. Instead of debating documents, I’m now sharing working mini-apps with my team ask them "react to this, let’s refine it” I used Opal to prototype the vibe with an: -Empathy Mapper -User Journey Analyzer -Competitive Landscape Tool Each one took minutes. Each one was immediately shareable. Each one changed the conversation. Use Opal when: -You want to validate an idea before writing a PRD -You need a quick tool for a workshop or meeting -You want to make research or concepts visible -You want to better empathize about your user Think of Opal as your 10-minute lab. If it takes longer than that, move it to a full prototype — that’s where other AI prototyping tools come in. Tips for PMs adopting this workflow -Start tiny. Your first Opal app should take under ten minutes. That constraint keeps you focused on intent, not polish. -Think in verbs, not nouns. Prompts like “summarize feedback” or “visualize trends” produce far better prototypes than static descriptions. -Collaborate live. Invite designers, engineers, and stakeholders into the session. Watching the prototype evolve creates alignment faster than any meeting. -Reflect. After every prototype, note what worked. Each build sharpens your prompting instincts and your product intuition. 🔗 Guides + masterclass in the comments 👇

Uber PM: AI prototyping only goes so far. Is it possible to solve this? For most PMs still, eng is still the bottleneck. I completely sympathize with Nimisha! And don’t mean to call her out. I think there are 3 ways teams can solve this: 1. Modernizing code This one is really for engineering leaders to solve. You want to make the code base easy to vibe code with. > Are engineers using Claude Code and Devin? Or are they stuck with Github Copilot? > Can you build and deploy nearly instantly? Or does it take hours? > Is your code built with Tailwind and microservices? Or too big for AI context windows? 2. AI experimentation: You don’t always need to make huge backend changes. Set up with an Optimizely or Kameleoon where you can allows non-technical users to vibe experiment in a way that uses your design and code base. This unlocks front-end testing from the engineering dependency almost entirely, with the exception of a code review by the on-call engineer. 3. AI discovery: Not everything needs to go to production. Vibe code then send the prototype to Usertesring or Voicepanel. Get real human feedback in just a few hours. Resources: 1. Modernizing code: a. Meta example: https://lnkd.in/eeqvdbvV b. Tech guide: https://lnkd.in/eD6e6Wgt 2. AI experimentation a. Full guide: https://lnkd.in/e86mpjGR b. Tech review workflow: https://lnkd.in/etXnfc2C 3. AI discovery a. Teresa Torres: https://lnkd.in/e7Q6mMpc b. Detailed guide: https://lnkd.in/e9QrMEDw Want to stay up with this new way of working? Follow Aakash Gupta for daily tips.

Happy Friday, this week in #learnwithmz, let's explore how AI is revolutionizing product prototyping, from idea to interactive mockup faster than ever. I’m delivering an internal talk on this topic for my team, and thought it would be valuable to share some highlights here as well. 𝐓𝐨𝐩 𝐀𝐈 𝐏𝐫𝐨𝐭𝐨𝐭𝐲𝐩𝐢𝐧𝐠 𝐓𝐨𝐨𝐥𝐬 𝐟𝐨𝐫 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐫𝐬 -Visily Transform text prompts, sketches, or screenshots into editable UI designs. 🔗 https://lnkd.in/gcerJweq - Uizard Generate wireframes and mockups instantly from text descriptions. 🔗 https://lnkd.in/grdSadcb - Microsoft 365 Copilot Prototype ideas directly within your workflow using Word, Excel, PowerPoint, and Teams. Great for early PRDs, visualizations, and cross-team brainstorming. 🔗 https://lnkd.in/gB2PNq9k - V0 by Vercel Create full-stack web apps from prompts, integrating frontend and backend. 🔗 https://v0.dev/ - Bolt Rapidly build and iterate on AI-driven product ideas. 🔗 https://boltai.co - Lovable Design and deploy AI-powered products with minimal coding. 🔗 https://lovable.so 𝐎𝐩𝐞𝐧-𝐒𝐨𝐮𝐫𝐜𝐞 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬 - NodeTool: Build and automate AI workflows without code. 🔗 https://lnkd.in/gnnB_7UU - ReacType: Visualize and export React applications with drag-and-drop. 🔗 https://lnkd.in/geQbxbEC 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠𝐬 - Speed vs. Precision: AI tools are great accelerators, but manual polish is still needed for complex workflows and specific needs. - Experiment often: The space is evolving fast; test, learn, and share back. - Check before you use: Always check your company’s policies on tool usage, especially when working with sensitive product data or proprietary designs. 𝐅𝐮𝐫𝐭𝐡𝐞𝐫 𝐑𝐞𝐚𝐝𝐢𝐧𝐠 A Guide to AI Prototyping for Product Managers by Lenny Rachitsky and Colin Matthews 🔗 https://lnkd.in/ge6nbzcr Which AI prototyping tools are in your workflow or on your radar? Drop your experiences or recommendations below 👇 #AI #ProductManagement #Prototyping #AItools #learnwithmz

As a Product Leader, I have been using Lovable frequently over the last few weeks and I love the adaptability and flexibility it provides and helps me think more completely about product/features. One advantage I find over the other options is how stable any of the created applications are on Lovable PMs, here's how you can use the tool as a superpower. Rapid Prototyping: - Transform ideas into working web apps in seconds by simply describing your vision in plain language (being more detailed helps but you can progressively add the details too). - Quickly generate functional, beautiful prototypes to validate MVPs and test concepts. Empower Your Team: - Enable non-technical team members to contribute directly, enhancing cross-functional collaboration. - Align on abstract ideas by converting them into tangible prototypes (even if you are trying to just rationalise an idea just for yourself, the tool works great!) Seamless Integrations: - Enjoy built-in support for Supabase for backend functionality and GitHub for version control. - Maintain complete code ownership and easily hand off projects as needed. Enhanced Design Workflow: - Leverage new Figma integration to convert design prototypes into fully interactive, testable apps. - Rapidly iterate based on real-time feedback using intuitive chat-based edits. Accelerated Time-to-Market: - Deploy and share your prototypes with one-click, ensuring continuous feedback and agile development. - Streamline your workflow to focus on strategic product decisions and customer validation. You must discover how Lovable empowers Product Managers to innovate faster, optimize resources, and lead a new era of product development. It is a game changer! PS: No, I have not been paid by Lovable or have any contact with their team

AI tools dramatically changed how I do product. Here’s a workflow I did recently that I recommend every PM to try. We’re working on a new product that needs a lot of product definition under a huge time crunch (sounds familiar, anyone?). Instead of weeks of back-and-forth with the team to get my vision and thinking across, I vibe coded a few prototypes to convey my concepts... and it was shockingly effective. Using Lovable or AI Studio, you can quickly bring your ideas to about 70% of where you want them to be (but like everything genAI… good luck closing the gap of the remaining 30% 🫠 ). For a prototype though, 70% is perfectly fine. These prototypes grasped our key concepts so well, that we decided to test them in user research to validate our hypotheses quickly. As we have pretty ambitious plans (plug.. watch this space), a figma prototype would have taken designers serious time to create, and static wireframes just wouldn’t have gotten us the learnings. While the quickly developed AI prototypes didn’t look or feel at all like the core interface, this actually played into our advantage as it removed bias, and let users give feedback on functionality rather than the UI. And a bonus tip: I fed the UXR Transcripts to Gemini, using it as a thought-partner to clarify my thinking when writing user journeys, requirements, definitions. Try this to get rid of the blank canvas problem of writing. I honestly couldn’t be more excited about the opportunities these tools bring. It allows me to spend my time focusing on deep thinking, direction, vision, and strategy (all that stuff PMs are uniqely positioned to do) instead of wasting time on tasks that require little or no creativity. (and yes for the sake of illustrating this post I built a prototype that builds prototypes 😵💫)