Rapid Prototyping Workflows That Boost Team Collaboration

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

Product leaders, stop hiding behind docs! If your team is still spending all their time in PRDs and product strategy docs, they're not operating in 2025. AI prototyping has literally changed the game. Here's how teams should do it: — THE OLD WAY (STILL HAUNTS MOST ORGS) 1. Ideation (~5% actually prototyped) “We should build X.” Cool idea. But no prototype. Just a Notion doc and crossed fingers. 2. Planning (~15% use real prototypes) Sketches in Figma. Maybe a flowchart. But nothing a user could actually click. 3. Discovery (~50% try protos) Sometimes skipped. Sometimes just a survey. Rarely ever tested with something interactive. 4. PM Handoff (~5%) PM: “Here’s the PRD.” Design: “Uhh… where’s the prototype?” PRDs get passed around like homework. 5. Design Design scrambles to build something semi-clickable, just so people stop asking “what’s the plan?” 6. Eng Start Engineering starts cold. No head start. They’re building from scratch because nothing usable exists. — WHAT HAPPENS - Loop after loop. Everyone frustrated. - Slow launches. Lots of guesswork. - And no one truly understands the user until it’s too late. — THE NEW WAY (THIS IS HOW WINNERS SHIP) 1. Ideation PMs don’t just write ideas. They prototype them. Want to solve a user problem? Click, drag, test. There. No waiting. No “someday.” You build it, even if it’s ugly. 2. Planning Prototypes are the roadmap. You walk into planning with a live flow, not a list of features. And everyone’s like: “Oh. THAT’S what you meant.” 3. Discovery Real users. Real prototypes. You send them a flow and you watch them break it. You’re not guessing anymore. You’re observing. 4. PM Handoff PMs don’t just hand off docs. They ship working demos alongside the PRD. No more “interpret this paragraph.” Just click and see it work. 5. Design Designers don’t start from scratch. They take what’s already tested, validated, and tweak it. Suddenly, “design time” is “refinement time.” 6. Eng Start Engineers don’t wait around. They start with something usable. If not, they prompt an AI tool to build it. And we’re off to the races. — If you want to see how AI prototyping actually works (and learn from expert Colin Matthews), check out the deep dive: https://lnkd.in/eJujDhBV

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!

I tried 10+ AI prototyping apps. Only one stood out. Here's why: Don't sleep on this tool. I tried the usual suspects (Lovable, Stitch, Make, Bolt, v0, etc.) But when I found Magic Patterns, I stopped looking. It had everything I needed for collaborative, AI-powered prototyping, especially in the early stages of the design process. Everyone’s debating which AI prototyping tool generates the best UI designs or code. Or they're showing off a random vibe coded app. But I think the real opportunity for product teams is being overlooked. Early-stage collaborative AI prototyping is where the magic happens. Fast exploration, shared context, real momentum. 3 Reasons why Magic Patterns excels at this: 1. Live AI prototyping with others = game changer Magic Patterns lets you invite people to a shared canvas. Review and interact with multiple prototypes in one view. Fork, remix, and build on ideas instantly. It’s multiplayer AI prototyping done right, perfect for my AI design sprint workshops. And perfect for product teams to rally around a problem and explore ideas. 2. Front-end focus, no backend noise You can explore flows and concepts fast, without getting distracted by databases or logic. Many of the hyped AI tools are focused on vibe coding complete apps. But for early-stage work you just need to quickly explore multiple ideas, iterate, get alignment, and test for feedback. For this purpose, Magic Patterns is exactly what I needed. 3. Thoughtful features that speed up your flow Magic Patterns is perfect for first-time AI prototypers. The beginner friendly interface and useful features like "Presets," "Inspiration," and "Polish", make it easy for anyone to experiment with purposeful ideas. Bonus Reason: Don't mistake Magic Patterns for a basic AI UI tool. There are advanced features and smart workflows I’ll show you that make this the most valuable tool I’ve added to my design process in years. I’m hosting a FREE live walkthrough next week where I’ll demo exactly how I use Magic Patterns inside my AI Design Sprint workshops, including best practices and the frameworks I’ve used in real sessions. This is a glimpse into how design, product, and engineering will work together in the AI era. Once you see it in action, you’ll want to run your next workshop this way. Come hang out. It’s going to be fun, useful, and maybe even a little magical. 🪄 Spots are limited. Drop “magic” in the comments or DM me to reserve your spot.