The Future of Innovation in Product Development Practices

Product development in 2024 - the old way: • Design low-fi wireframes to align on structure • Create pixel-perfect Figma mockups • Socialize designs with stakeholders • Wait weeks for engineering capacity to build • Build core functionality first • Push "nice-to-have" animations to v2 • Ship v1 without thoughtful interactions • Iterate based on limited feedback • Repeat the cycle for 3-6 months Product development in 2025: • Quickly prototype in code with AI tools like Bolt • Generate functional prototypes in hours, not days • Deploy to real URLs for immediate testing • Add analytics to track actual usage patterns • Test with users while still in development • Designers directly create interaction details • Engineers implement interaction details by copying working code • Ship v1 with thoughtful animations and transitions • Iterate rapidly based on both qualitative and quantitative data • Implement improvements within days Last week, we hosted William Newton from Amplitude to share how this shift is fundamentally changing their product development approach. "I made those interaction details myself. I made those components myself, and I sent them to my engineer and he copied and pasted them in." Features that would have been pushed to "future versions" are now included in initial releases. Loading animations, transition states, and micro-interactions that improve user confidence—all shipped in v1. This approach doesn't eliminate the need for thoughtful design and engineering. Instead, it changes the order of operations: - Traditional process: Perfect the design → Build the code → Ship → Learn - Emerging process: Prototype in code → Learn while building → Ship with polish → Continue learning The limiting factor is shifting from technical implementation to your taste and judgment about what makes a great experience. When designers and PMs can participate directly in the creation process using the actual medium (code), they make different—often better—decisions about what truly matters.

AI isn't just a tool; it's becoming a teammate. A major field experiment with 776 professionals at Procter & Gamble, led by researchers from Harvard, Wharton, and Warwick, revealed something remarkable: Generative AI can replicate and even outperform human teamwork. Read the recently published paper here: In a real-world new product development challenge, professionals were assigned to one of four conditions: 1. Control Individuals without AI 2. Human Team R&D + Commercial without AI (+0.24 SD) 3. Individual + AI Working alone with GPT-4 (+0.37 SD) 4. AI-Augmented Team Human team + GPT-4 (+0.39 SD) Key findings: ⭐ Individuals with AI matched the output quality of traditional teams, with 16% less time spent. ⭐ AI helped non-experts perform like seasoned product developers. ⭐ It flattened functional silos: R&D and Commercial employees produced more balanced, cross-functional solutions. ⭐ It made work feel better: AI users reported higher excitement and energy and lower anxiety, even more so than many working in human-only teams. What does this mean for organizations? 💡 Rethink team structures. One AI-empowered individual can do the work of two and do it faster. 💡 Democratize expertise. AI is a boundary-spanning engine that reduces reliance on deep specialization. 💡 Invest in AI fluency. Prompting and AI collaboration skills are the new competitive edge. 💡 Double down on innovation. AI + team = highest chance of top-tier breakthrough ideas. This is not just productivity software. This is a redefinition of how work happens. AI is no longer the intern or the assistant. It’s showing up as a cybernetic teammate, enhancing performance, dissolving silos, and lifting morale. The future of work isn’t human vs. AI. The next step is human + AI + new ways of collaborating. Are you ready?

The Future of Smart Object Manufacturing 🔧 What if your dinner plate could talk to your phone and automatically log your meals? Your coffee mug reminding you to stay hydrated? These ideas exist, of course. But what about things that haven't been invented? It may not be long before you just print a smart object when you need it. This isn't science fiction. We're moving toward a world where anyone can create or download a design file and print fully functional smart objects at home. No assembly required. No electronics to buy separately. Just hit print and get a working device. What's making this possible? Embedded electronics in 3D printing is creating something incredible: 🖱️ Touch-sensitive surfaces printed directly into objects ⚡ Electronics integrated from the ground up, not bolted on 🌍 Digital designs becoming functional devices anywhere in the world Imagine walking into any FedEx shop in a couple of years from now to create a new product based on your own ideas: 📦 Shipping boxes that automatically text you when they're delivered and report if they've been damaged 🏭 Supply chain sensors printed directly into packaging to log temperature, humidity, and location in real-time 📄 Smart documents with embedded chips that verify authenticity and track who's accessed them 🛃 Product authentication tags that let US customs instantly verify what's inside a shipment matches the declared contents This isn't just about making gadgets cheaper. It's about democratizing innovation. The next big thing could come from anywhere: 🚚 A freight forwarder might invent the smart cargo tracker that finally solves last-mile visibility 📋 A customs broker could design the document chip that streamlines border crossings 📦 A 3PL warehouse worker might create the inventory tool that revolutionizes picking accuracy 🚛 A truck driver could develop the fatigue monitor that saves lives on the highway We have no idea what people will invent with this technology, but that's exactly what makes it so exciting. What products would you create if you could embed full electronics into any shape? #Innovation #Manufacturing #3DPrinting #SupplyChain #Logistics #Truckl #SmartObjects

Most people are talking about how AI speeds up product development. But that misses a more powerful and completely different benefit… Yes, as we shift to AI-native product teams AI will help accelerate existing product development cycles. But as Scott Belsky, CPO of Adobe and investor in Reforge highlighted in his newsletter (link in comments): “What makes this technology truly distinctive from other advances is its reasoning and imaginative capabilities (not taste-based imagination, but boundless directed exploration). What this technology really gives us is MORE CYCLES - more cycles to explore” Here is why this is so important… In today’s world, most product teams face pressure to ship often. Teams can’t afford to explore many solution paths. This creates three problems: 🚫 High-stakes decisions based on limited data 🫡 Solutions optimized for internal consensus rather than customer value ✂️ Innovative approaches killed by time constraints before they can prove themselves But with an expanded capacity to explore: ⤇ Multiple interface designs ⤇ More prototypes ⤇ Dozens of copy variations ⤇ Different GTM narratives ⤇ and more… What would have historically been impossible can now happen in parallel, increasing both the quantity and quality of product decisions. In other words, AI isn't just accelerating our existing processes; it's fundamentally changing how we discover and validate product opportunities. Shifting to AI-native product teams won’t be about accelerating existing processes, it will be about asking - "What’s possible now that wasn’t before?" More thoughts on AI-native product teams in the comments...⬇︎⬇︎