Trends Shaping Innovation in Product Development Today

The product trio is merging. And it's not just because of AI. In fact, I first saw this concept in 2020, presented by Yuhki Yamashita, CPO of Figma. (ie, well before the current AI boom) — It's driven by a few key trends: 1. Engineers are taking an active role in the problem space The early startup paradigm of product-focused engineers is moving into larger companies. It's just a pre-requisite for engineering success these days. They don't just ask, how big was the feature, or important the technical innovation. They ask: how big was the impact? Naturally, tech leads and engineering managers everywhere have become more critical of driving that. 2. Designers are taking an active role in the business More than ever, designers are learning and building for metrics. In a world where OKRs rule the roost, the incentive is natural. They can't just trust a PM to be able to fully vet the business space. Because, too many times, the PM gets it wrong. And this creates an environment where collaboration tends to do better than silos. 3. PMs are learning design and tech drive performance The little details of how you design a product and the technical decisions you make determine whether it's successful. Both product leaders and product managers are realizing they have to get into the details. You can't just have a conversation with a CEO who is in the details of the product by outsourcing it all to your tech and design partners. 4. Finally, yes, AI is accelerating the merge Now: • Design engineer is the hottest thing on Twitter • Companies everywhere are waiting to hire PMs • All disciplines continue to use AI to speed up their work This will reduce time on finessing details & increase time on the why. — Putting all this together... It seems undeniable the roles have started to merge on the edges. But, the core responsibilities remain differentiated. So, in this increasingly overlapped world, how you work with your sister functions becomes a differentiator. Those who: • Lead with empowerment • Collaborate with empathy   • Blend roles, but don't step on toes Will be the one's leading us into this new era. On the other hand, those that try to maintain the silos, will find themselves outdated.

After spending three decades in the aerospace industry, I’ve seen firsthand how crucial it is for different sectors to learn from each other. We no longer can afford to stay stuck in our own bubbles. Take the aerospace industry, for example. They’ve been looking at how car manufacturers automate their factories to improve their own processes. And those racing teams? Their ability to prototype quickly and develop at a breakneck pace is something we can all learn from to speed up our product development. It’s all about breaking down those silos and embracing new ideas from wherever we can find them. When I was leading the Scorpion Jet program, our rapid development – less than two years to develop a new aircraft – caught the attention of a company known for razors and electric shavers. They reached out to us, intrigued by our ability to iterate so quickly, telling me "you developed a new jet faster than we can develop new razors..." They wanted to learn how we managed to streamline our processes. It was quite an unexpected and fascinating experience that underscored the value of looking beyond one’s own industry can lead to significant improvements and efficiencies, even in fields as seemingly unrelated as aerospace and consumer electronics. In today’s fast-paced world, it’s more important than ever for industries to break out of their silos and look to other sectors for fresh ideas and processes. This kind of cross-industry learning not only fosters innovation but also helps stay competitive in a rapidly changing market. For instance, the aerospace industry has been taking cues from car manufacturers to improve factory automation. And the automotive companies are adopting aerospace processes for systems engineering. Meanwhile, both sectors are picking up tips from tech giants like Apple and Google to boost their electronics and software development. And at Siemens, we partner with racing teams. Why? Because their knack for rapid prototyping and fast-paced development is something we can all learn from to speed up our product development cycles. This cross-pollination of ideas is crucial as industries evolve and integrate more advanced technologies. By exploring best practices from other industries, companies can find innovative new ways to improve their processes and products. After all, how can someone think outside the box, if they are only looking in the box? If you are interested in learning more, I suggest checking out this article by my colleagues Todd Tuthill and Nand Kochhar where they take a closer look at how cross-industry learning are key to developing advanced air mobility solutions. https://lnkd.in/dK3U6pJf

AI won’t just enhance existing products. It will rewrite the product playbook. That was the core thesis from Sarah Guo, founder of Conviction, in our recent #MicrosoftPMCon. Here are 5 takeaways that left a lasting impression—and how I’m thinking about them as a product maker: 1️⃣ Don’t just add AI. Reimagine the product. Sarah distinguishes between AI-enhanced and AI-native. The latter doesn’t bolt AI onto workflows—it starts with the assumption that the product is the intelligence. I’m learning to ask: If this were built today from scratch—with an LLM as a teammate—what would it look like? 2️⃣ The most valuable products won’t be wrappers—they’ll be rethinkers. We’re past the "GPT inside" phase. The next wave requires scaffolding, orchestration, user trust, and graceful failure handling. Sarah compares it to how Salesforce rewrapped relational databases. The new "CRM wrappers" will be intelligent, fluid, and role-specific—not bound by legacy UX. 3️⃣ User understanding matters even more in AI. It’s not just about prompt tuning. Sarah emphasized that deep user empathy is essential when building agents that make decisions, not just surface info. Her portfolio companies hire lawyers to co-design legal AI tools and clinicians to build in healthcare. That level of domain fluency is what differentiates useful from magical. 4️⃣ New muscle groups are required. AI product development means navigating long-run tasks, unpredictable outcomes, and non-deterministic behavior. The best teams are blending product, infra, and research to ask: How do we make a 5-hour task feel delightful? How do we teach users to debug their AI teammates? 5️⃣ Product builders now need a ‘research ear’. In most tech eras, you could ignore what was happening in the labs. Now? The frontier shifts every two months. Sarah put it bluntly: If you’re not projecting capability curves, you’re building for a world that no longer exists. Curious: What skill do you think today’s PMs need that didn’t matter 3 years ago? Let’s learn from each other. —  👋 Hi! I’m Shyvee, I share insights on AI and the future of work. Subscribe for AI insights, programs, and an invitation to our AI Enthusiast Community: https://lnkd.in/eR2ebrEM #ProductManagement #AI #MicrosoftLife

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.

Forget the old “lab in the back” stereotype. Today, some CPG giants are dropping $30-100 million annually on R&D. This is serious growth engine for companies pulling in $10B to $30B in sales. Here’s what jumped out from a recent whitepaper I dove into: R&D isn’t just a support team for marketing anymore. The smartest CPG companies have put it front and center, giving R&D real power to shape what hits the shelves. Budgets are doubling at food, beverage, and household brands. These companies are betting big that new products = new growth. But money alone? That doesn’t cut it. The brands actually launching winning products, not just filing patents, have cracked a different code: Start with the consumer: They obsess over what people actually want. Cool patents don’t mean much if no one buys. Process matters: One exec nailed it. Trying to innovate without a solid process is like playing golf without a swing. Most have 70-100 projects cooking simultaneously, carefully categorized by risk: Low risk: Quick wins, building on what’s already working. Medium risk: Exploring new ground, but with some safety nets. High risk: Bold bets that can create entirely new product categories. If they pay off. Metrics rule: ROI, time-to-shelf, net present value. Every project gets scrutinized. Some firms aim for at least one game-changing launch every two years. Think $500M+ in fresh annual revenue. And here’s a bonus nugget: nobody’s innovating in a vacuum anymore. Open innovation is the norm: tapping into startups, suppliers, universities, even competitors. Bottom line: innovate or get left behind. R&D has officially shifted from “cost center” to a core revenue driver. The companies crushing it? They’re the ones treating R&D like a real business. Relentlessly shipping new products, over and over.