Innovation in Product Development

In the late 1990s, a 53-year-old toy inventor looked at the $80 electric toothbrushes on the market and thought: this is overengineered. John Osher wasn’t a dentist. He was a product guy who had built his career in toys. One of his biggest hits? A battery-powered lollipop that spun in your mouth. It sounded silly. It sold like crazy. But what he really built was manufacturing insight. If you can mass-produce a small motorized gadget for kids at ultra-low cost, why can’t you do the same thing for adults brushing their teeth? That question led to a radically simple idea: a battery-powered toothbrush that actually worked, ran on AA batteries, and cost about five dollars. No premium positioning. No luxury pricing. Just volume and accessibility. And then he added a retail hack: a button on the package so shoppers could turn it on in the aisle. No ad campaign could compete with that moment of tactile proof. They called it Spinbrush The product exploded. Shelves cleared. The data was undeniable. When Procter & Gamble got their hands on it, they didn’t just want to put their brand on it. They bought the entire company. The deal: roughly $475 million. The lesson isn’t about toothbrushes. It’s about transfer learning. John Osher didn’t invent new technology. He applied toy economics to a stagnant category and changed the price-performance equation overnight. That’s pattern recognition at scale. Hear the full story on How I Built This with @guy.raz.

AI Product Management AI Product Management is evolving rapidly. The growth of generative AI and AI-based developer tools has created numerous opportunities to build AI applications. This is making it possible to build new kinds of things, which in turn is driving shifts in best practices in product management — the discipline of defining what to build to serve users — because what is possible to build has shifted. In this post, I’ll share some best practices I have noticed. Use concrete examples to specify AI products. Starting with a concrete idea helps teams gain speed. If a product manager (PM) proposes to build “a chatbot to answer banking inquiries that relate to user accounts,” this is a vague specification that leaves much to the imagination. For instance, should the chatbot answer questions only about account balances or also about interest rates, processes for initiating a wire transfer, and so on? But if the PM writes out a number (say, between 10 and 50) of concrete examples of conversations they’d like a chatbot to execute, the scope of their proposal becomes much clearer. Just as a machine learning algorithm needs training examples to learn from, an AI product development team needs concrete examples of what we want an AI system to do. In other words, the data is your PRD (product requirements document)! In a similar vein, if someone requests “a vision system to detect pedestrians outside our store,” it’s hard for a developer to understand the boundary conditions. Is the system expected to work at night? What is the range of permissible camera angles? Is it expected to detect pedestrians who appear in the image even though they’re 100m away? But if the PM collects a handful of pictures and annotates them with the desired output, the meaning of “detect pedestrians” becomes concrete. An engineer can assess if the specification is technically feasible and if so, build toward it. Initially, the data might be obtained via a one-off, scrappy process, such as the PM walking around taking pictures and annotating them. Eventually, the data mix will shift to real-word data collected by a system running in production. Using examples (such as inputs and desired outputs) to specify a product has been helpful for many years, but the explosion of possible AI applications is creating a need for more product managers to learn this practice. Assess technical feasibility of LLM-based applications by prompting. When a PM scopes out a potential AI application, whether the application can actually be built — that is, its technical feasibility — is a key criterion in deciding what to do next. For many ideas for LLM-based applications, it’s increasingly possible for a PM, who might not be a software engineer, to try prompting — or write just small amounts of code — to get an initial sense of feasibility. [Reached length limit. Full text: https://lnkd.in/gYY-hvHh ]

Anthropic’s “Prompting 101” is one of the best real world tutorials I’ve seen lately on how to actually build a great prompt. Not a toy example. They showcase a real task: analyzing handwritten Swedish car accident forms. Here’s the breakdown: 𝟭. 𝗣𝗿𝗼𝗺𝗽𝘁𝗶𝗻𝗴 𝗶𝘀 𝗶𝘁𝗲𝗿𝗮𝘁𝗶𝘃𝗲. You don’t write the perfect prompt on the first try. You test, observe, refine. Just like any other product loop. 𝟮. 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗺𝗮𝘁𝘁𝗲𝗿𝘀. The best prompts follow a playbook: - Start with task + tone context - Load static knowledge into the system prompt - Give clear rules and step-by-step instructions - Show concrete examples - Ask the model to think step-by-step - Define structured output 𝟯. 𝗗𝗼𝗻’𝘁 𝘁𝗿𝘂𝘀𝘁 𝘁𝗵𝗲 𝗺𝗼𝗱𝗲𝗹, 𝘆𝗼𝘂 𝗻𝗲𝗲𝗱 𝘁𝗼 𝗱𝗲𝘀𝗶𝗴𝗻 𝗳𝗼𝗿 𝗶𝘁. In the first version, Claude hallucinated a skiing accident. Only after adding context, rules, and constraints did it produce reliable results. You wouldn’t let a junior analyst guess on regulatory filings. Don’t let your LLM do it either. 𝟰. 𝗧𝗵𝗲 𝗽𝗿𝗼𝗺𝗽𝘁 𝗶𝘀 𝘁𝗵𝗲 𝗶𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲. In traditional software, interfaces are buttons and APIs. In GenAI, the interface is language. Your prompt is the program. Most teams still treat prompts like notes in a playground. High-performing teams treat them like production code. That's why in our IBM watsonx platform, prompts are assets just like code or data. 👉Access the video tutorial here: https://lnkd.in/gUdHc2uy ________________________ ♻️ Repost to share these insights! ➕ Follow Armand Ruiz for more

When Style Disrupts Safety: A Lesson in Product Design Today, while driving behind the sleek Mahindra BE.6E, a futuristic and stylish EV, I experienced something unexpected. The car in front of me braked suddenly. I had maintained a safe distance, so I stopped comfortably. But something felt off. Why did the braking catch me off guard? Then I realized: The brake lights were too subtle. The taillights are designed as a thin rectangular LED strip, stunning to look at, no doubt. But the brake lights occupy only a tiny section on the top edge of that strip. Visually stylish, but functionally weak. In real traffic conditions, where immediacy and clarity are critical, this design doesn’t help other drivers react intuitively. This reminded me of a fundamental product design principle: Aesthetics must never come at the cost of usability. A good product delights not just by how it looks but by how well it works. Whether we’re designing: • A mobile app • A banking interface • Or a car’s tail lights …it’s our job as product managers and designers to make sure the experience is not just elegant, but intuitive, accessible, and safe. Lesson for us in Product Management: Design for the user’s reality, not just the brand’s imagination. Functionality and clarity should never be hidden behind a glossy UI, whether it’s a screen… or an LED strip on a car. #ProductManagement #UXDesign #Usability #AutomotiveDesign #DesignThinking #BuildWithEmpathy

The future of footwear may not be manufactured in bulk. It may be fabricated around you. That is what makes this shift so interesting to me. 3D-printed footwear is moving from novelty to a real industrial model, with market forecasts pointing to rapid growth over the next decade. At the same time, brands and manufacturers are using additive manufacturing, digital design, and custom-fit workflows to shorten development cycles and make more personalized products viable. What is new here is not just the printer. It is the system around it: → scan the foot → model the fit digitally → print the part on demand → produce closer to the customer That matters. Because once footwear becomes data-driven and locally fabricated, several things change fast: → fit gets more personal → prototyping gets faster → waste drops because you do not overproduce → inventory pressure falls because you do not need to guess demand the same way To me, that is the bigger signal. This is not just about a better sneaker. It is about a different manufacturing logic. Formlabs notes that 3D printing already enables customized orthotics with better biomechanical precision, lower material waste, and simpler digital workflows. McKinsey has also pointed to digitization and 3D design as a way to shorten design cycles and reduce sampling iterations in apparel and footwear. And once that logic matures, the use cases get much bigger: → custom athletic footwear built from gait and pressure data → hospitals producing orthotics faster and closer to the patient → micro-factories making products on demand instead of stocking shelves → footwear designed for one body, not an average body That is why I think this matters now. The question is no longer whether personalized fabrication is possible. It is whether brands move fast enough before customers start expecting every product to fit like it was made only for them. Would you actually wear a shoe fabricated around your own biometric data? #AI #3DPrinting #Footwear #Manufacturing #Innovation #FutureOfWork #RetailTech #Customization #Technology

When packaging becomes part of you Wearable packaging is no longer a futuristic concept it's a growing design frontier that merges functionality, fashion, and emotional connection. Beyond the shelf: packaging you can wear From fragrance necklaces to ring-shaped lip balms and refillable compacts designed like jewelry, beauty brands are transforming packaging into accessories. The product becomes not just something you use, but something you wear turning daily rituals into statements of identity. Why it works In a world saturated with options, wearable packaging offers immediacy, memorability, and emotional value. It adds a layer of meaning: a perfume worn around the neck is not just a scent, it’s a story you carry. A lipstick shaped like a pendant becomes both utility and ornament. It taps into consumers’ desire for customization, portability, and aesthetic expression particularly among Gen Z and Millennials who seek objects that are both functional and symbolic. A new layer of storytelling Wearable formats create a deeper connection between brand and user. They’re conversation starters, collectible, and often more sustainable built for reuse and ritual, rather than discard. Design becomes not only a visual differentiator but a tactile, emotional experience that enhances the perceived value of the product. From beauty to fashion and back again This blurring of categories also opens doors to cross-industry innovation. When beauty products act like accessories, they enter the realm of fashion making room for brand collaborations, limited editions, and viral potential on social media. It’s no longer just about packaging design. It’s about presence. Relevance. And creating a product people don’t want to put away — they want to put on. Featured brands: Rhode Bubble Yepoda Laneige #WearablePackaging #CosmeticAccessories #FragranceOnTheGo #LuxuryPackaging #EmotionalDesign #GenZBeauty #FutureOfBeauty

The average Muslim family in Britain pays thousands more for their Islamic mortgage. And God willing, we're about to fix that Islamic mortgage premium forever: Our home finance fund just passed £40 million. For context, that's tiny in the grand scheme of UK mortgages. But I think it might be the most important £40 million in Islamic finance right now. Here's why. The dream for the Muslim community in the UK has always been simple: get a house in an Islamic way that's priced the same as everyone else's mortgage. That's it. Not asking for much. But the reality is that Islamic home finance has consistently been 1-2% more expensive. On a typical mortgage, that's tens of thousands of pounds extra. So Muslims face this horrible choice - their principles or their financial well-being. What we're doing with this fund is actually quite straightforward. We're providing funding lines to Islamic home finance providers. We've backed Stride Up and Offa. And we've got plenty more in the pipeline. The mechanism is simple: more providers mean more competition. More competition means better pricing. It's not revolutionary economics, but nobody was doing it at scale before. The interesting bit is what happens next. Once we solve the pricing problem - and I genuinely think we will in the next 2-3 years - we can start innovating on the actual mortgage structure itself. Making products that aren't just Sharia-compliant copies of conventional mortgages, but genuinely better alternatives. Maybe products that share risk more equitably. Maybe structures that work better for freelancers or entrepreneurs. Maybe even products that non-Muslims would choose because they're simply superior. We're not there yet. £40 million is just the beginning. But when we hit £400 million? That's when this market fundamentally changes. The path from "Islamic finance is always more expensive" to "Islamic finance is the obvious choice" - that path is actually visible now. And that's quite exciting. PS - for those of you interested in learning more about investing in this fund with us, head over to https://bit.ly/4hmW34S. PPS - If you're an experienced or high-net-worth investor considering an allocation of USD100k+ then fill out this Typeform, and myself or a member of our experienced investment team will personally be in touch: https://lnkd.in/d3w6HHjT

What does it actually take to put GLP-1 in a pill?   The headlines make it sound simple – scientists figured out how to turn an injection into a tablet. But the reality behind this breakthrough tells a very different story.   To develop our oral GLP-1 pill for obesity treatment, we tested 217 different molecules. Only one worked.   To solve the challenge of protecting GLP-1 from stomach acid – so it could remain active for a full week in pill form – we tested 70 different research technologies. We finally found success with one called SNAC.   We could have decided to go an easier way, but that would never have led to an “injection in a pill”. We could have compromised, but that would not be us.    This is the reality of pharmaceutical innovation. It requires being relentless in the pursuit of solutions, resilient through countless setbacks, and persistent when others might give up.   That's what 30 years of pioneering research has taught us: breakthrough science requires breakthrough persistence.

This furniture isn't made with wood, but something you wouldn't expect! And it’s helping to fight deforestation! Indowud from India, have found a way to make everything from doors, decking and furniture using rice! Rice husks, the outer shell left behind after rice is harvested, are turned into strong, versatile boards that are waterproof, flame-resistant, and 100% recyclable. Helping reuse agricultural waste and prevent trees being cut down for wood. First the rice husks are dried and ground into a powder. Natural resins are added, then the mix is heated and pressed into shape. Resulting in a strong moldable material, that can be cut and shaped, just like wood! It’s designed to replace materials like MDF and plywood, which are often full of toxic resins and can't be recycled. Indowud even have a buy-back program to recycle old boards into new ones, creating a more circular system. Would you use furniture made from rice?

India has 150 million+ people above the age 60 and there is a massive opportunity to keep them healthy & fit. But everyone’s focused on Gen Z and no one’s building for their parents. It’s a hard business but a big one. We’ve invested in two companies. Here’s why it’s tough and how one should crack it. Understand the reality first. 1. Elders don’t think of “health” as proactive. They’re conditioned to wait until something breaks before acting. You’re selling a solution to a problem they don’t know they have yet. 2. The 65-year-old needs it but their 35-year-old child pays for it. You're not selling to the elder. You’re selling to their guilt-driven kids in Gurgaon or US. The buyer ≠ the user. 3. Trust is everything and you don’t have it. Indian elders trust: Their doctor, astrologer & their neighbour Not apps. Not tech bros. Not AI. You can't growth hack trust. You earn it slowly, locally. 4. They don’t want new habits. They’ve had the same breakfast for 40 years. You’re not selling a product. You’re undoing decades of routine. 5. Distribution is hyperlocal. Elders don’t click Insta ads. They talk to the uncle in their colony. You scale building by building not by user cohorts. Yes, 150M+ elders. But it’s not one market. It’s a thousand tiny tribes. Different languages, cultures, food habits, family structures, and tech comfort levels. If it were easy, Tata or Reliance would’ve done it already. But it’s wide open now. The one who combines tech + trust + real care will win. So how do you crack it? 1. Think first principles & not trends Don’t build a “senior fitness app.” Ask: Why did they stop moving? What gives them joy? You’re selling independence, not health. 2. Design for peace, not features. One-click help, One daily routine, One trusted face. Great elder products feel like human care not software. 3. Human-first, tech-enable. Don’t replace the daughter. Support her. Train 100 amazing elder coaches. Build tools to help them scale. 4. Don't focus on CAC. Here, it’s about trust per acquisition. You’re not selling toothpaste. You’re asking to be let into their daily life. Start offline. Build trust then tech. 5. You’re in the business of habit change & not selling an app or a pill. Get them to walk 15 minutes a day. Add protein to breakfast. Laugh more. Sleep better. Small wins compound. Don’t build for scale first. Build for consistency. Be in the business of habit change. 6. This isn’t a hackable D2C play. It’s a decade-long trust business. Build for one community. Get to know 100 elders by name. Solve deep, boring problems with elegance. Everyone’s chasing the next billion youth users. But the hidden opportunity lies in serving the first 150 million elders. The elder care market in India isn’t just underserved. It’s misunderstood and needs long-term play. Founders who crack this will build generational companies.