Importance Of Prototyping In Engineering

99% of high-performing software engineers I’ve worked with in the last 19 years of my career at Google, Paytm, Amazon, and startups had this one habit that made them stand out: → They used to build prototypes. Fast. Frequently. Even if they’re throwaway. It’s so much easier to reason about a real demo or code sample than to argue endlessly about abstract ideas. 🔁 Building trumps theorizing, every single time: ∟ A quick proof-of-concept > A detailed architecture doc You’ll find edge cases, constraints, and blockers in minutes, not weeks. ∟ 30 lines of code > 3 hours of debate Nothing kills overthinking faster than seeing something actually run. ∟ “Let me show you” > “Let’s brainstorm on a whiteboard” Teams align faster when they see a prototype in action, not just sketches and talk. ∟ One-day spike > Week-long design meetings Most teams need signals and feedback, not another round of speculation. ∟ Even a failed prototype > Weeks of “What if…” Because a failed demo answers more questions than a month of guessing. The best engineers get this: → Shipping something, even if it’s ugly, is the fastest way to stress-test your assumptions and bring others onboard. The feedback you get from a live prototype is 10x more valuable than a week of endless discussion. That’s how you cut through noise. That’s how you lead as an engineer.

Prototypes aren't for testing your product. They're for testing your assumptions. Most teams get this backward, and it costs them weeks of wasted effort and a product nobody wants. A prototype isn't a tiny product; it's a medium for learning. It's a tool designed to ask a specific question and test a core assumption with the right audience. An unintentionally designed prototype is a flawed input, and even with advanced teams and tools, flawed inputs only amplify flaws. The true power of a prototype isn't in its polish, but in the intentional "message" it sends. To unlock this power and truly accelerate collective learning across your organization, you must design with intent: ✺ Low-Fidelity Prototypes: These are for asking foundational, "Does this even solve the right problem?" questions. They signal that everything is up for debate. The intentional message is: "Let's explore the idea, not the pixels." ✺ Medium-Fidelity Prototypes: Use these to test core user flows and information architecture. The intentional message is: "Is this journey intuitive?" By keeping them a little rough, you prevent stakeholders from getting fixated on visual design. ✺ High-Fidelity Prototypes: Reserve these for the final stages to test things like micro-interactions, brand consistency, or subtle emotional responses. The intentional message is: "We're almost there. What are we missing?" This is how you turn prototyping from a simple task into a strategic lever for change and Team Learning. It ensures your team isn't just building things, but is learning together and making better decisions about what to build and why. It's how you break down silos and create a "Holding Environment" for generative dialogue. What's a time you intentionally used a low-fidelity prototype to prevent a high-stakes meeting from spiraling? Let’s discuss in the comments below. #ProductDesign #SystemsThinking #StrategicDesign #UXStrategy #DesignLeadership #ComplexSystems #TeamLearning #Prototyping #OrganizationalDesign #Innovation

"When people tell you something is wrong, they're usually right. When they tell you how to fix it, they're usually wrong" When renowned actor and comedian Bill Hader made this comment, he wasn't necessarily thinking about product development or engineering. Yet, this concept maps well onto those domains, serving as a valuable lesson for everyone from young product developers to seasoned engineers. At the heart of this idea is the recognition that feedback, particularly from users or customers, is an invaluable source of insight into problems. Users are highly adept at pointing out what's wrong or where pain exists. Their lived experience with a product or service often lends them a unique perspective, allowing them to identify issues that may not be immediately apparent to those who designed or built it. However, the translation of these problem areas into workable solutions is a skill set that resides more comfortably with the creators—the engineers and product developers. This is where the second part of Hader's observation rings true. When users propose solutions, they often reflect a personal perspective or a narrow view of the problem, unaware of technical complexities, overarching product strategy, or design constraints. We might cringe when we hear, "we just went to users and asked them what they wanted." This approach, although seemingly customer-centric, can lead to misguided efforts and misplaced resources. It risks being swayed by articulate or loud voices, and not by genuine, widespread needs. It's crucial to take a step back and reconsider how we approach and utilize feedback. Product teams and engineers should listen attentively to the problems users describe, then apply their professional knowledge and expertise to devise appropriate solutions. This ensures that we are addressing real issues in the most efficient and effective way, driving innovation rooted in user needs while retaining a firm grasp on feasibility and strategic alignment. This principle is perhaps more nuanced in the field of engineering. Unlike the arts, engineering leans towards empirical, often quantifiable solutions. There are standards, best practices, and established methodologies that provide guidelines. Still, the core concept remains—listen for the problem, and then employ your expertise to devise the solution. So, the next time you receive feedback, remember: focus on the issue at hand and leverage your own skills, knowledge, and creativity to find a solution. Doing so will allow you to turn insights into innovation, driving your product or project towards success. Feedback, when decoded correctly, can be one of the most powerful tools in your arsenal. #learning #productivity #product #engineering 

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

PROTOTYPES ACCELERATE DISCOVERY, NOT DELIVERY Prototypes are powerful tools for the discovery phase — helping teams quickly explore product directions, validate concepts with customers through high-fidelity experiences, and align executives around tangible visions. The leverage they provide in answering "what's the right experience to build?" is remarkable. However, I frequently see PMs expecting to hand prototypes directly to engineering teams for production implementation. This approach consistently leads to disappointment. Here's why: prototype code isn't built to meet the security, reliability, robustness, and maintainability standards that production systems require. Your engineering team rightfully prioritizes these critical attributes. And that's perfectly fine. The value of prototypes lies entirely in discovery. Even when engineering teams ultimately rebuild from scratch, prototypes have already delivered tremendous ROI by: - Accelerating team alignment on product direction - Validating customer demand with realistic experiences - Securing executive buy-in through tangible demonstrations The code was never meant to ship — the insights were.

I had the chance a few weeks ago to sit down (virtually of course) with Woodrow Bellamy III, host of SAE’s Aerospace & Defense Technology podcast, for a candid conversation about virtual prototyping. While I work across many industries these days, I always enjoy a chance to share insights from my years working in Aerospace. The key question was about the reliability of virtual prototyping as a replacement for physical prototyping. How much faith can be put into a digital model for accurately simulating a real-word system, when you have real-world stakes and consequences? The answer is: a lot. When we first started using simulation for some of the aircraft programs I worked, we questioned if we could trust the results to predict peformance of a new aircraft. It was an appropriate question to ask. It was only after conducting extensive testing to validate the results of the simulation against an existing aircraft that we started to trust the simulation models while designing a new aircraft. The same litmus test will be needed for companies in any industry to take the leap with virtual prototyping: A company can start by developing the virtual model and ensure the validity and robustness of the simulation by comparing against existing physical products. Once the team is sufficiently confident about the performance of the digital model, they can take the insights from existing products and systems and apply them toward the development of future projects. The digital twin of a physical system is infinitely more malleable. It can be designed, tested, and experimented upon with far more ease and using significantly fewer resources. Virtual prototypes allow for limitless design exploration, help to identify design issues early and before building physical prototypes, and make physical testing more effective. Before going for the real-life testing, virtual analyses highlight critical areas in the design, and the test plans can be adjusted to focus on areas of greatest concern. The aerospace industry adopted the use of the digital twin as a revolutionary design tool decades ago. And the digital twin has evolved quite a bit over the ensuing decades. It is no longer just a 3D model of a product or process. Today, the comprehensive digital twin is a precise virtual representation of the product that replicates its physical form, function and behavior and encompasses all cross-domain models and data from mechanical and electrical through software code. So, although the current ratio of prototyping testing, worldwide, may be 90% physical and 10% digital, it isn’t an overstatement to conceive of a future where the ratio is flipped; maybe even 100% digital. I'm excited about the opportunities offered by virtual prototyping and testing as a means to enable companies to develop and validate innovative products faster! To check out my conversation with Woodrow, please check out the link in the comments. #digitaltransformation #siemensxcelerator

A $12 prototype can make $50,000 of engineering analysis look ridiculous A team of engineers was stuck on a bearing failure analysis for six weeks. Vibration data, FFT analysis, metallurgy reports - they had everything except answers. The client kept asking for root cause and the engineers kept finding more variables to analyze. Temperature gradients, load distributions, contamination levels, manufacturing tolerances. Each analysis created more questions. Then the intern did something that made the engineers feel stupid. She 3D printed a transparent housing and filled it with clear oil so the engineers could actually see what was happening inside the bearing assembly. Took her four hours and $12 in materials. They watched the oil flow patterns and immediately saw the lubrication wasn't reaching the critical contact points. All their sophisticated analysis was based on assuming proper lubrication distribution. Wrong assumption. Six weeks of wasted effort. The visual prototype didn't just solve the problem - it changed how the engineers approach these types of investigations. Now they build crude mockups before diving into analysis rabbit holes. Cardboard, tape, clear plastic, whatever works. Physical models force you to confront your assumptions before you spend weeks analyzing the wrong thing. Sometimes the cheapest prototype teaches you more than the most expensive simulation. #engineering #prototyping #problemsolving

I used to think user research was easy. But then I switched to B2B. And oh boy... reality hit hard Back when I was working on a B2C product, I could run 10 user interviews in a day. Users would happily spend 45 minutes answering questions and testing new designs. I thought this was just regular product design. Turns out, I was riding a perfect wave of continuous discovery without even realizing it. Then I switched to B2B. And I admit it really felt scary at first. Users were just too busy to pick up my phone calls. It took 3 weeks to schedule 5 calls. Some users left a bad CSAT score with barely any comment. Damn. How can we build anything serious without ever talking to users? At that time, it really felt like an impossible task. And any way I tried to put it, there were just no efficient process to get those users on the phone. But then it hit me. What if the best discovery touch points weren’t designers or PMs at all? What if they were already happening… in sales calls, support chats, internal Slack threads? And we had this feedback scattered across tools, threads, and people. But no one was making sense of it. So we built a Feedback Management System. We plugged every feedback into a single source of truth directly in Notion: - Intercom conversations and Modjo calls with customers - Internal tickets from sales and support to discuss user pain points or feature requests - User feedback forms submitted on the platform All filtered and organized per team through Notion automations. Each designer spends 2 hours per week turning raw feedback into structured insights. Then each team reviews it together weekly, and it feeds product decisions and the roadmap. It’s simple. It’s scalable. And it changed everything. Product designers no longer design based on shaky assumptions or partial data. They're now the source of customer truth and alignment. In B2B, discovery doesn’t happen in a lab. It happens in the wild. You just need to know where to listen. #productdesign #uxdesign #userresearch

What if the best solutions for your process started with cardboard? When testing new ideas or improvements, jumping straight to high-cost, permanent solutions can be risky—and expensive. That’s where cardboard engineering comes in. Cardboard is one of the simplest, most cost-effective tools for rapid prototyping and testing ideas. It’s lightweight, easy to shape, and lets you visualize, test, and refine your concepts before committing to more expensive materials. Why Cardboard Is Perfect for Prototyping: 1️⃣ Low-Cost Experimentation Testing with cardboard lets you try multiple iterations of a design without worrying about material costs. 2️⃣ Fast Feedback Loops You can build and modify a prototype in minutes, gathering instant feedback from your team or operators. 3️⃣ Hands-On Collaboration Cardboard prototypes allow teams to actively engage with ideas, making it easier to identify issues or opportunities for improvement. 4️⃣ Visual Validation Sometimes, seeing a physical model highlights challenges that wouldn’t be obvious in a drawing or plan. How to Use Cardboard for Lean Improvements: 🔍 Test Workstation Layouts Use cardboard cutouts to mock up layouts and placement of tools, parts, and equipment. Adjust until everything flows smoothly. 📦 Simulate Material Flow Prototype racks, bins, or carts to ensure materials are stored and moved efficiently before building them with more durable materials. 🛠️ Design Fixtures or Jigs Create cardboard versions of fixtures or jigs to test their functionality in the process. Refine the design before investing in the final version. 📐 Test Ergonomics Mock up equipment or workstation designs with cardboard to test ease of use, reach, and operator comfort. Example of Cardboard in Action: A manufacturing team wanted to redesign a workstation to reduce operator motion. Instead of committing to expensive reconfigurations, they used cardboard to prototype the layout. After several iterations, they found the optimal setup, reducing motion by 25% and saving hours of work. Cardboard isn’t just for packaging—it’s a powerful tool for testing and refining your ideas. By prototyping with low-cost materials, you can experiment, learn, and improve quickly without breaking the bank.

Prototyping a system in small numbers on a tight timeline can lead to interesting decisions. For instance, it was quicker and more cost-effective for us to source a copper-core PCB than a sheet-metal part.   In the Framework Laptop SDR, we use two heat pipes to cool the AFEs. The heat pipes are soldered to a 1mm copper sheet that sits on top of the AFEs. Instead of using a copper sheet metal part with a surface finish suitable for low-temperature soldering, we found that, in low quantities, it was much faster to source a copper-core PCB. The surface finish and planarity of the copper-core PCB are also subject to much tighter process control. With a lead time of only two days, and the added benefit of being able to place sensors directly on the heat spreader, it proved to be a much better option than a sheet metal part. The heat pipes are in direct contact with the copper core at critical points, so the thermal performance is equivalent to that of a plain copper sheet.   For higher quantities, the copper sheet metal part is of course a lot cheaper, due to fewer processing steps. However, we might even stick with the copper core PCB solution due to the added benefit of being able to place sensors on the heat spreaders without the need for wiring. #design #hardware #electronics