This Feature Will Save Us

Steven Webster - When Fitness Products Start Acting Like Coaches

Steven Webster thinks fitness products have become too obsessed with scores and dashboards. His alternative is much closer to the way a coach actually works: observing what's happening, understanding the context and stepping in when needed. That idea runs through much of what ASENSEI is building with movement recognition and AI. Steven joins Marco and Jonas to talk about moving from apps to agents, the proprietary language ASENSEI built to describe human movement, and why that language became unexpectedly valuable with LLMs. They also get into the product decisions behind a 12-year journey: building toward technology that didn't exist yet, letting customers influence the roadmap without simply reacting to requests, deciding what not to build, and making an early bet on on-device AI. Steven breaks down: → Why fitness products have become too obsessed with scores and dashboards → What conversational coaching could look like as products move from apps to agents → How ASENSEI built a language for human movement and why LLMs made it more valuable → How to build toward a product vision when the technology doesn’t exist yet → How ASENSEI lets customers influence the roadmap without simply reacting to requests → Why knowing what’s core to the product also means knowing what not to build → Why ASENSEI is betting on on-device AI for coaching Follow Steven Webster LinkedIn: Steven Webster Website: ASENSEI Follow Marco Benitez and Jonas Dücker LinkedIn Marco: Marco Benitez LinkedIn Jonas: Jonas Dücker Get in touch with This Feature Will Save Us Podcast LinkedIn: https://www.linkedin.com/showcase/this-feature-will-save-us Website: https://thisfeaturewillsaveus.com/ Powered by ROOK: https://www.tryrook.io/ 0:00 - Rapid fire with Steven 3:35 - Why fitness is too obsessed with scores and dashboards 6:10 - Coach vs machine: who gives better feedback? 8:45 - Moving from apps and screens to conversational experiences 13:00 - What changes when an AI coach already has the context 15:00 - How ASENSEI uses movement recognition for AI coaching 18:00 - From martial arts and Adobe to building ASENSEI 22:30 - Why ASENSEI started with indoor rowing 25:00 - Building a language for human movement 26:30 - Why that movement language became valuable with LLMs 29:30 - Product evolution vs pivoting 33:00 - Building toward technology that doesn’t exist yet 37:00 - Designing for your customer’s customer 42:00 - Knowing what’s core and what not to build 44:00 - Reactive roadmaps vs acting ahead of the market 47:00 - Why ASENSEI is betting on on-device AI 50:00 - The feature that will save us: an agentic workforce

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Nick Longo - When Does Software Make Gym Equipment Better?

Nick Longo has spent the last five years at Life Fitness / Hammer Strength, starting as a biomechanics engineer before moving into product management and, more recently, partnerships and integrations. He’s seen how seemingly simple product decisions can play out once equipment is actually in the gym. Making Quick Start easier to use on treadmills got people moving faster, but usage of other workouts dropped. Bringing casting to commercial equipment meant solving problems that don’t exist at home, especially when 20 treadmills are lined up next to each other. Nick talks with Marco and Jonas about those decisions, why serviceability and uptime have such a big influence on product design, and how he evaluates partnerships when they have to compete with the company’s own product work for resources. They also get into where today’s wearable integrations come up short and what could be possible if workout and recovery data moved more easily between the products people already use. Nick breaks down: → Why serviceability and uptime have such a big influence on commercial fitness equipment design → What happened when Life Fitness / Hammer Strength made Quick Start easier to use → Why bringing casting into a commercial gym is harder than doing it at home → What Nick looks at when deciding whether a partnership or integration is worth pursuing → Why partnership work can be difficult to prioritize against internal product development → Where today’s wearable integrations still come up short → What could change if workout and recovery data moved more easily between wearables and fitness equipment → How Life Fitness / Hammer Strength learns how people use equipment that isn’t connected → Why product teams sometimes need to zoom out from the feature or product in front of them → How Nick decides when negative feedback is something the product team needs to act on Follow Nick Longo: LinkedIn: Nick Longo Life Fitness/Hammer Strength: lifefitness.com Follow Marco Benitez and Jonas Dücker LinkedIn Marco: Marco Benitez LinkedIn Jonas: Jonas Dücker Get in touch with This Feature Will Save Us Podcast LinkedIn: https://www.linkedin.com/showcase/this-feature-will-save-us Website: https://thisfeaturewillsaveus.com/ Powered by ROOK: https://www.tryrook.io/ 00:00 Rapid-fire with Nick Longo 07:00 Designing for serviceability and uptime 12:00 Evaluating partnerships and integrations 15:00 Bringing casting to commercial fitness equipment 18:00 When Quick Start changed how people used workouts 23:00 Where wearable integrations fall short 25:00 Connecting workout and recovery data to equipment 27:00 Software, subscriptions and the fitness equipment business 33:00 Learning from equipment that isn’t connected 37:00 Knowing when to zoom out from the product 39:00 Handling negative feedback after product changes 41:00 Prioritizing partnerships against internal product work 45:00 What Nick wants to see next in connected fitness

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Rohit Nambiar - Great Execution Should Be Boring

After more than 20 years in large organizations, Rohit Nambiar decided that if he really wanted to understand AI, he needed to get his hands dirty. That took him from studying AI at MIT and advising startups to building one himself. Today, he’s CEO and co-founder of Sabai, an AI-powered health companion, where the move from corporate leadership to startup life has put him much closer to the day-to-day work of building, testing and growing a product. Rohit joins Marco and Jonas to talk about what that experience has taught him about product and execution, including why the day-to-day discipline behind good execution can be surprisingly boring. They also get into building a remote team, deciding when to keep going and when to cut, and where Rohit thinks human judgment still matters as more of the work gets done with AI. Rohit breaks down: → Why the feature a product team spends the most time on may not be the one users actually value → What he looks at when deciding whether to keep iterating or cut → How product usage changes across markets, languages, and urban versus rural users → What he’s learned from building a fully remote team across several countries → Why he thinks execution matters more than strategy → Why he focuses on lead indicators like usage, retention, and acquisition → How Sabai approaches guardrails for AI in healthcare → Why he asks his team to share their AI prompts, not just the finished output Follow Rohit Nambiar: LinkedIn: Rohit Nambiar Website: SabaiHealth Book: The Simplicity Trap Get in touch with This Feature Will Save Us Podcast LinkedIn: https://www.linkedin.com/showcase/this-feature-will-save-us Website: https://thisfeaturewillsaveus.com/ Powered by ROOK: https://www.tryrook.io/ 1:45 - Why healthcare and insurance struggle with trust and complexity 6:05 - Where Rohit looks for talent and why his startup is fully remote 8:15 - Building culture and accountability across a remote team 11:30 - Leaving corporate life, learning AI and becoming a startup founder 13:10 - Building Sabai’s MVP and the problems that showed up after launch 14:00 - Growing from 3,000 to 35,000 users and what Sabai is building 17:15 - Product bets that worked, failed and surprised Rohit 19:45 - Why Sabai’s medication reminder became an unexpected hit 22:10 - Using data to decide whether to iterate, persevere or cut 24:50 - When a product is too early versus solving a problem that doesn’t exist 26:00 - Building guardrails for AI in healthcare 29:30 - Why culture comes before frameworks when building quickly 32:00 - Why execution beats a brilliant strategy 33:55 - The lead KPIs Rohit uses to manage the business 36:45 - Why human judgment becomes more important as AI gets better 37:55 - Why Rohit asks his team to share their AI prompt

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Ed Buckley - Great Distribution Beats a Great Product

Ed Buckley has built companies across fitness, healthcare and education, including Peerfit, Sword Intelligence and now Scholar. Along the way, he’s changed how he thinks about what makes a product successful. Distribution is a much bigger part of the equation now. Ed would rather have a good product with great distribution than a great product with good distribution. For him, that starts with knowing who will use the product, who will pay for it, and where the biggest opportunity for distribution actually is. Ed joins Marco and Jonas to talk about what he’s learned from building and selling products across very different markets. They get into finding the right distribution channels, the deal with Peloton during COVID, building inside Sword Health, what happens when a product looks right on paper but people don’t use it, and where he draws the line on customization. Ed breaks down: → Why he’d rather have a good product with great distribution than a great product with good distribution → Why product teams need to think about who uses the product and who actually pays for it → How product adoption and usage shape what matters in an enterprise product → Why selling Sword Intelligence meant bringing product and engineering into the sales process → How an earlier relationship with Peloton turned into a deal when COVID changed the fitness market → What to look at when a product makes sense on paper but customers still aren’t using it → How a feature around special education accommodations became the focus of Scholar → Where he draws the line between enterprise customization and individual personalization Follow Ed Buckley: Website: edwardjbuckley.com LinkedIn: Ed Buckley Instagram: @ejgatoriii Scholar Education: joinscholar.com Follow Marco Benitez and Jonas Dücker LinkedIn Marco: https://www.linkedin.com/in/marcobzg/ LinkedIn Jonas: https://www.linkedin.com/in/jonas-ducker-37460bb3/ Get in touch with This Feature Will Save Us Podcast LinkedIn: https://www.linkedin.com/showcase/this-feature-will-save-us Website: https://thisfeaturewillsaveus.com/ Powered by ROOK: https://www.tryrook.io/ 0:25 - Welcome and rapid-fire questions with Ed 5:45 - Why Peerfit was the hardest company Ed built 7:05 - Why great distribution can beat a great product 9:30 - What changes when almost anyone can build a decent product 11:30 - The difference between the person using the product and the person paying for it 13:30 - How product supports distribution in enterprise 16:45 - Selling across employers, insurers, schools and hospitals 17:55 - Why Sword Intelligence brought product and engineering into sales 19:55 - Learning to lead when you’re no longer the subject matter expert 21:35 - From Peerfit to FitOn Health, Scholar and Sword Intelligence 24:50 - How the Peloton deal came together during COVID 30:20 - When a product should work on paper, but doesn’t 32:15 - The teacher request that changed Scholar 33:55 - How one feature became the focus of the company 36:30 - How easier development changes the customization question 37:40 - Enterprise customization vs. individual personalization 40:55 - The next feature Scholar is trying to figure out

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Jason David - The Gym Owner Is Never the Problem

Jason spent years running a CrossFit gym before he started building Gym Force. That experience gave him a pretty specific view of what wasn't working. He'd used gym management software, marketing tools and outside business support, but having access to more tools didn't necessarily make running the business any easier. Now he's on the other side, building a product for the kind of operator he used to be. Jason talks with Marco and Jonas about how that experience has shaped Gym Force, from the problems they chose to build around to how they listen to gym owners without taking every request at face value. They also spend time on community and what actually makes people stay with a gym. The discussion gets into the role of coaching, learning and skill development, where technology fits into those relationships, and where Jason thinks it doesn't. Jason breaks down: → What running a gym taught him about the software built for operators → How Gym Force identifies the problems worth building around → Why customer requests don't always lead to the right product decisions → What "the gym owner is never the problem" means for the way they build → How Gym Force thinks about measuring whether the product is actually working → Why community plays such a large role in Jason's thinking about fitness products → Where technology can help coaches and gym owners, and where Jason draws the line Follow Jason: LinkedIn: https://www.linkedin.com/in/jason-david-2642371/ Website: https://gymforce.app Follow Marco Benitez and Jonas Dücker LinkedIn Marco: https://www.linkedin.com/in/marcobzg/ LinkedIn Jonas: https://www.linkedin.com/in/jonas-ducker-37460bb3/ Get in touch with This Feature Will Save Us Podcast LinkedIn: https://www.linkedin.com/showcase/this-feature-will-save-us Website: https://thisfeaturewillsaveus.com/ Powered by ROOK: https://www.tryrook.io/ 0:21 - Welcome and quick questions with Jason 4:31 - Jason's path from CrossFit gym owner to building for gym operators 5:41 - How COVID exposed the business side of running a gym 6:51 - Having the software doesn't mean the problem is solved 8:51 - Wanting to coach without constantly selling and finding new members 12:11 - Why the gym owner is never the problem 13:01 - What Gym Force is being built to do 13:46 - Building the roadmap around customer struggling moments 14:31 - How Gym Force thinks about measuring success 15:21 - Identifying what gym owners are actually struggling with 17:16 - What customers ask for vs. what they're trying to accomplish 18:51 - Connecting independent gyms with corporate wellness 21:01 - The missing data between fitness, employers and insurance 28:01 - Is community actually the product in fitness? 28:41 - Why lasting communities need learning and skill development 31:11 - Building around coaches and communities 35:41 - What the fitness industry should stop building

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Dave Hannum - Stop Building Features Just Because You Can

Dave Hannum has spent more than 30 years building products in the fitness industry. He led product and business development at Technogym before founding Functional Solutions, one of the early platforms for connected fitness and digital coaching. For most of his career, building software meant working within engineering constraints. Today, those constraints are changing. Dave shares how that shift is changing the way product teams think about roadmaps, customer feedback, feature development, and where real competitive advantage comes from. The conversation also looks at what AI changes, what it doesn't, and why understanding people is becoming even more important as building software gets easier. Dave breaks down: → Why faster development doesn't always lead to better products → The tradeoff between building for today's customers and tomorrow's customers → How AI is changing product teams without replacing product thinking → Why legacy software is becoming harder to compete with → Where roadmaps still matter, and where they don't → Why understanding people is still the biggest competitive advantage Follow Dave: LinkedIn: https://www.linkedin.com/in/davehannum Follow Marco Benitez and Jonas Dücker LinkedIn Marco: https://www.linkedin.com/in/marcobzg/ LinkedIn Jonas: https://www.linkedin.com/in/jonas-ducker-37460bb3/ Get in touch with This Feature Will Save Us Podcast LinkedIn: https://www.linkedin.com/showcase/this-feature-will-save-us Website: https://thisfeaturewillsaveus.com/ Powered by ROOK: https://www.tryrook.io/ 0:21 – From product roadmaps to vibe coding: how AI is changing the way products get built 4:25 – If coding isn't the moat anymore, what is? 8:50 – Rebuilding Functional Solutions with modern AI tools 9:03 – Functional Solutions and the early days of connected fitness 11:31 – The SMS feature that kept members engaged beyond the gym 14:03 – Why building for your biggest customer can derail your roadmap 15:39 – Feature bloat doesn't disappear. It just happens faster. 17:46 – Product failure, iteration, and rewriting the rules of development 20:45 – Why building software is getting easier, but building a business isn't 25:30 – Generalists, specialists, and the future of product teams 30:30 – Legacy software, acquisitions, and what big companies can't move fast enough to do 40:45 – Why understanding people is still the real moat 42:41 – Rapid-fire questions

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Brian Shoemaker - What Life Time's 190 Clubs Taught Him About Killing Features

Brian Shoemaker started as a developer before he ever had a product title, and ten years later he's running Life Time Labs and the company's new Innovation Hub. His background shows up in how he talks about product decisions: less about the pitch, more about what survives contact with 190 clubs and real staff on the floor. It also means he's got a running list of the ones that didn't make it, and a few that got shelved only to come back around years later once the technology caught up. He joins Marco and Jonas to talk through the Apple Watch feature that took eighteen months to kill, and what Life Time is trying next. Brian breaks down: → Why LT Connect's Apple Watch integration made sense on paper and fell apart in practice → Building live streaming across 40 Life Time locations in a month during COVID, and why it later scaled back down → How the Labs team decides whether a pilot is ready to scale past a few clubs → Why a failed facilities-intelligence pilot from years ago is worth revisiting now → How the Labs team stays small by borrowing people from other teams for a few months at a time → What the Innovation Hub does with 190 startup applications and a 20,000-member beta pool → Where agentic coding tools are becoming a multiplier, and the new bottleneck that creates → What changes for Life Time once iOS 27 opens Siri up to booking classes directly Follow Brian: LinkedIn: https://www.linkedin.com/in/brianshoemaker/ Life Time: https://www.lifetime.life/ Follow Marco Benitez and Jonas Dücker LinkedIn Marco: https://www.linkedin.com/in/marcobzg/ LinkedIn Jonas: https://www.linkedin.com/in/jonas-ducker-37460bb3/ Get in touch with This Feature Will Save Us Podcast LinkedIn: https://www.linkedin.com/showcase/this-feature-will-save-us Website: https://thisfeaturewillsaveus.com/ Powered by ROOK: https://www.tryrook.io/ 0:00 - Welcome and rapid fire questions with Brian 3:20 - Brian's path from developer to leading Life Time's Labs team 4:10 - Cardio, strength training, and the shift toward hybrid fitness 6:00 - Favorite AI tools for research, coding, and legal drafting 9:00 - The most underrated metric in product: L28 10:40 - A pilot that looked great in one club but never scaled 12:20 - Face recognition check-in, and why it never stuck 14:00 - Reviving a failed vibration-sensor pilot as a facilities intelligence platform 17:30 - When cost actually enters the product decision 19:20 - How big the Labs team is, and borrowing talent 21:00 - Life Time's squad structure and two-week sprints 22:40 - Launching the Innovation Hub and rehydrating the old beta program 25:30 - How 190 startup applications get vetted 29:40 - Agentic coding as a multiplier, and the new bottleneck it creates 32:30 - Structuring a day around constant stakeholder input 34:20 - Building live streaming across 40 clubs in a month during COVID 37:00 - Why live streaming scaled down once the world reopened 38:40 - LT Connect and the Apple Watch integration Brian was sure would work 41:30 - What's next: Siri, iOS 27, and whether the app is still the product

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Ernst de Neef - Why Funxtion Walked Away From Its Own AI Workout Builder

Ernst de Neef, CEO and co-founder of Funxtion, joins Marco and Jonas to talk about building digital products for large fitness operators. After more than a decade in the industry, Ernst has seen what happens when customers want flexibility, product teams want simplicity, and the roadmap is expected to somehow make both sides happy. They get into APIs, SDKs, enterprise sales cycles, customization, and an AI workout feature Funxtion spent a long time building before asking a harder question: even if the technology works, can you trust what it gives the user? There is also the familiar question underneath all of it: when a big customer asks for something, is it a useful signal or just a very expensive distraction? Ernst gets into: → Why poor prioritization can cost more than poor execution → The customer request that moved Funxtion from hardware toward APIs and SDKs → Why the fitness industry resisted digital products while the existing club model was still working → What makes enterprise fitness sales cycles take so long → How Funxtion connects engagement to member lifetime value → Why large customers often ask for customization they may later regret → How to say no to a feature request without shutting down the customer relationship → Why Funxtion stopped building a fully generative AI workout builder → Where AI can help personalize fitness programs without creating unpredictable outcomes Follow Ernst de Neef: LinkedIn: https://www.linkedin.com/in/ernst-de-neef-312a251/ Funxtion: https://www.funxtion.com LinkedIn: https://www.linkedin.com/company/funxtion-international/ Follow Marco Benitez and Jonas Dücker LinkedIn Marco: https://www.linkedin.com/in/marcobzg/ LinkedIn Jonas: https://www.linkedin.com/in/jonas-ducker-37460bb3/ Get in touch with This Feature Will Save Us Podcast LinkedIn: https://www.linkedin.com/showcase/this-feature-will-save-us Website: https://thisfeaturewillsaveus.com/ Powered by ROOK: https://www.tryrook.io/ 0:00 - Welcome and quick questions with Ernst 4:38 - Why bad prioritization costs more than bad execution 6:06 - Ernst’s background and what Funxtion builds 8:15 - What hyper-personalization means in fitness today 11:02 - What fitness products can learn from social media engagement 13:15 - Using data and connected platforms to make recommendations more relevant 14:31 - Why the fitness industry fell behind on digital experiences 17:04 - The customer request that moved Funxtion toward APIs and SDKs 19:00 - The reality of selling embedded software to large fitness operators 20:53 - Starting with lifetime value and working backward to engagement 24:20 - How much enterprise customization is too much 28:12 - Keeping the company vision steady while customers and investors ask for changes 32:41 - How to say no to a customer and still help them 33:00 - Why Funxtion stopped building its AI workout generator 35:30 - The next attempt at making personalized fitness programs work 37:06 - Why progress in fitness technology depends on companies working together

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Gabriela Cordero - When the Roadmap Came With Inventory

Some product bets fail because the idea was wrong. Some get a lot messier because the world around it changed. Gabriela Cordero joins Marco and Jonas to talk about building health and fitness products where that kind of thing happens. One launch had the product, the inventory, and the plan. Then COVID hit, gyms closed, and the team had to work through what happens when a hardware product is ready, but there’s nowhere for the inventory to go. That leads into a bigger conversation about hardware and software product work. Software can move fast, at least in theory. Hardware asks for more commitment. Sensors, manufacturing, inventory, timelines, and physical design all make the product calls feel a little less reversible. Gabriela also talks about what she’s building now at MedWatch Technologies: a needle-free glucose wearable. She gets into the process behind bringing that kind of product to market, from the science behind the signal and the hardware constraints to validation, FDA positioning, and how glucose data becomes useful beyond traditional disease management. Gabriela breaks down: → What happens when a hardware product launches into conditions no one planned for → Why hardware product decisions are harder to unwind than software decisions → How customer research and market feedback shape product roadmaps → Why AI changes parts of software development faster than hardware development → Why product teams need to separate a good idea from the right feature to build now → How acquisition dynamics can create product conflict inside larger companies → What she learned from helping bring Nix Biosensors’ hydration wearable to market → Why form factor matters more as wearables move into more personal health use cases Follow Gabriela: LinkedIn: https://www.linkedin.com/in/gabriela-cordero1 Follow Marco Benitez and Jonas Dücker LinkedIn Marco: https://www.linkedin.com/in/marcobzg/ LinkedIn Jonas: https://www.linkedin.com/in/jonas-ducker-37460bb3/ Get in touch with This Feature Will Save Us Podcast LinkedIn: https://www.linkedin.com/showcase/this-feature-will-save-us Website: https://thisfeaturewillsaveus.com/ Powered by ROOK: https://www.tryrook.io/ 1:50 - Hardware, software, and why Gabriela likes B2B2C 5:40 - The highs and lows of building hardware products 6:20 - Launching fitness equipment during COVID 11:10 - Hardware vs software product cycles 12:50 - Where AI helps, and where hardware is still very hands-on 14:20 - Sensor miniaturization and the future of wearable form factors 15:20 - What MedWatch Technologies is building 17:10 - The needle-free wearable Gabriela’s team is developing 20:40 - Chasing the founder vision when the product has never existed before 21:45 - Clinical trials, scientific validation, and building from data 24:45 - Managing product, commercial, marketing, and brand work in an early-stage startup 26:30 - How Gabriela thinks about roadmap tradeoffs 27:20 - What happens when leadership wants a feature the market may not need 30:45 - The product Gabriela is proud of helping bring to market 36:10 - The feature that will save us: glucose visibility 37:00 - Connecting glucose data to food, movement, sleep, and behavior 38:20 - Where to find Gabriela and MedWatch Technologies

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Nolan Parker - The Product Leader Who Still Coaches CrossFit

Nolan Parker’s product perspective was shaped long before he had a product title. As a former gym owner, CrossFit coach, and trainer, he understands the day-to-day reality of the people using fitness software: busy operators, time-strapped coaches, overwhelmed staff, and members who do not care how complicated the system is behind the scenes. Now, as a product leader at PushPress, he is building for those same workflows from the inside. This episode is about the calls product teams actually have to make: when to trust customer feedback, when to challenge it, when to say no to a “good” feature, and how to keep a platform from becoming a bloated collection of edge cases. Nolan also brings his experience from ROOK into the conversation, where he worked with digital health companies using wearable data as product infrastructure. That background opens up a deeper discussion on data, behavior change, onboarding, AI, and what it takes to build tools that are not just technically useful, but actually usable in the field. Nolan breaks down: → Why being both the builder and the user can create better product instincts, but also stronger bias → How coaching taught him to simplify product experiences and avoid overloading users → The TrueCoach app rebuild that taught him the cost of adding too much information → Why SaaS products become bloated when every customer request turns into a feature → How he thinks about market parity, differentiation, world-class features, and “filler” → Why product teams need analytics to understand whether users actually love a feature → How Dashboard 2.0 showed him the difference between user resistance and product failure → Why adoption is often harder than building the product itself → How PushPress is thinking about AI, member intelligence, and surfacing the right context at the right time → Why pricing recommendation tools can be useful in theory but difficult to make work at scale → How gym owner benchmarking, AI assistants, and gamified performance loops could change fitness business software → Why internal trust matters before hard product tradeoff conversations happen Follow Nolan: LinkedIn: https://www.linkedin.com/in/nolan-parker Follow Marco Benitez and Jonas Dücker LinkedIn Marco: https://www.linkedin.com/in/marcobzg/ LinkedIn Jonas: https://www.linkedin.com/in/jonas-ducker-37460bb3/ Get in touch with This Feature Will Save Us Podcast LinkedIn: https://www.linkedin.com/showcase/this-feature-will-save-us Website: https://thisfeaturewillsaveus.com/ Powered by ROOK: https://www.tryrook.io/ 1:45 - Nolan’s most useful AI workflow 2:06 - Why product teams may over-index on NPS 2:49 - Garmin, Whoop, Polar, and Nolan’s wearable preferences 3:15 - Acquisition, retention, and the first habit moment 4:05 - Nolan’s underrated recovery habit 5:25 - Nolan’s role at PushPress and his coach/operator background 6:41 - From dietetics and gym ownership into tech and product 8:00 - ROOK, behavior change, and why information is no longer the main problem 8:51 - The advantage and bias of being both builder and user 9:21 - “Don’t make me think” as a product principle 11:26 - The TrueCoach app rebuild and the danger of too much information 13:48 - How product bloat happens in gym management software 15:40 - Market parity, differentiation, world-class features, and filler 17:00 - Using product analytics to decide what deserves to stay 18:17 - Dashboard 2.0 and why users resist better products 20:01 - Why adoption is often harder than building 20:58 - Meeting users where they are instead of being louder 21:45 - Member Intel and giving coaches the right context before class 23:53 - Turning scattered coach knowledge into usable product context 25:41 - Managing noise from CEOs, clients, tech teams, and the roadmap 28:00 - Building in public vs. using a smaller beta group 29:25 - A feature Nolan expected to work better than it did 31:20 - Gym benchmarking, pricing data, and business insights for operators 32:14 - AI assistants, gym leaderboards, and gamifying operator performance 33:31 - Where internal product friction really comes from 34:25 - Why relationship-building has to happen before hard product decisions 36:16 - Building trust and alignment on remote teams

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When the Workaround Is the Product | Alex Peacock

Alex from Leisure Labs joins Marco and Jonas for the first episode of This Feature Will Save Us. They talk about a feature from the Netpulse days called X-Capture, which let gym members take a photo of a cardio machine console and log the workout from the image. At the time, it solved a messy problem: fitness operators wanted connected equipment, but connecting every machine directly was a headache. The conversation moves into the stuff product teams usually have to sort through before a feature ever ships: timing, simplicity, internal alignment, and the difference between something that demos well and something that actually holds up. They also get into the 2021 omnichannel rush in fitness, AI prototyping, vibe coding, and why Alex thinks hyper-personalization at scale is the next real shift for fitness and wellness products. Alex breaks down: → Why X-Capture worked as a simple workaround for a complicated integration problem → How product teams decide between building, buying, or connecting multiple tools → Why company vision problems usually become roadmap problems → What the fitness industry got wrong about omnichannel during COVID → Where AI helps product teams move faster, and where it still gets risky → Why vibe-coded prototypes are useful, but not the same as production-ready products → Alex’s take on hyper-personalization at scale Follow Alex: LinkedIn: https://www.linkedin.com/in/alexpeacock/ Website: https://www.leisurelabs.co.uk/ Follow Marco Benitez and Jonas Dücker LinkedIn Marco: https://www.linkedin.com/in/marcobzg/ LinkedIn Jonas: https://www.linkedin.com/in/jonas-ducker-37460bb3/ Get in touch with This Feature Will Save Us Podcast LinkedIn: https://www.linkedin.com/showcase/this-feature-will-save-us Website: https://thisfeaturewillsaveus.com/ Powered by ROOK: https://www.tryrook.io/ 0:00 - Welcome and quick questions with Alex 3:35 - Alex’s background building 50+ products over 15 years 4:40 - X-Capture and the feature that made gym equipment data easier 7:40 - When product confusion is really company confusion 9:50 - Why Leisure Labs started Connect 13:40 - How AI is changing the buy vs build decision 18:20 - Why teams need agreement on the outcome before they build 21:45 - The “this feature will save us” trap in fitness 22:15 - The 2021 omnichannel rush and why gyms tried to become digital companies 25:20 - Stable vision, flexible roadmap and changing sprint priorities 30:40 - How AI helps teams prototype before they overbuild 35:20 - Why vibe coding is useful until the product has to survive production 37:00 - Hyper-personalization at scale as the next real product shift 38:30 - Where to find Alex and Leisure Labs

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Trailer: This Feature Will Save Us

Every product team has that moment. Someone pitches a feature and says, "This is the one." Sometimes they're right. Sometimes they are very wrong. Marco Benitez and Jonas Dücker talk to the people actually building products in health, fitness, and wearable tech. The ones making hard calls with messy data, shifting priorities, and stakeholder pressure that never really lets up. They get into why decisions made sense at the time, and what changed once they had to hold up in the real world. Follow This Feature Will Save Us for new episodes every other week. Hosted by Marco Benitez and Jonas Dücker. Powered by ROOK: https://www.tryrook.io