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I lead product and transformation programs - using AI-native strategy and modern…
Articles by Sam
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Is AI the New Microwave
Is AI the New Microwave
In 1969, Amana (the company that brought the first affordable microwave into American kitchens) called it "the greatest…
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Experience and the AI Adoption Gap
Experience and the AI Adoption Gap
If you've been on LinkedIn this week, your feed is probably full of a red and blue radar chart showing the gap between…
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Sam Love posted thisToday is my last day at Quantium (for the second time). I want to thank Adam Driussi and Greg Schneider for having me back and for creating an environment that is truly all-in on AI. My first chapter was Quantium Telstra, working with Sandy Cameron, James Roberts and others on how to detect and prevent scams at scale. It is rare in a career to work on a problem that genuinely matters, with the backing of organisations like CBA and Telstra behind you. The passion and commitment the CBA and Telstra teams showed to scam prevention is something that will stay with me. That work won an AFR AI Award and has prevented millions in scam and fraud losses for Australians. A great example of how AI can be used for good. My second chapter was Quantium itself, working on a different kind of problem. How can we enable executives to go from AI aware to AI effective? Working alongside the Accelerator platform team on that question has sharpened how I think about what it takes to make AI work in the messy reality of organisations figuring it out in real time. It has also sharpened a pattern that I have been noticing my entire career: there is a widening gap between leaders who have personally worked with AI on real problems and those who are still relying on briefings, vendor demos and strategy decks. It's not a gap in intelligence or commitment; it's a gap in reference points, and it compounds. Every decision made without them makes the next one harder, and more expensive. That has always been true of technology transformations, but AI is accelerating it like never before. That challenge turned out to be the one I most wanted to keep working on. Going forward, I will be working with senior leaders and leadership teams who are either just starting to navigate AI or who are ready to accelerate. No training programmes or strategy documents - just calibrated, experience-built judgement that lets you set the right direction. If that resonates (or if you are just curious) I would love to hear from you.
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Sam Love shared thisA friend of mine recently suggested that AI might be the new microwave - in that it is useful for specific things, but not a replacement for the oven. The analogy holds in more ways than one - but is most telling where it breaks. Full article below. 👇
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Sam Love posted thisSomeone recently told me they were holding back on AI because it might turn out to be "the new microwave." I confess I did not immediately understand what he meant. He explained that when the microwave launched, people thought it would replace the oven. Cookbooks were published with recipes for roasting whole chickens, microwaving Thanksgiving turkeys, and flaming brandy for boeuf bourguignon. Fair to say that the microwave did not replace the oven - but it did find its niche. His view is that AI might go the same way. He runs a successful business, has ChatGPT on his phone, and has tried it enough times to form a view. It is a reasonable position. Separately, I've been seeing people who use AI every day switch platforms and discover that a writing style that felt natural in one tool comes out generic in another. The instinct is to conclude the new tool is worse, when what has actually happened is that familiarity was doing more of the work than you'd expect. Two different people, at different levels of AI adoption, arriving at the same place: a confident view of AI, shaped by experience that is narrower than it seems. I see this a lot (including in myself). Most of the time you do not see the gap until something forces a comparison, whether that is trying a new tool, talking to someone using AI differently, or working on a problem you assumed AI could not help with (until it did). Microwaves still can't cook a decent steak - but they still found their way into most kitchens.
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Sam Love shared thisLast week Anthropic published data showing a 5:1 gap between what AI can do in management roles and what's actually being used. In the same fortnight, a US attorney went viral describing how AI lets his two-person firm compete at 100x its size, and HBR published research on the emotional barriers holding senior leaders back. The three sources point to the same gap. Most leaders have heard what AI is capable of, but without hands-on experience, that knowledge creates urgency without direction. The leaders who have used AI on real problems are making more grounded decisions, because they have reference points that only come from use. I wrote about it in my first article 👇
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Sam Love reposted thisSam Love reposted thisIn a few years, product managers probably won't exist... ...nor will software engineers, UX designers or other product functions. A single person will replace the entire product team. This may sound radical, but this is how we used to build software products. In the 90s, Chris Sawyer made one of the best-selling PC games of the decade, outselling everything on the market despite releasing partway through the year. He wrote in assembly language. No frameworks, no libraries, no teammates. He held the entire product in his mind and built it fast. He called working alone a superpower: "I could get ideas...working really quickly - no issues...having to explain or justify ideas to anyone else." The game was RollerCoaster Tycoon. But this wasn't unique. Tetris, SimCity and even entire operating systems like Linux and even the World Wide Web were all first shipped by soloists. Then codebases outgrew what one person could handle. So we hired specialists. Specialists created handoffs, handoffs created miscommunication, so we hired coordinators. Every fix required another hire. Before long, shipping a feature needed ten people and a Jira board. Once you go down this path, it's almost impossible to reverse. The only way back is if the dynamics change enough that one person can do what a whole team did, better. This is starting to happen. Claude Code and Cursor aren't assistants anymore. They augment your mind with the entire product, codebase and problem space. But who directs the AI? I've started calling them a Product Architect. Why not "AI builder"? AI is a tool, not an identity. You don't call a surgeon a "scalpel cutter." And "builder" describes someone who puts pieces together. You don't hire a bricklayer for a skyscraper, you hire an architect. AI builds. The product architect thinks, decides and directs. They replace a cross-functional team with a single visionary executor. One mind holding strategy, experience and insights, eliminating every handoff and miscommunication. They're generalists, but go deep along one of three axes: 1. Systems: How services and infrastructure work together. Keeping the codebase performant and maintainable but with customers needs firmly in their mind. 2. Experience: Keeping products coherent, useable and elegant. Building entire features end-to-end where experience is the crux. 3. Insight: Knowing users like no one else. Experimenting daily, shipping fast, killing what doesn't work, accelerated by reusability from of the experience and systems product architects. Today's engineers become systems-focused product architects. Designers become experience-focused. PMs, researchers and data scientists become insight-focused. But all ship end to end. Sam Altman has a betting pool with his CEO friends for when one person builds a billion dollar company. That might be a way off. But the one person product team? Probably a lot sooner. What do you think the next generation product organisation looks like?
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Sam Love posted this"I'm not technical enough." This is what a consultant I work with said when I suggested she could build an AI solution herself. She's wrong. What she's good at (asking the right questions, breaking problems down, understanding what the user needs) is what effective AI design requires. The approach I'd taken to solve the same problem was mostly design thinking: using AI to research best practice, defining the standard, then iterating on the output until it met it. There was nothing here that she couldn't do. Too many organisations frame AI as a technology problem. That framing tells capable professionals it's not their work, and they believe it. Your best AI contributors might not be who you think. They might be opting out.
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Sam Love posted thisA common pattern that I see in organisations is technically excellent work that doesn't connect to a business decision. The team delivered exactly what was asked for. It was on time, within scope and analytically sound. The problem is that what was asked for wasn't what was needed. The analysis answered the agreed question - but not the question the business actually had. As a young analyst, I delivered a technically perfect piece of work. The trouble was that it didn't help anyone make a decision. My big shift was learning to orient to the decision behind the deliverable, not the deliverable itself. Same data, dramatically different value. By reframing from "what have we been asked to do?" to "what decision does this need to inform?", the difference is between work that sits in a drawer and work that moves something forward. This was one of the ideas I unpacked at #womenintechfest this week, talking to a room of women in tech about the non-technical skills that change everything.
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Sam Love posted thisA client once told me to always remember the bigger Russian doll. It took me years to understand what he meant. Early in my career, I excelled at the innermost layer: the deliverable, the timeline, the technically correct answer. Not the business outcome it served. Not the relationships it depended on. Not the motivations that would determine whether anyone acted on it. The skill that changed my career wasn't technical. It was learning to zoom out before diving in. That skill matters now more than ever. A lot of how we think about AI in business is on the inner layers. I'm finding it increasingly valuable at the outer ones - surfacing context I haven't considered, challenging whether I'm solving the right problem and helping me see the 'why' behind the 'what'. But only because the judgment is there first. Without it, you don't even know what to ask. I'm unpacking this at #womenintechfest next Wednesday. Come say hi!
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Sam Love posted thisI used the phrase "think big, test small" (borrowed from a post by Thomas Gläser 🚀) twice last week with two different teams. It landed both times, and I've been thinking about why it resonates so much. Working with AI right now involves a double uncertainty. The technology is shifting constantly, and we're still discovering what users and businesses actually need. You can't plan through it. You have to learn through it. For the teams I was working with, that meant focusing on what we could learn this week - about our users and the technology - and letting that shape what we build next. How does this apply to senior leaders earlier in their AI journey? The most useful version of "test small" might be the simplest. Use the tools yourself on a real problem - personal or professional - and start to build a feel for what AI can and can't (yet) do. We've learned that action follows strategy. AI is inverting this for senior leaders and product teams alike.
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One thing that worked well in a team I worked with was building learning outcomes into sprint wrap-ups. Alongside what shipped, each team shared what they learned and (importantly) what they were changing as a result. Without that structure, the learning conversation never happens. "Ship to learn" quietly becomes "ship to say we shipped."
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Sam Love liked thisStartups will help shape the future of healthcare, but not alone Loved being back at Start it Accelerate | @KBC, always impressed by the energy, quality, and drive of the ecosystem! It was a great moment to step out of the daily grind… to listen, connect, and reflect A few reflections that stuck with me: > The rate of change in healthcare is accelerating, across technology, legislation, and generational expectations > Startups will play a vital role in navigating this, bringing speed, focus, and fresh thinking > In healthcare, no startup can do it alone Real impact comes from ecosystems. Start it is a core pillar — alongside organisations like Biovia , VLAIO - Flanders Innovation & Entrepreneurship , FIT - Flanders Investment & Trade, lifetech.brussels, Health Hub Aalst, KBC Bank & Verzekering, PMV, Love Tomorrow and many others helping to make innovation real. Excited to see what this next wave builds!!!Sam Love liked thisThe past 72 hours we opened our doors to 270 startups. It was a privilege to host: 160 startups for Start it @KBC with the support of KBC Bank & Verzekering 34 startups for Start it @CBC with the support of Wallonie Entreprendre & CBC Banque & Assurance 18 startups for Start it Fashion with the support of Stad Antwerpen 28 startups for Start it Hardware with the support of Leuven MindGate 30 scaleups for Scale it Agro with the support of KBC Bank & Verzekering Boerenbond Arvesta AIF Cera Coop To the founders: Thank you and well done. Your grit, your passion, and that energy are exactly why we do what we do. To my team: Thank you for the early mornings, late nights and the relentless focus. Evaluating such a high volume of talent in a short window and organising this practically is a monumental task. Your dedication to a qualitative, thorough, fair process is what makes our ecosystem, not only the biggest in Europe, but also world-class. These past weeks have been very intense. Andy Gijbels, PhDAnn Martens, Bastien Van Wylick, Christophe Cieters, Dirk Lievens, Donat Pajer, Francesca Nista, Harold Roquet, Inge Wouters, Liesbeth Van der Jonckheyd, Lucas Tamboryn, Ludo Dhelft, Mieke Daniels, Nadia Van der Velden, @peggy, Pieter V., Raf Seymus, Sophie Verhulst, Stefanie Windels, Maxim Leirman, Tara Reid, Kjell Clarysse The wait is almost over. We will be announcing our newest cohort later today!
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Sam Love liked thisSam Love liked thisThere’s something energising about stepping into a space where the future of your industry is being shaped in real time ✨ Intertraffic Amsterdam delivered exactly that. From the moment I walked the halls, it was clear that road safety and infrastructure are entering a new era, one driven by sustainability, smarter materials, and integrated technology. What stood out most wasn’t just the innovation itself, but the intent behind it. A clear shift toward: • Safer outcomes for workers and road users 🦺 • Longer-lasting, lower-maintenance solutions ♻️ • Materials and systems that reduce environmental impact 🌱 • Data and intelligence playing a bigger role in how roads perform over time 📊 It reinforced something I’ve been deeply focused on, that the next generation of road marking isn’t just about visibility, it’s about performance, durability, and responsibility. I had some incredible conversations with global leaders, challengers, and innovators, the kind that spark ideas you carry long after you’ve left the room 💡 I’m currently travelling through Europe, spending time with our supply partners going deeper into the chemistry, the manufacturing, and the thinking behind the next generation of materials. I’m feeling inspired, slightly exhausted, and very clear on where the momentum is going. The line is being raised and I’m here for it 🚀 #RoadSafety #Infrastructure #LineMarking #RoadMarking #SustainableInfrastructure #Innovation #SmartMaterials #FutureOfTransport #IndustryLeadership #SaferRoads Rayolite Australia Pty Ltd #RaisingTheLine
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Sam Love liked thisSam Love liked this🔥 Ich freue mich sehr über die erneute #Wahl in den Vorstand des Bitkom - AK FinTechs & Digital Banking 🔥. Der #Finanzstandort Deutschland steht mehr denn je an einem entscheidenden Punkt. Die nächsten Jahre entscheiden darüber, ob wir europäische Wertschöpfung und Innovation (weiter) entwickeln und „selbst haben“. Was wir brauchen, ist keine platte Diskussion zu „mehr“ oder „weniger Regulierung“. Regulierung ist gut und wichtig, muss aber klug, passgenau und proportional und insbesondere auch ➡️technologieoffen, und ➡️innovationsfreundlich ausgestaltet sein. In dem neu gewählten #Vorstand bringen wir wichtige Perspektiven und Erfahrungen zusammen: Banken, FinTechs, Tech-Unternehmen und neue Player entlang der gesamten Wertschöpfungskette. Unser gemeinsames Ziel ist es, den Finanzstandort Deutschland 🇩🇪 und Europa 🇪🇺aktiv mitzugestalten und zu verbessern. Themenschwerpunkte werden sein: ➡️AI, ➡️Open Finance, ➡️digitale Identitäten, ➡️Cloud im Finanzsektor oder ➡️Zukunft der privaten Altersvorsorge. Ich freue mich sehr auf die nächste Legislaturperiode und besonders auf die (weitere) Zusammenarbeit mit Sascha Dewald ,Dr. Verena Thaler, Delia D. König, Christoph Kuban und Dr. Florian Lörsch sowie mit Alina Stephanie Bone-Winkel und Tim Haremsa vom Bitkom - let’s go 🔥!
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Sam Love liked thisSam Love liked thisWe say we have to ship fast to learn. But most teams aren’t learning after they ship. Yes we've increased our shipping velocity. We've removed the friction to generate ideas, vibe code prototypes, and push things out into the world, but our speed of learning has not kept pace. Most teams still do not have a shared view of what must be true before they ship. There is still no clear definition of what success looks like, and still no time for the teams to stop and ask if what they shipped actually worked afterwards. But there are always more things to ship. The Build Measure Learn loop turned back into the Build Build Build loop all over again, now even faster because of AI. It's almost as if we didn't actually fix the feature factory issue, instead we scaled it with AI and in doing so are compounding risk instead of reducing it. As leaders you need to get ahead of this before it gets out of control. If you actually want teams to ship to learn, learning has to show up in how decisions get made. Your teams need to see it and hear it from you. It has to show up in what gets funded, what continues, and what stops. Otherwise AI just helps you ship faster in all directions, all at once. And that's not speed... that's drift.
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Sam Love liked thisSam Love liked thisJust published in Nature! I’m pleased to share that a new paper I co‑authored with dozens of esteemed colleagues worldwide who are all smarter than me has been published in Nature, part of the Nature Portfolio. The project—one of the largest analytical‑robustness initiatives ever conducted in the social and behavioural sciences—examined a simple but consequential question: How much do research findings depend on the analyst rather than the data? Using 100 previously published studies, independent teams re‑analysed the same datasets to test the robustness of the original conclusions. The results highlight a structural vulnerability in empirical research: - Only 34% of reanalyses reproduced the original effect size within a narrow tolerance. - With a broader tolerance, similarity rose to 57%. - Yet 74% of teams still reached the same overall conclusion. - 24% found no effect or inconclusive results. - 2% found the opposite effect. The implication is clear: analytic choices introduce far more variability than most researchers assume, and single‑path analyses should not be treated as inherently robust. The paper calls for stronger norms around transparency, multi‑analyst pipelines, and explicit communication of analytic uncertainty—practices that will strengthen the credibility of social‑science evidence going forward. For those interested, the article is available here: https://lnkd.in/ehYuyPuRInvestigating the analytical robustness of the social and behavioural sciences - NatureInvestigating the analytical robustness of the social and behavioural sciences - Nature
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Sam Love liked thisSam Love liked thisReally interesting perspective from Kera on how Swiss Re is using AI in underwriting today—not as a replacement, but as "augmented underwriting". It’s all about combining technology with human judgment to make smarter, more informed decisions. --- Swiss Re’s Group Chief Underwriting Officer, Kera McDonald, shares how AI is helping to strengthen underwriting without replacing human judgment. In an interview with Insurance Business, she explains that AI at Swiss Re is increasingly being used to improve how underwriters access data, identify trends, and gain earlier visibility into emerging risks. “Taking risk is our job. AI helps us understand that risk better and faster, but it does not make decisions for us.” Kera draws a firm line around decision-making authority. AI supports underwriting decisions, but it does not replace them. “We talk about ‘augmented underwriting.’ The human remains in the loop, especially given the nuance and complexity of reinsurance.” Read the entire interview to find out more: https://ow.ly/1F3w30sUkNt
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Sam Love liked thisgreat role, with a great leader at coal face of Enterprise AI 🚀Sam Love liked thisHands down, one of the most exciting finance roles going right now — working where finance meets AI. A rare opportunity to both partner closely with our AI division and leverage AI to drive transformation in finance. Find out first hand, what it means to be a Finance professional in an AI- first world.
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Sam Love liked thisSam Love liked thisOur team is growing! We're on the hunt for a TA Specialist to join the P&C team hiring for roles in Australia. We're looking for someone who is relationship driven with a background in internal recruitment (bonus points for tech / SaaS). If you love end-to-end recruiting, have an interest in contributing to broader P&C initiatives and want to do it somewhere people genuinely love coming to work, this could be the role for you! In return, you'll get to work alongside a fab P&C team, a culture that is collaborative and supportive and get access to some pretty nice perks. DM me directly if you want to chat!
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Georgie Smallwood
Georgie Smallwood
I scale and transform international businesses at the moments that determine whether growth becomes durable or fragile.<br><br>My career has been built inside hyper-growth environments across Europe, Australia and Asia. I scaled N26 across 22 markets (EU+US) as CPO from 800k to 6m+ customers, helped build TIER Mobility into a global leader in shared micro-mobility across more than 520+ cities and now lead Product, Data and Technology at Moonpig Group plc, the UK’s best-known online gifting and greeting card platform, through the scrutiny of public markets.<br><br>I’ve led through IPO preparation, funding rounds, international expansion and organisational resets, not from the sidelines but from inside the operating model. The common thread has been simple: take something promising and turn it into something structurally resilient, commercially disciplined and built to scale.<br><br>While my background is rooted in Product and Technology, my roles have required full enterprise accountability, from Customer Support to Marketing. I’ve aligned product strategy, commercial performance, cost base and leadership structure so that scale translates into long-term value, not just short-term momentum.<br><br>I’ve rebuilt leadership teams, redesigned operating models, clarified decision rights and introduced the financial and performance discipline that international growth demands. I’m comfortable making hard calls when the organisation that got you here will not get you there. The work is rarely cosmetic; it is structural.<br><br>I believe durable growth comes from aligning deep customer obsession with financial discipline. The best consumer companies are emotionally resonant and operationally rigorous in equal measure. Neither works without the other.<br><br>Alongside my executive career, I founded Auxilia out of a direct frustration with the funding gap facing diverse entrepreneurs. It is a network for current and future female founders built on the belief that the best ideas come from the broadest representation of people. I invest through Accel’s Starter Program with a specific focus on female founders and serve as a board director and advisor where the brief is the same as in my executive work: strategic clarity and operational realism in equal measure.<br><br>I’m most effective where ambition and discipline must coexist and where leadership clarity determines outcome.
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