Platform Engineering Insights

I strongly believe that technology can drive processes in a way that builds and strengthens trust between clients & vendors. Tech platform services have made processes in project procurement faster, data-driven, and transparent. Tasks like vendor scouting, assessments, and comparisons that once took weeks can now be done in days. Trust is built when decisions are backed by data and transparency—stakeholders understand why a vendor was chosen. Responsiveness is equally critical; when clients promptly address vendor queries, it fosters confidence on both sides. I remember we worked with a client struggling to find the right vendor for a specialized CapEx project. Through Venwiz, they: - Identified pre-verified vendors in a flash. - Assessed vendor capabilities with over 20+ custom data points. - Used the platform to share updates and ensure alignment with vendors. The result? A faster, more objective, and transparent process that strengthened trust on both sides. For me, the intersection of technology and trust makes decisions more objective and better informed. But these are my experiences, would love to hear your thoughts/additions. #Procurement #CapEx #Trust #Technology

The New Culture of Influence Power no longer moves top-down from institutions—it now flows outward from communities, creators, and digital networks. Gen Z places 5× more trust in peers and influencers than older generations. They look sideways, not upwards, for authority. • Identity has gone global: Gen Z and Millennials form global communities through platforms like TikTok, Discord, and Twitch. Geography matters less; shared values matter more. A climate activist in California connects more deeply with another in Seoul than their local politician. The internet has united young people across borders and reshaped identity into something global and collaborative. • Culture wars vs. creative renaissance: The narrative of polarization and culture wars misses the creativity rising from the chaos. Young generations use memes as political statements and remix traditional arts using AI. Nearly half of Gen Z already uses AI daily—not just for work but for music, art, and culture. Their nuanced stance—both excited and wary—will define how we balance innovation and integrity. • Platform power: loyalty earned, not demanded: Tech giants no longer monopolize culture. Young users instantly abandon platforms that violate trust or lose relevance, shifting influence quickly. Loyalty today is continuously earned, creating opportunities for new, more responsive players. Influence is increasingly open-source—a teen with a phone can launch a movement forcing a corporate or governmental response overnight. America’s next chapter belongs to a politically disillusioned yet socially empowered generation. They’re redefining trust, loyalty, and power. The center of gravity has shifted, and the new influential voices are grassroots, digital-first, and global in outlook. Smart founders, policymakers, artists, and strategists must engage these emerging networks and values directly. Bold ideas now spread bottom-up—and that’s exactly where the future of culture and innovation lies.

𝗪𝗵𝗮𝘁 𝗽𝗶𝘇𝘇𝗮 𝗮𝗻𝗱 𝗰𝗵𝗲𝗲𝘀𝗲 𝘁𝗲𝗮𝗰𝗵 𝘂𝘀 𝗮𝗯𝗼𝘂𝘁 𝗱𝗮𝘁𝗮 𝗾𝘂𝗮𝗹𝗶𝘁𝘆: LLM providers have been training their models on public data, for example from Twitter and Reddit, leading to concerns over the contents they’ve learned from. So, they have been striking licensing deals with content providers to get access to their data — and that creates new challenges. Datasets obtained from the public Internet contain false information, sarcasm, and potentially harmful content. Given that Generative AI, unlike humans, has no understanding of common sense and nuance, this can backfire quickly. An AI-augmented Google search has recently recommended: adding non-toxic glue to your pizza to prevent the cheese from sliding off. (Don’t try this at home.) The Internet has traced the information back to a decade-old thread on Reddit that the model has presumably processed and incorporated into its AI-generated output. Think about autonomous agents that will book your travel, negotiate a contract with your supplier, or provide information about your products, parts, and warranties. Mishaps for any of these examples due to bad data can have a real impact on your business — from ending up in the wrong location at the wrong time to overpaying, causing damage to your customers’ assets, and more. Spending extra effort to review, clean, and correct your datasets remains key. So does attributing generated information to the exact source document or dataset. That way, your users have a reference point to verify if the generated output is actually correct. Otherwise, you might end up with the equivalent business outcome of suggesting to add glue to prevent cheese from sliding off of your pizza. A sticky situation. Read the article 👇🏻 for the full details and get the next one in your inbox tomorrow. 𝗜𝘀 𝘁𝗵𝗲 𝗼𝗹𝗱 𝘀𝗮𝘆𝗶𝗻𝗴 𝗲𝘃𝗲𝗿 𝗺𝗼𝗿𝗲 𝗿𝗲𝗹𝗲𝘃𝗮𝗻𝘁? —> “𝘋𝘰𝘯’𝘵 𝘵𝘳𝘶𝘴𝘵 𝘦𝘷𝘦𝘳𝘺𝘵𝘩𝘪𝘯𝘨 𝘺𝘰𝘶 𝘳𝘦𝘢𝘥 𝘰𝘯 𝘵𝘩𝘦 𝘐𝘯𝘵𝘦𝘳𝘯𝘦𝘵.” #ArtificialIntelligence #GenerativeAI #IntelligenceBriefing

💣 In for a contrarian view: "#Insurtechs fail at scaling #microinsurance" That’s according to research by Yannick Perticone and Jean-Christophe Graz, recently published in Cambridge University Press. The authors argue that Insurtech’s promises fall short of expectations because of the contradiction between the principles of platform scalability and insurance risk pooling. ___ Here's what the authors argue in this paper: Insurance is based on pooling risks, whereas insurtech platforms are often premised on unpooling risks. These two opposing forces create a challenging case for insurtech as a viable enabler for microinsurance. The study highlights three key dimensions of digital insurance that, while central to insurtech platforms, may also hinder their success: 🔗 Interoperability Insurtechs rely on data from other parties, such as MNOs. Due to data protection regulations and practices, the data they receive is often limited, which could result in mispricing of insurance solutions. 💴Valuation Platform owners collect data for specific purposes, which may not be sufficient for accurate risk pricing in insurance. This mismatch between the data needed for risk assessment and what is actually available may lead to incorrect pricing and, ultimately, incorrect premiums. ⚛️ Aggregation Insurtechs atomise risk pools, breaking them into smaller segments to facilitate precise risk profiling. However, this reduces the pool size, undermining the fundamental principle of insurance as a solidarity risk-sharing mechanism, which may lead to higher, not lower prices. According to the authors, these three challenges make insurtechs an unlikely solution for the growth of inclusive or microinsurance. _____ ⁉️ Do you agree? This is certainly one of the more thought-provoking views I’ve shared here. While I may not fully align with the author’s conclusions, I believe it raises important points worth discussing. I’m eager to hear your thoughts and learn from your perspectives. 𝘛𝘩𝘦 𝘩𝘪𝘨𝘩𝘭𝘪𝘨𝘩𝘵𝘴 𝘪𝘯 𝘵𝘩𝘦 𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘱𝘢𝘱𝘦𝘳 𝘢𝘳𝘦 𝘮𝘪𝘯𝘦. 𝘈 𝘭𝘪𝘯𝘬 𝘵𝘰 𝘵𝘩𝘦 𝘴𝘰𝘶𝘳𝘤𝘦 𝘪𝘴 𝘪𝘯 𝘵𝘩𝘦 𝘤𝘰𝘮𝘮𝘦𝘯𝘵𝘴. ━━━━━━━━━━━━━━━ 🤝 Hi, I'm Bert. I'm passionate about staying up-to-date with the latest in #microinsurance. I'd be delighted to connect and exchange insights with you. 🚀 With the annual Microinsurance Master Master accelerator program, we are on a mission to help organisations thrive. Join us in March 2025 to make a difference in the business of reducing the risks of low-income communities. ⠀

This is your casual reminder: don't fall for the CDP trap or hype. Why a Customer or Business Data Platform may not be the solution you need: 1. 🎯 CDPs are not the single source of truth. They add yet another data consumer layer to your overall data infrastructure, complicating it further. Eventually, you may compromise the quality of your data (resulting in poor marketing campaign performance) or triple the total cost of ownership. 2. 🔄 Mapping users across all sources is tricky. No CDP offers a magic solution to resolve customer identities and create a unified 360-degree customer view unless you already have it. 3. 🚩 CDPs introduce different versions of the same entities and metrics. A CDP will create its own definitions of DAU or Churn, which you might not be able to replicate in other applications. Yay to 5 more LTV variations! 4. 💰 CDPs are expensive. Apart from (a) the cost of the CDP itself, (b) dedicating engineering and analytical resources to its setup and maintenance, and (c) the cost of ETLs to ingest the data into the CDP, you will also have to double the storage cost because data must be replicated to the CDP. 5. 🧯CDPs require resources to maintain. CDPs promise fast ROI and self-service, but the reality is quite different. Maintaining a data layer that can ingest data at scale from any source and ensure it is clean and accurate requires everything from data engineering and analytics - APIs, SDKs, pipelines, monitoring, governance, and Q&A. Additionally, analysts should not lose flexibility and ownership of the data reporting ecosystem, regardless of which CDP you adopt. https://lnkd.in/gyvnHJaQ

I'm incredibly excited to finally share publicly the output of months of hard work from our entire team at Patch. We’ve been thinking deeply about what it will really take to unlock the potential of the voluntary carbon market. We know that there are billions of dollars on the sidelines, and when we talk to carbon credit buyers, we’re hearing the same three challenges: 1. Fragmentation in the market is making it way too difficult to find the right credits at a fair price. Fundamentally, this is fragmentation of data: how many credits are available for a project? What are the overall pricing trends among all suppliers of that credit or type? 2. And then there’s the fragmentation of MRV data, project data, integrity data, ratings data, etc. This makes it incredibly expensive to diligence any single project — let alone a portfolio — in a reasonable period of time. The stakes are high. Funding the wrong project can damage your sustainability program. Taking too long means you can miss out on fast-moving inventory. 3. Lastly, the entire buyer journey is profoundly inefficient. Sourcing, diligence, procurement — these are resource-intensive workflows, heavily reliant on expertise and collaboration among internal and external parties. They don’t just incrementally increase the costs of a carbon program — they can fundamentally break it. This is what our customers are telling us — Workday, Autodesk, Bain & Company, Capgemini, Deutsche Telekom, and many more. That’s why I’m so proud to launch our all-new end-to-end carbon credit platform — we’re helping them solve these big challenges. From strategy to sourcing to diligence to purchase to management, Patch brings in comprehensive data, human expertise, and AI-powered software at every key decision point and workflow of your carbon program. I wrote a blog taking you behind the new platform and explaining our choices. Link is in the comments below.

As #datacenters scale rapidly to support #AI, cloud computing, and other digital services, much has been written about whether existing grids can meet the surge in electricity demand—and whether emissions will spike, since most grids remain carbon intensive. This outlook - focusing on the risks and challenges of data center growth - misses the transformative role that data centers and technology companies could play in accelerating national and regional energy, climate, and sustainable development goals. In our new blog, Perrine Toledano, Bradford M. Willis and I explain how #hyperscalers can help resolve the very constraints that are slowing the energy transition and undermining broader climate and development goals. Specifically, hyperscalers can uniquely: 🔹 reduce investment risks and marginal costs for new clean grid infrastructure, as large, predictable off-takers 🔹 create financeable demand for large-scale energy storage. Storage integration - which strengthens grid reliability and resilience - has been hard to finance because of uncertain revenue streams. 🔹 expand access to water and thermal systems through shared-use infrastructure platforms, learning from successful models in other sectors like mining 🔹 deploy rapidly-evolving AI and digital tools to increase energy efficiency, manage energy demand, streamline interconnection, lower system costs, and optimize maintenance, among other evolving functions, and 🔹 expand access to broadband and digital services, closing the persistent digital divide, and bringing transformative benefits in health, education, agriculture, and financial inclusion to underserved communities. These benefits are happening already in ad hoc ways - but could be massively scaled when embedded in strategic policy frameworks and coordinated with public and private partners. 🔗 https://lnkd.in/ea6vMMaG Side note: our current focus on carbon footprinting has distracted from—rather than supported—tech firms’ transformative potential. While footprinting can provide a useful snapshot of emissions/exposure/influence, our over-emphasis on emissions reporting has crowded out any discussion of strategic systemic integration and even creates perverse incentives. The over-reliance on footprinting as the key metric has also very predictably led to myriad illegitimate practices, including 'offsetting' emissions with unbundled RECs or dubious carbon credits, and other accounting loopholes (see yet another timely, insightful article from Simon Mundy on big tech's climate claims: https://lnkd.in/eNvtGxGu). Let's shift the focus to encouraging tech firms to engage in strategic public/private cooperation in grid design and expansion, financing solutions, and expanded digital inclusion -- optimizing transformative digital innovations for societal and planetary benefit.

One insurance gap almost wiped 40% off this insurtech's valuation overnight. Here's how we helped their CFO… The call I got from their CFO was one we get multiple times a year. They now needed deeper expertise. Like many funded startups… They put a basic insurance program in place during their friends & family round. Box ticked. Rolled it through their Series A. Three years later: In the market for a new capital raise. A matured digital I platform serving thousands of customers, and partnerships with several sizeable banks. But their insurance program was still stuck in 2021. Their risk management framework and insurance coverage were speaking different languages. And one insurance savvy investor flagged a gap during due diligence that left a major exposure unchecked. From a 30k view… Here's the insurance framework we helped them design to protect their Series B valuation: 1. Cyber Insurance → ransomware/extortion limits → tech platform interruption calc 2. Technology E&O → software failure coverage → customer data handling errors 3. D&O for Tech Companies → IPO/funding round protection → regulatory tech compliance 4. Coverage Adequacy → tech platform exposure limits → API/integration gap analysis 5. Regulatory Tech Insurance → fintech compliance coverage → digital insurance regs 6. Cost Optimization → insurtech market benchmarking → startup growth scaling costs 7. Data Liability → AI/ML decision coverage → data privacy protection 8. Policy Terms for Tech → API failure exclusions → cloud service interruption 9. Property Insurance → server/hardware protection → remote workforce coverage 10. Risk Management Services → cybersecurity programs → tech incident response 11. Emerging Tech Risks → blockchain exposure → AI liability assessment 12. Coverage Integration → legacy vs digital coverage → partner API protection 13. Claims Process → digital claims handling → real-time reporting systems 14. Policy Documentation → digital certificate system → API-based policy mgmt 15. Market Conditions → insurtech capacity limits → digital insurance trends 16. Regulatory Compliance → fintech licensing reqs → digital compliance reporting 17. Risk Transfer Alternatives → parametric solutions → micro-insurance platforms 18. Coverage Triggers → digital incident definition → automated notice systems 19. Insurance Program Structure → tech platform coverage → startup scaling structure 20. Specialized Tech Needs → open banking exposure → digital payment protection 21-25 Cont in comments… P.S. if you like this post you’ll love our newsletter. Every Friday we flag the top three articles impacting the global insurance markets. It’s for busy executives that want to stay current on the market…

Three Norwegian founders moved into a grandmother's 160-year-old house in Stavanger in 2022. When they tried to fix a simple heat pump, the installation process was so painfully slow that they decided to build the platform they wished existed. Two years later, they're powering renewable energy deployment across Europe and setting their sights on the US's $257B opportunity. The Company: Installer.com. An infrastructure platform for renewable energy deployment - connecting manufacturers, installers, and customers in one system. Founders: Gunnar Windsand Sem, Kristoffer Gjerde, Thomas Kristiansen – together they combine renewable energy consulting, AI strategy, supply chain optimization, and hands-on installer experience. The Problem They're Solving: The energy transition is hitting a critical bottleneck. It's not the hardware anymore - it's the complete absence of scalable, digital infrastructure to manage deployment efficiently. Installer.com provides the enabling infrastructure, much like Shopify did for e-commerce. Unlike service aggregators, which require companies to outsource control, Installer.com’s platform empowers businesses to own their installation process and customer experience. Traction: Customer base manages hundreds of thousands of installations annually across 18 European markets. Now executing US market entry with early climate tech traction. Funding: $4.8M total ($4M seed led by Brighteye Ventures, with Futurum Ventures, Sondo, PT1, Startuplab) US Market Opportunity: US EV charging market alone projected at $257B by 2032 and heating, batteries and solar are booming too. The primary barrier isn't hardware—it's scalable installation infrastructure. This is a future they have already navigated. The Nordics lead the world in renewable technology adoption, from EV penetration to heat pumps. They have built and hardened their platform in these highly advanced markets, solving the exact fragmentation, labor shortage, and customer experience challenges that the US is now facing at an unprecedented scale US Entry Strategy: Establish high-profile US customers with the current $4M runway. Series A planned for 2026 with US expansion focus. Going to Houston Energy and Climate Startup Week! Who They Want to Talk To: ·    VCs with portfolio companies requiring product installation ·    ClimateTech advisors (solar, EV charging, batteries, heating) ·    Renewable asset companies (residential/commercial) Want to chat with the team? Let me know or just reach out to the directly. ---------------------------------------------------------------------------- I'm launching a weekly series highlighting Nordic companies that are planning to enter the US market, or are already making waves there. As someone with one foot in each of these ecosystems, strengthening this bridge has become a mission of mine, so I want to connect the great companies I work with everyday with my network back home. Interested in leaning in, just let me know!

Most people think trust is lost in big, dramatic failures. It’s not. It often dies in small, seemingly insignificant moments, aka "micro-infractions". These are the tiny lapses that signal to customers: 💡 "Maybe they’re not as reliable as I thought." 💡 "Maybe I need to start double-checking everything they say." 💡 "Maybe I should loop in someone higher up.” By the time it’s obvious, it’s too late. Here are four micro-infractions that quietly break customer trust (and how to spot them before they do real damage): 🔥 Missed or Delayed Follow-Ups ❌ You promised to follow up by Friday. It’s Monday, and you finally send a rushed update. 👉 Warning Sign: The customer starts sending “Just following up” emails—or stops trusting your timelines altogether. 🔥 Inconsistent Messaging ❌ One person says a feature is coming soon. Another says it’s not on the roadmap. 👉 Warning Sign: Customers double-check information, reference old emails, or ask, “Wait, which is it?” 🔥 Ignoring or Deflecting Concerns ❌ Customer raises a problem. The response? “That’s great feedback! Let me tell you about our latest update…” (without addressing the issue). 👉 Warning Sign: The customer repeats their concern. Or worse, they escalate. 🔥 Lack of Proactive Updates ❌ A delay happens. But instead of keeping the customer informed, you wait until they ask. 👉 Warning Sign: Customers start repeating, “Can you keep me posted?” Translation: They don’t trust you to follow through. Trust is built in the details. Customers don’t always call these things out—but they notice. And when they do, you’re one step closer to losing them. Seen these in action? Drop your thoughts below. 👇