Technology Integration in Strategy

“Loop engineering” is a hot buzzphrase after mentions of it by Boris Cherny (Claude Code’s creator) and Peter Steinberger (OpenClaw's creator) went viral on social media. Loops are now a key part of how we get AI agents to iterate at length to build software. In this letter, I’d like to share my 3 key loops, shown in the image below, for building 0-to-1 products. These loops guide not just how I build software, but also how I decide what software to build. Agentic coding loop: Given a product specification and optionally a set of evals (that is, a dataset against which to measure performance), we can have an AI agent write code, test its work, and keep iterating until the code is bug-free and meets its specification. This idea of closing the loop took off around the end of last year, and it has been a game changer in enabling coding agents to work longer productively without human intervention. For example, over the weekend, I was building an app for my daughter to practice typing, and my coding agent could easily work for around an hour, using a web browser to check what it had built multiple times before getting back to me, without needing my intervention. The engineering loop executes quickly. Every few minutes, the coding agent might build and test a new version of the software. I hear frequently from developers who are finding new ways to engineer more effective engineering loops. This is an active area of invention! Developer feedback loop: In this loop, a developer examines the current product and steers the coding agent to improve it. Last year, a lot of developers (including me) were acting as the QA (quality assurance) function for our coding agents, manually finding bugs and then asking the agent to fix them. But with coding agents much more able to test their own code, the amount of time we need to spend on this function has decreased significantly. This allows us to make higher-level product decisions, such as what key features to offer, where the UI needs improvement, and so on. The developer-feedback loop operates over time intervals between tens of minutes and hours — that's how frequently a developer might review a product and give feedback. In the case of the typing app, I changed my mind a few times about the visual design, what cat costumes she can unlock as she learns (she loves cats), and the user flow for a grown-up to log in and steer the child's learning experience. When a developer has a clear vision for what to build, it is still a lot of work to translate that vision into a specification for a coding agent to implement. Further, after the developer has seen an implementation, they might update (or perhaps clarify) the spec to steer it toward what they want. If you find that the system repeatedly runs into certain problems, building a set of evals for the agent becomes useful. [Truncated for length. Full text: https://lnkd.in/gKDQ6H9s]

Turning Europe into a quantum industrial powerhouse Europe has been the cradle of quantum mechanics, the revolutionary science born from the genius of Max Planck, Albert Einstein, Niels Bohr, Erwin Schrödinger, and other visionaries who rewrote the rules of physical reality. On 2 July 2025, in the year marking a centenary since the initial development of quantum mechanics, the Commission has adopted an ambitious European Quantum Strategy, integrating Europe's unique scientific heritage with its vibrant quantum ecosystem of startups, SMEs, large industries, research and technology organisations, academia and research institutes. The mission is clear: turn Europe into a quantum industrial powerhouse that transforms breakthrough science into market-ready applications, while maintaining its scientific leadership. We are imagining a Union where medical scans can detect illnesses at the earliest stages, accelerating from weeks of uncertainty to mere seconds of precise diagnosis; where sensors are able to warn about volcanic activity or water shortages before they happen; and where unprecedented computational power will be available to solve complex problems in logistics, finance and climate modelling. A safer Europe, where our personal data, critical infrastructure, and businesses will always remain private and well-protected; where transport systems are optimised to reduce congestion and prevent accidents; and air travel is guided by quantum-enhanced precision navigation, pinpointing objects' locations down to the centimetre. A greener Europe, where sustainable energy grids can flawlessly manage millions of electric vehicles charging simultaneously overnight. These tangible, transformative technologies are within reach through support from the EU Quantum Strategy. The quantum community has clearly outlined what's needed to achieve this future: · Combine Europe's scientific excellence to bring quantum breakthroughs rapidly to market · Develop advanced quantum supercomputers like the ones we are supporting under the Quantum Flagship and are acquiring under the EuroHPC Joint Undertaking to operate as accelerators next to our leading network of supercomputers · Deploy secure communication networks such as those under EuroQCI, our secure quantum communication infrastructure that will be spanning the whole EU, composed of a terrestrial segment relying on fibre communications networks linking strategic sites at national and cross-border level, and a space segment based on satellites · Support quantum startups and SMEs, enhancing supply chain resilience, and foster supranational innovation clusters · Integrate quantum advancements into strategic capabilities for security and defence, protecting citizens and infrastructure · Educate Europe's workforce through specialised initiatives like the European Quantum Skills Academy Quantum is not one more technology to add to the list; is a high tide that will deeply transform our society and economy.

Breaking Quantum News: Real algorithms, real data, real quantum machines HSBC, in partnership with IBM, has delivered the world’s first quantum-enabled algorithmic trading trial. Using live, production-scale data from the European corporate bond market, HSBC integrated IBM’s quantum processors with classical systems—achieving up to a 34% improvement in predicting the probability of winning trades compared with classical methods alone. Why it matters: - Bond trading is one of the most complex, data-heavy challenges in finance. - Classical models struggle to capture hidden pricing signals in noisy markets. - By augmenting workflows with IBM Quantum Heron, HSBC uncovered insights classical systems could not. As Philip Intallura Ph.D, HSBC’s Global Head of Quantum Technologies, put it: “This is a tangible example of how today’s quantum computers could solve a real-world business problem at scale and offer a competitive edge.” And as IBM’s Jay Gambetta emphasized: breakthroughs come from combining deep financial expertise with cutting-edge quantum algorithms—demonstrating what becomes possible as quantum advances. This is not hype. It’s not distant. Quantum is entering the market—today. #QuantumComputing #Finance #Innovation #PQC #QuantumReady

"Unfortunately, most current counter-drone systems look like someone strapped $500,000 worth of sensors to a laser pointer and hoped for the best. Enter yet another tech marvel from Sweden: the Kreuger 100. A stripped-down, software-driven interceptor that’s less F-35 and more Ikea flat-pack missile. That’s not an insult. That’s the future. Launched by Nordic Air Defense (NAD), a Stockholm startup that clearly got tired of watching Europe buy defense tech from across the Atlantic, the Kreuger 100 was designed from the ground up to be cheap, scalable, and fast to deploy. What sets the Kreuger 100 apart isn’t just what’s inside but what’s missing. In the traditional world of air defense, interceptors come bloated with cost-heavy payloads: radar transceivers, laser rangefinders, gimbaled optics, complex gyroscopic stabilization, and propulsion systems that look like they were ripped from Cold War cruise missiles. The Kreuger 100 throws that model out the window and replaces it with a radical, minimalist architecture where the real brainpower lives not in hardware but in code. At the heart of this interceptor is a machine-learning-based flight control algorithm that adapts to environmental variables in real time: wind, angle of attack, target evasion maneuvers, and even thermal distortion caused by cluttered urban landscapes. Instead of reacting like a heat-seeking missile on rails, the Kreuger 100 behaves more like a predator drone with a nervous system. It doesn’t just follow, it predicts. It calculates an interception course based on probabilistic modeling of the drone’s behavior, a kind of anticipatory flight path generation that gives it a split-second edge in a knife fight in the sky. And unlike traditional systems locked into proprietary software ecosystems, the Kreuger 100 is designed to run on modular, updateable codebases. That means when a new drone threat emerges, say, a smaller, faster loitering munition or a decoy swarm, the Kreuger’s software can be updated without touching the hardware. In war, that adaptability is gold. Its infrared tracking system, while simple by Western standards, is fully integrated into this software layer. Rather than relying on heavy stabilization and high-end optics to isolate a heat signature, the Kreuger uses digital signal processing and software-based noise filtering to lock onto targets even with low contrast or amidst thermal clutter. It’s not the most powerful eye in the sky, but it’s smart enough to see through fog, rain, or smoke and still make the shot. [...] In short, the Kreuger 100 doesn’t match legacy interceptors feature-for-feature. It leapfrogs them by reducing complexity, cutting costs, and moving the brain from silicon to code. The result is a nimble, adaptable air defense solution that behaves more like a swarm AI than a missile." From https://archive.ph/pumek

12 March 2026: Here are the opening paragraphs of an article I co-authored with Isaac F., a very impressive American entrepreneur and software engineer who has spent the past four years helping the Ukrainian military build out its various software battle command platforms: "The era of autonomous warfare will not announce itself with robotic armies marching across battlefields. Instead, it is already emerging, quietly and inexorably, in the skies and fields of eastern Ukraine (and to a lesser degree in the Middle East), where missions are increasingly executed by machines at speeds no human can match and electronic warfare is severing the links between operators and their machines. Very soon, autonomous systems will no longer operate individually; over time, they will form platoon- or even battalion-sized units that share information and coordinate without human intervention. And the side that waits for human approval before acting will lose. This transition demands that militaries rethink not just the nature of command but the fundamental nature of war. The adaptation challenge goes beyond technological and industrial issues, although those aspects are enormously important. Already, Ukrainian engineers are rapidly developing software for autonomous navigation, and Ukrainian military technicians are now assembling first-person-view drones and other types in extraordinary numbers: some 3.5 million last year and a potential seven million this year, compared with 300,000 to 400,000 now assembled annually in the United States. The U.S. military will have to adapt much faster to manufacture drones in the enormous numbers required and to learn to employ autonomous systems effectively. But hardware and software will not be enough. It will be just as critical to develop new concepts and doctrine, adjust organizational structures, and institute the new kinds of military education and training that autonomous warfare will demand. These are all areas in which military institutions are often overly deliberate. But which militaries move first to change how they think about command and how the nature of war is evolving will determine which countries win the wars of the future." #autonomouswarfare #linkedintopvoices https://lnkd.in/em-m9s4j

But what if insurance worked more like Netflix? Netflix tracks your viewing behavior and adapts recommendations instantly. If insurance products adapting the same way, premiums adjusting dynamically to fitness levels, coverage expanding with life stages, benefits rebalancing as goals evolve. McKinsey estimates AI-led personalization could lift insurer revenues by 10–15%, while lowering claims costs through early risk detection. And The technology already exists. Wearables generate 250+ daily data points per user around heart rate, sleep, activity. PwC reports 63% of consumers are willing to share health data if it results in cheaper or more personalized premiums. And Personlaized premiums is not a distant reality. It can be achieved by: 𝟏. 𝐈𝐧𝐭𝐞𝐫𝐨𝐩𝐞𝐫𝐚𝐛𝐥𝐞 𝐝𝐚𝐭𝐚 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 that allow secure ingestion of health and behavioral data at scale. 𝟐. 𝐑𝐞𝐠𝐮𝐥𝐚𝐭𝐨𝐫𝐲 𝐬𝐚𝐧𝐝𝐛𝐨𝐱𝐞𝐬 that encourage innovation while protecting privacy. 𝟑. 𝐀𝐈 𝐞𝐱𝐩𝐥𝐚𝐢𝐧𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬 to ensure transparent pricing and avoid hidden bias. 𝟒. 𝐄𝐜𝐨𝐬𝐲𝐬𝐭𝐞𝐦 𝐩𝐚𝐫𝐭𝐧𝐞𝐫𝐬𝐡𝐢𝐩𝐬 with health-tech, fintech, and wellness players to broaden value delivery. Insurance is likely evolve from a once-in-a-decade purchase to a living product. #DigitalIndia #Fintech #AI #technology #Fintech #AI #technology

"Many militaries are expanding the scope and speed of incorporating more complex data-driven techniques into the processes of determining courses of action, including when it comes to the use of force. These developments raise questions about the changing roles played by humans and machines, or human-machine interaction, in warfare. "This report contributes to ongoing debates on AI DSS by reviewing main developments and discussions surrounding these systems and their reported uses. It takes stock of what is known about AI DSS in military decision-making on the use of force, including in ongoing war zones around the globe. Section 2 provides a brief overview of the roles that AI DSS can play in use-of-force decision-making. Section 3 reviews main developments that we treat as indicative of trends in AI DSS in the military domain." "It focuses on three concrete empirical cases, namely the United States (US)’ Project Maven initiative, as well as systems reportedly used in the Russia-Ukraine war (2022-) and the Israel-Hamas war (2023-). Section 4 discusses opportunities and challenges associated with these developments, drawing inspiration from ongoing debates in the media and expert communities. The report concludes with some recommendations on potential ways forward to address the challenges discussed and with some questions raised by AI DSS that deserve further attention in the global debate on AI in the military domain." From Anna Nadibaidze Dr Ingvild Bode Qiaochu Zhang Center for War Studies, University of Southern Denmark

Yesterday, Russian drones violated NATO airspace over Poland. The most serious incident of its kind since the war in Ukraine began. This stark reminder of today’s rapidly evolving security environment underscores why speed, innovation and adaptation are no longer optional. They are mission critical. On September 10th, #NATO_ACT took a historic step by holding its first-ever Adoption Board, turning innovation from concept to reality. Why an Adoption Board? Innovation isn’t just about having great ideas, it’s about adoption. The journey from concept to operational capability is often a valley of death, where many promising solutions fail to survive. By launching this Adoption Board, ACT is scaling up initial projects in space, IT, and uncrewed vehicles, focusing on customers and integration, ensuring that cutting-edge technologies enter service quickly and effectively. This marks the operationalization of the La Haye Summit pledge on innovation, translating strategic intent into tangible action. What was decided? The Board selected several “beacon projects” for their transformational potential and short-term impact, complementing Allies’ rearmament efforts and accelerating lethality at speed and scale: Counter-UAS solutions Maritime Awareness Multi-Domain Network Space Broad Area Indications and Warnings Baltic USV Task Force X (Phase II) Targeting Network AI in training (scenario generation & red teaming) These projects are grounded in field-proven lessons and built for compatibility with NATO common-funded programs, ensuring rapid scaling and interoperability. The road ahead Yesterday’s incident in Poland highlights the urgency of this mission. In a world where the speed of technology is challenged by the speed of disorder, we need to transform NATO as a "learning" body, moving fast, being agile and paving the way ahead to make 32 Nato Nations be able to fight as one with a tangible fighting edge. Adoption success will come when projects meet the customer giving him "more bang for the buck" and opening the user's case portfolio. #NATO #Innovation #Defense #Security #Transformation #Poland #AI #UncrewedVehicle #CounterUAS #Allies

This image is from an Amazon Braket slide deck that just did the rounds of all the Deep Tech conferences I've been at recently (this one from Eric Kessler). It's more profound than it might seem. As technical leaders, we're constantly evaluating how emerging technologies will reshape our computational strategies. Quantum computing is prominent in these discussions, but clarity on its practical integration is... emerging. It's becoming clear however that the path forward isn't about quantum versus classical, but how quantum and classical work together. This will be a core theme for the year ahead. As someone now on the implementation partner side of this work, and getting the chance to work on specific implementations of quantum-classical hybrid workloads, I think of it this way: Quantum Processing Units (QPUs) are specialised engines capable of tackling calculations that are currently intractable for even the largest supercomputers. That's the "quantum 101" explanation you've heard over and over. However, missing from that usual story, is that they require significant classical infrastructure for: - Control and calibration - Data preparation and readout - Error mitigation and correction frameworks - Executing the parts of algorithms not suited for quantum speedup Therefore, the near-to-medium term future involves integrating QPUs as accelerators within a broader classical computing environment. Much like GPUs accelerate specific AI/graphics tasks alongside CPUs, QPUs are a promising resource to accelerate specific quantum-suited operations within larger applications. What does this mean for technical decision-makers? Focus on Integration: Strategic planning should center on identifying how and where quantum capabilities can be integrated into existing or future HPC workflows, not on replacing them entirely. Identify Target Problems: The key is pinpointing high-value business or research problems where the unique capabilities of quantum computation could provide a substantial advantage. Prepare for Hybrid Architectures: Consider architectures and software platforms designed explicitly to manage these complex hybrid workflows efficiently. PS: Some companies like Quantum Brilliance are focused on this space from the hardware side from the outset, working with Pawsey Supercomputing Research Centre and Oak Ridge National Laboratory. On the software side there's the likes of Q-CTRL, Classiq Technologies, Haiqu and Strangeworks all tackling the challenge of managing actual workloads (with different levels of abstraction). Speaking to these teams will give you a good feel for topic and approaches. Get to it. #QuantumComputing #HybridComputing #HPC

Our new policy paper on European digital sovereignty, for a hard reset. Digital authoritarianism is on the rise. Meanwhile, Europe has become, with some notable exceptions, a digital colony. Technical dependence, in hardware and software, is a dangerous trend for both the European economy and democracy. To counter this, in our view, Europe must assert its digital sovereignty – not in isolation, but on its own terms. Hence “The European Way – A Blueprint for Reclaiming our Digital Future,” written by a strong and heterogeneous group of thinkers and practitioners, led by Kai Zenner and including, e.g., EuroStackers Cristina Caffarra, Sebastiano Toffaletti, AI insiders Dr. Miriam Meckel, Dr. Léa Steinacker, Dr. Till Klein, Dr. Frauke Goll, Björn Ommer, Rasmus Rothe, Joerg Bienert, Sebastian Hallensleben, and many more. Full text: https://lnkd.in/ewQKWmNK To operationalize this vision, we propose 6 interlocking reform packages: 1. Digital Infrastructure & Defence  Launch a European Digital Industrial Strategy that supports cloud, semiconductors, and quantum.  Develop a “EuroStack”—a modular, sovereign European tech stack.  Treat a digital and AI pivot in defence and cybersecurity, with a Digital Defence Fund, as core components of resilience and political autonomy.  Establish a European DARPA, support dual-use technologies, and think digital-first in defence procurement. 2. Digital Single Market & Industrial Policy  Complete the Capital Markets Union to fund digital innovation at scale.  Use public procurement to support European tech companies, via a "Buy European" framework.  Further update competition law to address data asymmetries and promote fair access to platforms.  Strengthen data spaces as a backbone for industrial collaboration. 3. Geopolitical Strategy  Build trusted digital trade partnerships with like-minded allies.  Develop an EU voice in global standard-setting bodies.  Promote tech diplomacy and increase Europe's global regulatory influence. 4. Governance & Institutions  Move toward coherent and principles-based digital regulation that supports innovation and flexibility.  Create a European Digital Enforcement Agency with unified powers for all digital acts, and clear political independence. 5. Energy Supply for the Digital Age  Forge a balanced Energy Mix Deal that supports both green energy and strategic autonomy.  Integrate the European electricity market to ensure stable supply for data centers and critical infrastructure.  Incentivize energy-efficient data infrastructure through regulation and support. 6. Digital Skills, Talent & Education  Launch an EU Tech Talent Initiative to expand training and retraining programs.  Introduce fast-track visas and intra-EU mobility tools to attract digital professionals - with adequate compensation via special funds. IMO, Europe can still lead—but it must act with urgency and vision.