Oskar Bruening

Stategraph just shipped a feature called multi-state transactions. You know what that does? It removes the need for things like terragrunt run-all, output mocking, and hand-rolled orchestration. When you fix the substrate, everything downstream changes. Never bet against the collective. #terraform

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Over the past few weeks, I’ve started sharing more about Exa Labs and today we’ve published a deeper look into what we’re building. It's no secret that the world is becoming increasingly AI-native. Capabilities are advancing fast but adoption remains deeply uneven globally. Emerging markets hold much of the raw opportunity, yet sit far from the frontier in data, compute, and deployment. Without a different approach, today’s readiness gap becomes a lasting outcome. Exa Labs is our response. We’re building across infrastructure, intelligence, and applications, a full stack designed to answer one question: "How do we accelerate the adoption and impact of frontier technology in emerging markets?"

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New blog post on tech debt. tl;dr; Tech debt is nuanced, its not always a problem, but it can become the sludge in the engine that slows you down. Having a tech debt strategy in place is important. https://lnkd.in/ghSdEXF6

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Proud to share this milestone for Surge, a Public Benefit Corporation. Yesterday, we announced a new partnership with BLUE-BAND LLC focused on building real-time, resilient AI data systems capable of supporting the complexity of autonomous systems, mobility platforms, and emerging AI applications in the real world. By combining Surge’s intelligent data infrastructure with Blue-Band’s edge intelligence capabilities, we’re laying the groundwork for scalable systems that communities and partners can rely on—not just today, but for the long term. Grateful to Kevin Yorke and the Blue-Band team for the shared vision and execution mindset. Excited for what we’re building together. Full press release: https://lnkd.in/gg5Jkvpx #Surge #AI #DataInfrastructure #EdgeAI #BlueBand #Partnership #PublicBenefitCorporation brandon richman | Kevin Yorke | Stephanie Hoback | William McGuire | John Cowan | James Thomason

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AI commoditizes automation and intelligence, which means that saas companies (which historically either automate stuff or present stuff as 'insights' on 'dashboards') will face an insane amount of competition and thus their racketeering adjescent seat based pricing will crumble. that said I tend to see a lot of ecom bro's or PE saas guys on linkedin with hot takes that are like 'nah uh, have you tried it, its too hard'. and I think thats also right! but I think its only right for a short period of time. the chart below focuses largely on enterprise, where the legacy saas companies' tam is big enough to warrant a legit effort by a new entrant, and more likely, the in house tech teams are strong (or egotistical) enough to try to bring it in house. the ecom guys and the PE guys tend to focus on the long tail and on blue collar businesses.... operators that are, mostly, too dumb, too ideological, or too busy to try to vibe code something. so yeah, *today*, I think its more likely that some of the thousands of developers at capital one bring a saas tool's functionality in house or that a team in india copy/pastes it for 1/20th the cost than I think that a dude with a room temp iq selling white label Chinese slop on Shopify is going to vibe code a new sms delivery tool. but thats today. tomorrow is coming fast.

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Today, we're announcing our $125M Series A led by Lightspeed with participation from Greylock Partners, Unusual Ventures, Artisanal Ventures, and A*. This round values Resolve AI at $1B. I've spent two decades building production systems and observability tools. In that time, I've learned that operating software is where most engineering time goes: 3AM pages, the cost optimizations to hit margin goals, the laborious compliance questionnaires. Production is the hardest part of software engineering, and every engineer I talk to has lived this story. AI is helping us write more code than ever, but that code still has to be deployed, monitored, and debugged in production. We're scaling code generation exponentially without scaling our ability to operate it. This is the gap Resolve AI closes. We're building AI for prod: agents that work across code, infrastructure, telemetry, and knowledge. Agents that bring together the expertise of multiple teams in every execution, absorbing context and learning continuously. Our goal is to help every engineer operate production fluently. Seeing the impact that customers like DoorDash, Zscaler, and Coinbase achieve with Resolve makes this work worth it. I'm incredibly proud of the team we've assembled to do it. Read my full announcement, linked in the comments

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Sola raised $17.5 million in early funding to enhance its enterprise process automation platform. The Series A funding round was led by Kimberly Tan and Jennifer Li at Andreessen Horowitz, bringing the company's total funding to $21 million. Sola Solutions provides AI agents that automate workflows using a no-code, visual approach, allowing business users to build, edit, and maintain processes easily. Co-founder and CEO Jessica Wu said the technology enables companies to automate tasks like shipment updates and billing processes without needing developers. Read more: https://lnkd.in/e7uqcvh7 📰 Subscribe to the weekly AI Funding News Newsletter: https://lnkd.in/enH99b34 #ai #artificialintelligence #ainews #aifunding

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Here’s why Claude’s recent progress has unlocked the next leap forward for Canvas Medical. Claude’s tools, combined with our Deep Unified Architecture and SDK, are enabling new use cases for automation while simultaneously making us exponentially faster in shipping customer specific enhancements. It's a double win. Said another way, Canvas is an EMR built to provide context and tools for automation. And now we can enable AI driven development for any user or customer, whether technical or non technical, to build their own custom workflows in Canvas. Just in the past couple of days our team has shipped: For Brigade Health - a customized panel management dashboard for high-risk patients For Vida Health - ability to parse unstructured lab results from a fax into the chart as structured clinical data For Radial - improvements to the provider onboarding experience to accelerate the rapid scaling of their medical group operations For Doctronic - in-workflow evals for clinicians to submit structured feedback on the performance of their AI-driven note generation The best part? All of this work was done without software engineers 🤯 We used the Canvas Plugin Assistant, powered by Claude Code and the Canvas SDK. We’re living in the future. Here’s a graphic from Anthropic’s presentation yesterday with a couple of annotations to explain. Sometimes a picture is worth a few hundred words.

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🚨 NEW BLOG ALERT 🚨 Scaling shouldn't mean a "rip and replace" or a "hiring tax." The Legacy Bridge layers AiVA onto existing tech for intelligent voice automation. This captures missed opportunities and scales operations without adding headcount. It makes your current systems work harder via an AI Voice Agent. How do you balance legacy stability with the need for modern automation? #ZentricAi #AiVA #WorkflowAutomation #BusinessScaling #IntelligentAutomation https://lnkd.in/gMNys5em

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What if the real opportunity isn’t in existing demand, but in creating it? Sometimes the market only becomes obvious after someone builds for it. At Peak XV & Surge Immersion, Vanta Co-founder & CEO Christina Cacioppo spoke with Rajan Anandan about building in a space where startup demand for SOC 2 compliance was practically non-existent. Vanta realized compliance was broken: the process was slow, complex, and expensive. Addressing these thoughtfully helped create a new market. And in the early days, the company didn’t even have a website. Much of the growth came through word of mouth as they scaled. Here's a short sneak peek from the session. We'll be sharing the talks soon.

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new summation pod with Thumbtack CEO Marco Zappacosta on the nearly trillion-dollar home services market, why software stopped being a capital asset, and the rise of the generalist. https://lnkd.in/e-sRz85f

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Why Draper Startup House Ventures invested in Taubyte Ai workloads are concentrating compute, cloud, and control plane power into fewer hands. Most cloud platforms introduce structural dependency at the infrastructure layer. Taubyte is rebuilding the cloud stack differently with Git-native deployment, content-addressed releases, and distributed execution across infrastructure you control. At the network layer, services communicate peer-to-peer via libp2p, eliminating central coordinators and creating a mesh that auto-discovers, self-heals, and scales horizontally without bottlenecks. Free from hyperscaler control planes and single points of failure. Infrastructure may be the real Ai arms race. Learn more 👉 taubyte.com Giulianna Crivello Nick Martin

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Inertia is the commercial fusion energy company, and today we're taking a big step forward with $450M in funding! With support from Bessemer Venture Partners GV (Google Ventures), Modern Capital, Threshold Ventures, Neo, Uncork Capital, Long Journey, and WndrCo we're taking proven physics from the lab to build the industrial foundation for gigawatt-scale fusion power plants. The road to get here involved $30 billion in government funding for inertial confinement fusion experiments, the groundbreaking demonstrations of fusion that works at the National Ignition Facility at Lawrence Livermore National Laboratory, the incredible ingenuity of my co-founders Andrea (Annie) Kritcher and Mike Dunne, and the team of DO-ers we’re building at Inertia. Now, with our funding, we're going to: 🔆 Build and scale the production of the world's most powerful laser  🔆 Build the world's first fusion fuel factory to mass produce fusion targets 🔆 Design and build the first gigawatt, utility-scale fusion energy power plant We're bringing star power to Earth. Read the founders' letter: https://inertia.com/news/ Read the press release: https://lnkd.in/gVEEYEpv And come build with us: https://inertia.com/jobs

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The bottleneck in AI-assisted development isn’t code anymore. It’s the decisions upstream of it. Boris nails what’s actually breaking, and what Catio is building to fix it.

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Breaking: Composite Raises $5.6M to Make Browser Automation Accessible to All Professionals Exciting news in the AI productivity space! Composite just secured $5.6M in seed funding to build a cross-browser AI agent that automates tedious browser-based tasks for professionals. Unlike browser-specific AI tools, Composite works across any browser you prefer. Why this matters: Most professionals spend hours on repetitive browser tasks - from recruiters screening candidates to security engineers managing vulnerabilities. Composite's solution lets non-technical users automate these workflows without switching browsers or writing code. The most impressive part? The tool learns from your patterns and can handle complex multi-step tasks across different websites where you're already logged in. This could be a game-changer for enterprise productivity. What are your thoughts on AI automation tools? Would you trust an AI assistant to handle your routine browser tasks? Read more: https://lnkd.in/guQyyByJ #ArtificialIntelligence #ProductivityTools #WorkplaceAutomation #TechStartups #AIFunding #FutureOfWork #EnterpriseAI #BrowserTechnology

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I'm calling it now. One of the biggest shifts coming in H1 2026 will be huge numbers of engineering teams being pushed, top-down, to become fully AI-native. Gaming, of all industries, is moving among the fastest here. Maybe it's not a surprise. Gaming is one of the industries that's relentlessly productivity-oriented when it comes to thinking about software engineering outcomes and headcount. But there are good and bad ways to shift to AI native.... and some really terrible ones. In the "hamfisted approach to AI native" category, KRAFTON Inc. who asked employees to voluntarily quit their jobs if they couldn't go “AI-first”. I get the massive pressure to drive AI, but asking folks to quit might be the worst way to get buy-in on transformational technology. It skips the part that actually makes AI-native engineering succeed in organizations and jumps to the threats. The way to think about this is like the shift from waterfall to agile: it requires tools, training, and frequent measurable wins, over IC pressure. If it were one of our customers at CoreStory, the playbook for this transition would go more like this: 1. Set up the AI-native process Install the machinery. It's not enough to give someone Copilot and call it a day. Most teams need the stack: coding agents, specification agents, context agents for existing codebases, workflows into JIRA/ADO and VCS, and measurement tools to see ROI metrics around productivity. AI-native development is a process change, not a headcount change. 2. Drive buy-in from individual engineers rack up their own wins. Engineers don’t need to be convinced by threats. Almost every engineer I talk to is extremely excited by AI, acutely aware of the limitations on real codebases, and looking for answers and org backing on how to drive the shift into their day-to-day. They mostly just need space and guidance to make the adoption happen. 3. Prove big wins early. Once the system is in place, engineers should be able to use AI to ship the features they care about faster and cleaner than ever, which leads to measurable boosts in the productivity of the overall team (measured in sprint velocity gains). Individual engineers can move to a "demo, don't memo" format. There's not much that's more motivating and fun than seeing weeks or months of work compressed into days on real features. We’ve been through this kind of transition before. The move from waterfall to agile took a decade, and companies that figured it out first dominated their markets. As usual, the firms that get this transition right will dramatically expand their engineering leverage. The ones that get it wrong will resort to blunt measures and lose people they should have empowered. https://lnkd.in/ggfpEVfi #AI #Engineering #GameDev #AINative #SoftwareDevelopment

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ICYMI, here's what Scott Sanchez said about margins in the LLM market on our inaugural podcast last week. Recording again this week but here's the link to E1: https://lnkd.in/gie2Quu8

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I had the pleasure of speaking with Steve Divitkos for the latest episode of his podcast In The Trenches. We had a deep-dive conversation about the most important things that searchers, investors, and other members of the ETA community should be thinking about when it comes to assessing the technical debt of target companies. Helping searchers and their investors understand the implications of technical debt for growth plans and working with them to develop go-forward strategies for tackling technical debt and putting the right technologies, processes, and people in place is one of the most rewarding aspects of the work I do in my role at Spellbound Partners. It was great to be able to share my perspective with Steve and to try to shed some light on the practical ways that technical debt can shape acquisition decisions and business operations:

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