Mike Groseclose

A lot shifted in 2025. AI made some things easier and other things more complicated, and it pushed teams to focus more on resilience. The 2025 State of the Internet Year in Review breaks down what stood out most this year. https://lnkd.in/eh2eZXfA

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Early in my career everything was about building large scale homogeneous systems. What’s been more interesting over the last 5y has been heterogeneous multi cloud systems. The tradeoffs are more complex to build simple (irreducible complexity) and elegant systems in that space.

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Waymo has unlocked a surprisingly specific use case in San Francisco: parents are trusting it to drive their kids to school. They wouldn’t put their kid in an Uber, but they’ll send them solo in a fully autonomous car. That was the moment it really clicked for me. If AI can handle real-time decisions where safety is on the line, it can handle a mortgage file. Document review, condition clearing, data extraction—it’s not even close in terms of complexity. The challenge isn’t whether it’s possible. It’s whether we’re designing systems that make better use of people’s time—because the manual work isn’t just inefficient. It’s holding the entire industry back. https://lnkd.in/gFVA9Yvk #MortgageTech #Automation #AIinLending

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If I worked somewhere where this was even remotely doable, I'd do it. (At a lot of companies, even if you want to publish your review, they don't want it published, citing "privacy laws" or "company policy. I've even been told in the past not to discuss your review with anyone other than your manager, which is a rule that I routinely ignore.) Transparency is vulnerability, and vulnerability is what creates connectedness and/or intimacy (depending on which word creeps you out less) with others. As Jordana points out, it humanizes somebody that would otherwise be a distant inhuman figure.

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We don’t lack clarity — we lack the right lens. This week I’m reframing systems thinking as human logic and showing how structure shapes behavior. https://lnkd.in/gAkmAJFF

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This was a good discussion about the Principal Engineer role at Amazon! I often say that the Principal Engineer role as it exists at Amazon simply doesn't make sense at smaller companies. To many, the title just means the next highest level of engineering skills. At Amazon, it requires dealing with high levels of ambiguity, business strategy, and organizational influence. If you're at a company with <50 people, the person with that level of influence should be leading the whole technical organization - it requires a significant amount of scale before it makes sense to have an IC role for it. I also personally appreciated Steve's points on internal level progression - or as Gergeley says, "Why being promoted from Senior to Principal at Amazon is one of the hardest jumps in tech." Steve: "Basically, to get from senior to principal, you have to do like two and a half level jump, from L6 to L7. Technically, it sounds like one level, but at some other companies, this might be like, you know, L8, L9 or L8 and a half. [...] I noticed that some of the best engineers that I'd ever worked with were having such problems getting to principal engineer that they ended up moving to Facebook or to Meta or to all these other places where the progression was sane. Now they're senior staff and, you know, principal and distinguished engineer at other companies. And so because we had high standards, we actually had this brain drain." In addition to the level itself being a big jump the promotion process is notoriously arduous and arbitrary. While I was L6, I had multiple managers over several years acknowledge that I was doing L7 work, and even agree that if I was being hired in from outside I would be hired at L7, and it was the internal promotion process that was the barrier. This was not the *only* reason I left Amazon, but it certainly made it very easy to do. Amazon has lost a lot of skilled engineers this way, but it's a difficult problem to fix, since the incentives are fundamentally badly aligned. If an L6 engineer is already doing the work that's needed, it's very hard for a manager to justify spending the 100+ hours of work it takes to advocate for their promotion. And while there have been attempts to make the process less arduous, no one wants to be seen as "lowering standards." I highly encourage engineers in that position to make it clear they will not be continuing to do work that way indefinitely. And I encourage leaders at other companies to learn from the example! https://lnkd.in/guC35n2B

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AI feels less like a feature upgrade and more like a productivity shock. The closest comparison I keep coming back to is the Industrial Revolution — chaotic in the moment, transformational in hindsight. It didn’t just cut costs. It made goods abundant. I think AI does the same for services. The real divide won’t be between companies that adopt AI and those that don’t. It’ll be between those who use it to “do the same with less” and those who use it to “do exponentially more with the same.” Efficiency is table stakes. Ambition is the differentiator. I wrote a short piece expanding on this here: https://lnkd.in/gTKGr2Dm Curious where others are landing.

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ACTORS + AI: Director/Actor/Producer/Writer AI Chef 🧑‍🍳 Hans Obma visits the Cozy AI Kitchen 🎂 https://lnkd.in/gjiAvEfP to share his insights on how AI has transformed his creative processes. You may have seen Chef Hans in such 📺 hits as Better Call Saul, Wandavision, or Narcos — and yes, he's probably the most handsome AI 🧑‍🍳 chef we've had in the kitchen to date :-). Hans needed to learn a new language ... how did he do it? He got multimodal AI models to help him speak Welsh. Hans needed a way to scale how he communicated with his stakeholders ... how did he do it? He created an authentic-to-him way of scaling by creating an instant entourage of supporting agents. HT 🧑‍🍳 Ross Heise 🧑‍🍳 Matt Scholz and the power of the Wisconsin network for bringing such a storied talent to the Cozy AI Kitchen! --- This 🍰 episode: https://lnkd.in/gjiAvEfP All 50 episodes: https://lnkd.in/g6upvbGX

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If you are anywhere near Fullerton, California this week, join us for the next "I Build with AI" meetup, where Mark Warrick, AI Strategist and App Developer, will be presenting and running a workshop on how to Turn Your Domain Expertise into a Mobile App with AI! Instead of focusing on code or technical implementation details, the session centers on understanding intent, decision-making, and real-world judgment, and how AI can help translate that thinking into software. To make the concepts concrete, Mark will walk through a real example called Trail Palette, a mobile weather app designed for outdoor photographers. Drawing on his experience spending countless hours in mountainous terrain as both a guide and photographer, Mark brings an intuitive understanding of how weather, light, and landscape interact, and how that domain knowledge shapes the logic and behavior of an app. This session is designed for knowledge workers and domain experts who are non-developers that want a clear mental model of what it takes to build a mobile app using AI. Along with a hands-on workshop, you’ll gain an understanding of the tools involved and inspiration to see how your own domain expertise could become the foundation for software. RSVP for the event at: https://lnkd.in/gCj-GTD5

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I’ve refactored and replatformed multiple times in my career. It’s been tedious and time consuming every time. Well, Cloudflare just replaced next.js with a home brewed vite alternative, for $1,100 in AI tokens. 🤯 https://lnkd.in/g63fgJey

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If you're keen on real AI use cases, this is actually quite powerful and I encourage you to read further (and help us build: https://lnkd.in/gsYnAfKK) At Hex, we've found our Threads product (https://lnkd.in/gJKCurJB) is the best way to summarize customer support load, because we're not limited to what's in the customer support portal - we can ask in terms of active users, customer size, feature adoption, and still get great answers. This is based on a strategy of keeping your data warehouse as a source of truth, and all related data work in one place - Hex - so that AI understands concepts in your business and makes smart connections between things. Arguably, ALL data analysis for a particular vertical is eventually best achieved in a tool like Hex, connected to curated data in your data warehouse. Wait - can't I do this directly in the customer support tool? Can't I connect an MCP server and get a functionality like this in one of my other AI enabled products? Maybe, but you have 100+ SaaS apps, so play this scenario out: - How many places are you going to sync your core data sets? - How many cross product integrations are going to exist, and how many of them are you going to enable? (100 choose 2 is ~5000) - In how many of these products will all users have seats? - In how many of these products will these seats have permissions to use AI features? (Our support tool just told me I don't have permission to ask the agent questions, probably because I don't have the right seat type, which means more $$) My bet is a on a world with ONE place for all analysis.

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