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I am a tenured Google employee of…
Articles by Christopher
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Google Cloud in State & Local Government
Google Cloud in State & Local Government
Google is betting big on State & Local governments. My team is growing (a lot!) and I’m going to be hiring 10+ customer…
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Christopher Hein shared thisHahahahaha. Nice job on this one LinkedIn. I've never been told to apply for a job on my own team before. 🤣 Hope I can pass the interview process, I hear the manager on this one is a doozy. Guess it gives me the opportunity to say... If you're a CTO-type with strong Cloud & Research skills here's the link: https://lnkd.in/gqPFY-TC maybe we can study for the interview process together. Note: If you message me there's a good chance it'll go into a blackhole in which LinkedIn messages go to die. If you're interested in the role please submit!
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Christopher Hein shared thisI really do enjoy the productivity benefits* that come from frontier generative models. But when it comes to material changes to the world, it's news like AlphaGenome Atlas and WeatherNext 3 that might well be the building blocks of life saving AI. *~90% of my token spend is on making meme videosChristopher Hein shared thisGoogle DeepMind doesn't get enough credit in the tech press for the amazing work it has done to advance fundamental scientific research. AlphaFold was a huge gift to human knowledge. Did it solve drug discovery? No. Did it advance science? Unquestionably. Now they are doing it again, using their AlphaGenome model to create a catalogue of all 9 billion possible single-point mutations that can occur in the human genome along with predictions of their likely effects. The database is being made freely available to academic researchers and will be made available to commercial entities under a paid license "soon." The predictions are not quite at the level of accuracy of AlphaFold's. But they are good enough to save researchers a lot of time and effort—at the very least, to point them in useful directions. The scientists Google DeepMind partnered with to beta test the catalogue, which Google DeepMind is just calling Atlas, reported some impressive results, including helping to pinpoint the mutation that had caused one patient's previously mysterious genetic brain disease. You can read my coverage here in Fortune:Google DeepMind publishes AI-powered predictions for the effect of all 9 billion possible single-point mutations to human DNA | FortuneGoogle DeepMind publishes AI-powered predictions for the effect of all 9 billion possible single-point mutations to human DNA | Fortune
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Christopher Hein shared thisI'm happy to see policies like Gold Eagle clearinghouse documenting the dire need for better cyber defense. The need for proactive threat sharing in a time of escalating attacks is clear. What's sometimes less clear is the architectural design that allows you to ingest and act on those threat feeds in real time. Cyber resilience means something different now: -Upstream detection to uncover and verify vulnerabilities across dependencies before deployment. -Autonomous code-level reasoning to accelerate root-cause analysis without false-alarm fatigue. -Automated patch generation that keeps human engineers firmly in control while eliminating manual remediation backlog. Through Google’s Fairwind Program, we're solving for all three leveraging Gemini 3.8 Flash Cyber to help teams autonomously analyze vulnerabilities and deploy verified code fixes in real time. I'll be at Google Public Sector Summit on October 20th demonstrating and talking about these capabilities. Reserve your spot to join the session: https://lnkd.in/gyHaviHx #GPSSummit
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Christopher Hein shared thisWe've had some phenomenal fellows over the years. Such a huge benefit to Google.Christopher Hein shared thisTaking the next step after your military service? The SkillBridge Military Fellowship provides transitioning service members and military spouses with hands-on training and civilian work experience through a corporate fellowship during the last 180 days of service. Apply by October 23rd to build your professional skillset and set yourself up for success in your next chapter → https://goo.gle/4zUAZM2
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Christopher Hein shared thisI love watching professional football (lifelong Steelers fan). One thing that always strikes me is how the most prestigious awards almost always go to the player with the ball in their hands (56% of Superbowl MVPs are QBs). In many ways this makes sense. You're putting a lot of trust in that player and their actions definitely dictate the course of the game. And yet it always feels unsatisfying to me in that it doesn't take into account the teamwork required to make that person successful. From the offensive line all the way to the coaching and training staff that prepared them for that moment. All that is to say... I'm really grateful for the recognition from Government Technology to be listed as one of their 2026 AI 50 list. But the reality is that there is an incredible team here at Google Public Sector doing the work. Thank you to all of them for creating the opportunity for me to work with US Public Sector institutions on their AI policies and implementations. There's no task more important than getting AI in government and education right. I'm energized and ready to keep pushing us forward. I remain optimistic that we can use AI to broadly benefit society through our public sector institutions. It's time to work.
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Christopher Hein shared thisTwo things stand out for me: 1. Foothills of the singularity is a good tagline. 2. The future is not yet written. On the second point - this is something I remind folks of all the time. We often act as if the negative aspects of AI are unavoidable. That we don't have any control, but in fact we do. We are going into this revolution with eyes wide open and as such we should be helping to steer.A Framework for Frontier AI and the Dawning of a New AgeA Framework for Frontier AI and the Dawning of a New Age
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Christopher Hein reposted thisChristopher Hein reposted thisThe 𝐑𝐚𝐩𝐢𝐝 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐓𝐞𝐚𝐦 at Google Public Sector is growing, and we are looking for a 𝐆𝐞𝐧 𝐀𝐈 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭 to join our Federal Engineering build team. We don't just talk about the "𝘢𝘳𝘵 𝘰𝘧 𝘵𝘩𝘦 𝘱𝘰𝘴𝘴𝘪𝘣𝘭𝘦"—we build it. In this role, you will get your hands dirty building prototypes on Google Cloud Platform to solve complex mission problems for Federal Civilian agencies. If you are obsessed with Gen AI, love rapid prototyping, and want to use your skills to make a tangible difference in the public sector, we want to hear from you. Apply here: https://lnkd.in/efUnBS9A
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Christopher Hein reposted thisChristopher Hein reposted thisWe are excited to announce the opening for our California/Hawaii Engineering Leader position. This front-line leader will collaborate with an exceptional team, including Gabriel M., Amanda Stange, Reymund Dumlao, and Christopher Mende. The selected leader will work with an amazing group of customer engineers, account managers, key account executives, principal architects, and a fantastic customer base within California and Hawaii's State, Local, and Higher Education sectors. We are looking for an experienced SLED engineering leader, ideally located in the Sacramento or Northern California market. Please feel free to reach out or share this position. For more details, visit: https://lnkd.in/dhxKizzy Elizabeth Foti, Elizabeth Moon, Brent Mitchell, Christopher Hein
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Christopher Hein shared thisI've been tracking this one for a bit. Really exciting work being done to leverage AI to improve permitting.Christopher Hein shared this📢 Today is a big day for the Digital Planning Programme. Extract - our AI-powered tool that converts historic planning maps and documents into standardised, usable planning data - is now live and available to every local planning authority in England, for free. What Extract does may sound simple (it's not!), but the impact is significant. Tasks that currently take planning and GIS officers up to two hours can now be done on average in two minutes - with officers reviewing and approving every output before it's exported into standardised formats for the national #PlanningDataPlatform. Huge thanks to our partners at Department for Science, Innovation and Technology's Incubator for Artificial Intelligence, the Open Digital Planning community and the 34 local planning authorities whose participation in research and testing made this possible. You helped us build something councils are already starting to use. The Ministry of Housing, Communities and Local Government and the Incubator for Artificial Intelligence are now also trialling a new AI tool, built in partnership with Google DeepMind and Faculty, in Barnet Council, London Borough of Camden and Dorset Council UK, that aims to halve the time it takes to process planning applications, from 8 weeks to 4. 🔗 Read more here: https://lnkd.in/e-fxexH7
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Christopher Hein reacted on thisChristopher Hein reacted on this𝗧𝗟;𝗗𝗥: Google Research just shared new work on coherent, minutes-long AI video, and I'm proud to be a co-author on the Co-Director paper, one of four in the suite. Clips are easy now. Stories are hard. 𝗧𝗵𝗲 𝗯𝗶𝗻𝗱: 𝟭. Diffusion models make stunning few-second clips, but chained pipelines suffer 𝘀𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗱𝗿𝗶𝗳𝘁: attire, props and scenery quietly change shot to shot. 𝟮. 𝗖𝗮𝘀𝗰𝗮𝗱𝗶𝗻𝗴 𝗳𝗮𝗶𝗹𝘂𝗿𝗲𝘀: one upstream artifact corrupts everything downstream, forcing manual fixes. 𝗧𝗵𝗲 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵: an agentic orchestration layer on Gemini and Veo (with SynthID watermarking) that treats long-form video as global optimization plus world-state tracking: • 𝗖𝗼-𝗗𝗶𝗿𝗲𝗰𝘁𝗼𝗿: +18.8% overall quality on GenAD-Bench (81.4 vs. 68.5) • 𝗖𝗔𝗡𝗩𝗔𝗦: up to 21.6% background, 9.6% character and 7.6% prop consistency gains • 𝗔²𝗥𝗗: up to 30% consistency and 20% narrative coherence gains across 3-, 5- and 10-minute runs • 𝗩𝗤𝗤𝗔: +11.57% (T2V-CompBench) and +8.43% (VBench2) absolute improvements On a personal note: I'm very proud to have a patent pending related to this work. I can't share the details yet, but the puzzle piece in the photo from the Google Patent Team says it well. Every innovation is one piece of something bigger. 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: For pharma and ISV teams, consistent video at scale opens doors in training, education and product storytelling. Consistency and closed-loop quality checks are the prerequisites. In regulated settings, human review stays essential, and the team is exploring human-in-the-loop workflows next. Huge thanks to my Co-Director co-authors: Yale Song, Yiwen Song, Nick Losier, Nathan Hodson, Daniel Vlasic, Gia Khanh Le Viet, Zack Chomyn, Brett Slatkin, Scott Penberthyy and Tomas Pfisterr, plus the Google Research team. It's a privilege to learn from you. 🔗 https://lnkd.in/ggu8fdag #GoogleResearch #GenerativeAI #GoogleCloud #AI #VideoGeneration #AgenticAI #Veo #Patents
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Christopher Hein liked thisChristopher Hein liked thisWe’re hiring — right now — for Research Engineers to join Polaris, a new team at Google DeepMind. As synthetic data pipelines hit their ceiling, the hardest engineering problem in AI is translating the full depth, nuance, and complexity of real-world software engineering into rigorous evaluation frameworks and training benchmarks. That’s why we’re building Polaris. Rather than generating a large number of tasks using a synthetic data pipeline, engineers on the Polaris team focus on creating a smaller number of tasks that more closely capture the complexity of real-world software engineering — taking roughly a week to complete, from ideation to final approval. Alongside building these benchmarks, you will have the autonomy to launch entirely new projects within DeepMind aimed at advancing Gemini’s training data and evaluations. You’ll create experiments, prototype implementations, design new architectures, and tackle real-world problems across AI, NLP, compilers, search, and hardware/software performance analysis all while staying connected to the wider research community through university partnerships and publishing papers. Great talent comes from anywhere. We're hiring across the entire spectrum of experience to find the best people in the world. We want to hear from you if you are: • A Competitor or Hacker: You thrive in competitive programming, math olympiads (IMO, IOI, Putnam, USAMO), or hackathons, and love constructing deeply challenging problems. • An AI-Native Builder: You already live in AI coding agents and LLM-based workflows to ship software at high velocity. • A Polyglot Engineer: You can parachute into unfamiliar programming paradigms, tools, and technical stacks and master them rapidly. If you want to build with a team at Google DeepMind, or know someone who belongs in this room, join us. Apply now → https://goo.gle/3V5Kacp
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Christopher Hein reacted on thisChristopher Hein reacted on thisI am incredibly proud of this win and the team that made it possible. Large language models can analyze and write code. Turning that capability into reliable, agentic modernization of complex, mission-critical systems at scale requires a new kind of engineering. That is exactly what our team has proven we can do. Now we get to help the U.S. Air Force modernize more systems, faster.
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Christopher Hein reacted on thisOpen role working with and learning from a great one👇
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Christopher Hein liked thisChristopher Hein liked thisApparently, somebody who in their 20s who has only ever worked in tech thinks that it's really easy to automate any other job in any other industry.
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Christopher Hein liked thisCongratulations to the my colleagues on the Data Commons team and the UN teams behind today’s launch of UN System Data Commons. UN System Data Commons is an open-source platform built on Data Commons by Google that brings global statics from more than 20 UN agencies together and makes it easier for people and organizations working on some of the toughest problems around the world to use. The teams used AI to help make the information accessible to more people – users can ask questions in plain language and get relevant data and interactive visualizations and AI assistant capabilities can help with data analysis, charts, graphs, and reports. I encourage you to take a look! Congrats to my colleagues Prem Ramaswami and team.Christopher Hein liked thishttps://lnkd.in/gwWMQHuq For 20 years, I have worked at the intersection of technology and social impact across health, crisis response, education and urban design. Today, the launch of the UN System Data Commons feels like a full-circle moment. For decades, some of the highest-integrity data in the world on how we work, learn, stay healthy, and care for our loved ones has lived in isolated silos across UN agencies. It is an honor to be on the floor of the UN today, as the Secretary-General announces the UN System Data Commons, a major first step in putting this treasure trove of this data in one, AI-ready repository that anyone can use. (https://data.un.org built on Data Commons by Google) Questions that might have taken users days or weeks to answer can now be addressed in minutes. Here are just a few of the things you can do on UN System Data Commons. Possibly most importantly, you don’t have to be a statistician or a programmer, either! -Make custom graphs and dashboards: Automatically harmonizes datasets from 20+ (and counting!) UN system entities. -Explore in natural language: Enables researchers, journalists, and policy analysts to query complex development statistics in plain language. -Use AI agents: Leverages MCP endpoints to allow AI research agents to query trusted, validated multilateral data to make your own applications or help you with your research. Today, we are starting out with more than 20 UN agencies. We’re targeting 80%+ of the UN system’s priority statistical datasets by 2027, a big part of the UN’s landmark UN80 initiative, which aims to modernize UN infrastructure to break down silos across its international network of agencies. (https://lnkd.in/gpWK2JD2) We are incredibly excited to continue our work alongside the United Nations (UN DESA, UN Secretary General, and UNICEF) to make UN80’s vision a reality for the UN. And, all this technology is possible because of the great foundation of Google Cloud Platform including tools like Spanner Graph. I’d normally list all the people who made this happen, but this one was truly a team effort across the Data Commons team at Google, many of our Google partner teams, and the UN team. *Want to give UN System Data Commons a try?* A good question is all you need! You can try it out at data.un.org or point your agent at the MCP endpoint here: https://lnkd.in/gRUcdnc8 And learn more here: https://lnkd.in/gwWMQHuq
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Google Certified Professional - Data Engineer
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Shilpi Kanade
Just like Deepesh, for the past five years, I haven’t written a single line of code. Like many engineering leaders, my world shifted to strategy, org design, business alignment, and scaling teams. Coding became something I used to do. Then Claude Code was rolled out across our engineering org. We have an upcoming project to build an agent, and almost playfully, I thought: Why not? Let me ask Claude to write it. A few months ago, I had built something similar as a side project. It took real time and effort. This time? It was done in minutes. That was an eye-opener. Was the code production-ready? Maybe. Maybe not. But that wasn’t the point. The point was this: the constraints just changed. The friction between idea and implementation is collapsing. The cost of experimentation is approaching zero. I may not go back to “coding” in the traditional sense — and that’s okay. The world will still be full of strategy, architecture, and business conversations. But now, those conversations are backed by the ability to prototype, test, and explore at a speed that felt impossible not long ago. The real opportunity isn’t just writing code faster. It’s reimagining what we dare to build. We’re only getting started.
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Dzuy Linh
I’ve finally figured out a pretty awesome workflow to quickly build things. Use all the AIs, folks. 1. Talk to humans about the problem 2. Talk to Claude about said problem. Strategize. Claude’s reasoning and practicality is a good foundation. Output something PRD-like so you have a North Star. Create a single large prompt to build a prototype. 3. Paste prompt to Lovable and build out the UI. Fine tune in Lovable because it's fast and has the best understanding of good UI patterns. No backend, no auth, no integrations yet. Just clickable prototype to get human feedback. 4. Setup a backend and a frontend somewhere (go, supabase, railway, vercel, etc). 5. Open the Lovable code in Codex to build out the BE/FE and tell it to clean up Lovable’s crappy code. 6. Finish off in Codex with integrations, auth, security checks Iterate / ship like crazy Human —> Claude —> Lovable —> Human —> Codex <—> Ship Funny part is once you adjust to this new speed, you only want to go faster and non-stop. For those who have gone deep into AI builder mode, what’s your workflow look like? I can’t be the only one suddenly looking to shave off minutes while I tell the bots what to do.
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Kushan Patel
The org chart said 40 engineers. The roadmap got 12. The other 28 were keeping the lights on. More than once in my career, I've been handed some version of the same mandate: help us improve engineering velocity, in partnership with engineering and design. The framing always assumed velocity was a process problem. Better prioritization. Tighter planning. A few weeks of looking turned up the same answer every time: years of accumulated systems, multiple pivots, and a maintenance burden that crept up year after year. Process was not the major constraint. Capacity was. Here's why this matters now. Everyone is pointing AI agents at new feature work. That amplifies the 12 and does nothing for the 28. And the scarce input in the agent era isn't agents. It's engineers. 12 engineers directing 100 agents each is 1,200 agents of supervised work. 40 engineers directing the same 100 is 4,000. I wrote about how to run this play: how to measure your deployable fraction, where the ripest agent targets hide (runbooks that are documents, the systems only one person understands), and why the agents should go to the KTLO team rather than an AI tiger team. Honest question for the engineering and product leaders here: do you know your deployable fraction? Many leaders I've asked have never truly computed it. https://lnkd.in/gQHbp-iC
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