Ben Walton

What does it feel like to be an engineering manager at Amazon: Since the RTO announcement it became popular to write shit about Amazon, but it's still one of the best companies around the world. A few weeks ago, Gilad Naor shared with the 'Leading Developers' readers 3 lessons from his time as an engineering manager at Amazon. Here is the first one, read the full article here: https://lnkd.in/dHBxv2Ha 𝟭. 𝗦𝗼𝗹𝘃𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝘄𝗶𝘁𝗵 𝗺𝗲𝗰𝗵𝗮𝗻𝗶𝘀𝗺𝘀 My first meeting at Amazon was baffling. I entered a room with about a dozen Software Development Managers (SDMs) and Product Managers (PMs). Everyone sat in silence and looked at their laptops or the printed papers they had before them. It was my second day at Amazon, and I picked up one of the extra sheets and started reading. After those first ten awkward minutes, everyone finished reading and the meeting began. Why do Amazon meetings always start this way? This is a specific example of how Amazon approaches problem-solving. It is the "Good Intentions Don't Matter" approach. In a famous internal video, Jeff Bezos talks about why good intentions are irrelevant. When things don't work, it does not matter what people wanted. All that matters is fixing the problems with mechanisms. For example, many busy managers come to meetings without first reading the prep material. They all intended to read the 6-Pager before the meeting. They just got sidetracked by the latest emergency. Scolding the managers won't solve the problem. A mechanism will. This is why all Amazon meetings start with a study period. The remaining meeting time is then spent on high-quality decision-making. Meta solves the same problem by creating cultural norms. I can't count the number of times that I heard a senior leader cut off the presenter: "Stop, assume that everyone here already read the slides. Let's get to the point." This is a culture-first approach. I have seen this work well in some teams, and not work at all in other teams. At Amazon, the solution is part of the company's "operating system". ------------------------- Anton here - by now everyone is familiar with the 6-pager concept, but that "operating system" thinking can be used almost anywhere. Think about something annoying that your developers do, and how can you solve it. For example, I remember being annoyed that people don’t update the Jira tickets. Finally, after requesting multiple times, now we just take 20 seconds from the standup to update them.

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Today was, personally, the culmination of over 10 years of waiting to attend #GoogleIO. There is no other event which brings the engineering workforce across the world together this way, and for me it was nothing less than a fan moment to be invited to Shoreline, and be a part of and interact with the pool of talent from Founders, CxOs, Engineers and all other leaders from startups to large scale organizations across all the verticals. My overall thoughts on the 2-day Google I/O: 1. AI dominated every announcement, from Search to #Android, Photos, YouTube, the web, and developer tools. Google’s hold over the mobile and web space makes this significant. 2. Gemini was the star of the show, especially the nano, flash variants and the 1.5 Pro with its increased 2M context window token limit—a big deal. The in-person demos of offline, on-device Gemma model inference using MediaPipe on Android were impressive and displayed a faster performance than I expected. On-device AI models are getting better and faster, but the openness of this ecosystem on Android remains to be seen. 3. Project Astra hints at a universal assistant future, as Demis Hassabis said. But a day prior to the Google IO, OpenAI stole some thunder with multimodal GPT-4o and its Apple partnership. My personal ick is—asking random things to your phone with your camera pointing things in public feels awkward haha, but maybe that’s just the introvert in me. 4. The keynote was really nice but at point felt like a series of Gemini's summarization demos. I wanted more on Android, which was largely missing. Innovation in Android seems to have plateaued for a while. 5. My first visit to the Bay Area was memorable. Google 's beautiful campus deserves a mention! The event was well-organized, with 1:1s with Googlers (what a brilliant idea) and open lunch tables fostering great discussions. 6. OpenAI is giving Google serious competition in innovation. OpenAI's models still produce higher-quality outputs, and many organizations, including Esper, prefer their API-accessed models for the quality and simplicity. Google, however, has a strong hold on the mobile and web ecosystems, allowing it more time to catch up. Google's deep AI integration across its product line demonstrates its capability to embed AI into daily life, something OpenAI can't match alone, as evidenced by its partnership with Apple. Final thoughts: Google I/O was everything that I expected it to be, and more. The live stream version really does not do justice in describing on how awesome things are in person. If you get a chance to go, please do! Definitely looking forward to be back next year!

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The policies being driven forward by Thierry Breton around the EU AI Act have been utmost damaging for the European tech industry, and they need to be revised as soon as possible. We need to better balance driving European innovation through data collection and modeling with conflicting needs such as data protection and safety. We need to ensure we can turn these developments into businesses that can be the pillar of the next generation of companies that provide productivity growth in Europe. We have no other choice - either we do this here, or we will have to take over products developed in the US and in China, as it already happened with search engines, cell phones, and social networks. We wouldn't want to let this happen with AI applications in robotics or digital assistants. #euacc #euaiact #aiact

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The story of inspeq ai is pretty amazing. Two engineers who didn't know each other, and didn't have an idea, both with backgrounds in multinational big tech companies in Ireland (Amazon, Microsoft, LinkedIn, Meta), decided to leave their jobs and take the entrepreneurial journey. They met eachother in the Founders Talent Accelerator, became co-founders, and within just a few months, have raised $1M to address a big global issue in AI safety. And nice to see also multinationals leaders as angel investors also, including the former MD of Meta Ireland, a senior executive at Salesforce, Gong, BT, and many others coming in alongside VCs Sure Valley Ventures (shout out to DC Cahalane) who led the round with Delta Partners. Bit of flywheel effect between multinationals and startups. We need more startup stories like this! If you're in a big tech job right now and have that entrepreneurial energy inside you, come down and have a chat with us or apply to the next programme. Or if you know someone who has that energy, share this story with them. Congrats to Apoorva Kumar Ramanujam MV, to the Founders team Heather Morris Jane Dillon Shiu Lun Tsang Emily O'​ Gorman Deirbhile Gorman. Inspeq AI raises $1.1m to grow staff as it plans further AI platform development https://lnkd.in/ekzmcnQa Apply: https://lnkd.in/e3gH7bW6 Founders is a pilot programme that is funded by the successful investments from NDRC startup portfolio, an initiative of Department of the Environment, Climate and Communications. Dogpatch Labs PorterShed RDI Hub Republic of Work

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How good are Trainium and Inference clusters for online serving of production traffic? Check this blog from Trishul Chilimbi on how Rufus responses are powered with high throughput and resiliency. #Trainium #Neuron #AWS Amazon Web Services (AWS)

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+1. The only goal for engineering productivity measurement should be to help improve developer happiness by identifying pain points and fixing them.

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🚨 Job Alert: Privacy Engineering at OpenAI Dublin 🚨 Ever wanted to tackle some of the most intriguing privacy challenges of our time? Love solving complex problems and want to make an impact in the world of AI? Well, have I got news for you! Privacy Engineering at OpenAI Dublin is hiring! 🎉 But here's the kicker—you'll have to work with me! 😱 Yes, I know, it's a lot to handle, but someone’s gotta do it. 🔍 What you’ll be doing: - Crafting solutions for cutting-edge privacy challenges. - Protecting data like a digital superhero. - Debating whether it’s “privacy engineering” or “engineering privacy.” - Avoiding my extremely detailed explanations of the difference. 🌟 What you’ll get: - The chance to work with an amazing team (seriously, they make up for my quirks). - Opportunities to shape the future of privacy in AI. - Regular exposure to my amazing sense of humor—whether you like it or not. Think you’ve got what it takes? Apply now before I think of more reasons why you shouldn't! 😁

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Continuing to learn about AI at the #DublinTechSummit today. Lots of excitement and curiosity around its usage here. Expectations from many speakers that its impact on traditional businesses will accelerate massively over the next three years. Many discussions on ethics and responsible AI governance too.

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𝗔𝗿𝗲 𝘆𝗼𝘂 𝗹𝗼𝘀𝗶𝗻𝗴 𝘀𝗹𝗲𝗲𝗽 💤 ? because you can't pinpoint your CI bottlenecks or spot problematic trends? At Pinterest, we faced the same challenges—but we’ve found a solution. 🌟 In our latest Pinterest Engineering blog post 🔗 https://lnkd.in/eJJ_GpGW We share how we’re leveraging honeycomb.io to identify CI root causes through cross-data correlations. Discover our innovative approach for categorizing CI failures in real-time using job log analysis. Learn how to segment CI jobs by agent wait time, script execution, specific Bazel targets, or any other level of detail tailored to your needs. Our enhanced CI observability metrics have let us improve CI stability and boost developer productivity—and they could do the same for you! Check out the blog for the full breakdown and see what’s possible when data-driven decisions guide your CI workflows. 🚀 Let’s make CI faster and more reliable together! #DevOps #DevX #CICD #honeycomb #observability #engineering #softwareengineer

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Pretty interesting about moving from cloud back to on-premise setup

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🚀 Ever felt overwhelmed by the sheer number of tech tools out there? 😅 You’re not alone! I have been getting a lot of questions about how I approach learning new technologies, and I realized it’s time to share my insights! ✍️ In my latest article, I outlined my personal strategies for mastering new tech tools efficiently. 💡 https://lnkd.in/dxDTwA-C Whether you are a seasoned developer or just starting out, these tips can help streamline your learning process and boost your productivity. 📈Curious about my journey? 🌟 Check it out and let’s discuss how you tackle learning in this fast-paced tech world! 🤔💬 #Learning #TechTools #DeveloperJourney 

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That's wild 🤯. Meta & Google is still on mono repo in 2024. I suppose it's more cost effective for both companies to re-engineer Mercurial & Perforce (respectively as "Sapling" & "Piper") & build custom development tooling, than to change their workflow for all of their engineers. In the case of Meta: a standard git merge operation would have taken 45 minutes. Legends has it, they consulted the Git team & was told to break up their repo. So instead, they went to the Mercurial team & got a better reception. Here's a perspective from one of their engineer. But wait... 🤔 the source code for Sapling & Piper + all of its IDEs & build tools are (probably) not store in the same repo? For sure with Meta Sappling, it's not (you can find it on GitHub). Same story with Android. These repos have totally separate concern domains 🤓 I get it. So maybe, it's "mono-repos" & :. truly, no actual mono repo 😅 With the collective wisdom of the Meta & Google engineering teams (combined!), who am I to judge 🫠

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Amazon-to-Google-to-Amazon #a2g2a thought of the day: interesting to see how RTO (Return-to-Office) outcomes are entirely different for the two companies. In my post today, I don't really want to go down the path of debating whether RTO is "good" or "bad". There's very emotional and valid opinions on both sides, and it affects people's personal lives in real ways. Please be respectful. Whether you agree with the policy or not, for it to actually work it does need *critical mass*. Both companies have essentially the same RTO policy (3 days/week expectation), but there's significant differences is in how the message was delivered and enforced - and the outcome. Google’s 3-days-per-week was mostly a “pretty-please, would-you, if-you-don't-mind” with no actual enforcement (but some vague threats). So most people ignored it. They still do. Leadership got frustrated and the message got less polite over time, but nothing really changed. Even as of 3 weeks ago, when I was still a Google employee, the buildings were fairly empty. That made being physically in the office significantly less useful, other than enjoying the perks of free food and massages by myself (and occasionally with 1 or 2 coworkers). Amazon’s 3-days-per-week came with actual enforcement. Amazon used badge reader data to track when people were actually coming to the office, with consequences. It does feel a bit draconian, but you can’t argue with the effectiveness of saying “we have a policy that we believe is business-critical and we’ll enforce it or else.” I appreciate that when I come to the office, I can find my coworkers there and we can have f2f meetings. There’s critical mass for RTO to actually be effective. Amazon has picked a lane. Personally, I have not figured out how to truly be productive and happy working remotely in the last 4 years. I respect and appreciate the fact that some people have, but I haven’t. I do like the option to stay home a day or two, skipping my long commute, working from a lounge chair in my backyard on a sunny day. But there’s nothing like the energy in the room of a good group meeting, or the chemistry of a face-to-face 1:1, or the enthusiasm of two engineers standing in front of a physical whiteboard drawing boxes and arrows with markers brainstorming about the future. Or the bonding of sharing a meal or a walk between buildings with a coworker. I feel energized when I’m physically in the office. It literally charges my batteries. I’ve been coming to the office 4x/week and loving it. 

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When building communities I used to think "failing fast" was the secret to success. Then I realized it was holding back my community-building journey. I've built the largest coding community in Ireland and we've definitely had our ups and downs. So what did failing fast do? It bred instability. Communities aren't built on speed; they're built on trust and connection. My wake-up call came when I saw engagement plummeting. Members are not just statistics; they're unique individuals with voices that need to be heard. So I shifted gears. Here’s how I transformed our community: ▶️ Listening became my priority. Engaging in conversations revealed insights we never imagined. ▶️ We celebrated every milestone, no matter how small. This nurtured a sense of achievement and belonging. ▶️ We chose genuine interactions over chasing metrics. This fostered resilience and unity. The outcome? The metrics might not be as impressive, but the quality of the connections was much better. And quality > quantity!

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Falling back in with a side-quest Colab about LLM evals (high level) - its not just about prompting. Including my absolute favorite: Cosine Similarity. I love this algorithm (or is it technically just a function? ratio? idk/care). This colab is a bridge to some concepts I'm hoping to get to soon: like how to automate quality evals, and auto-reject outputs that do not closely follow the prompt instructions. These are things that really should be handled by code when creating LLM-backed services for production purposes. Again, this is using the smallest Llama 3.2 1B model, and there's no training step this time, so you can run it on just a CPU runtime without much fuss. LMK what you find (anyone who runs this should get different results, and those results are probably always going to be interesting)

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Really insightful! Data driven decision making is one thing I too liked about my time at Amazon rather than just opinions or strong feelings. Sometimes, though its important to take strategic bets/risks to gain competitive advantage even when there is not sufficient data. And we balance between diving deep and bias for action. Deriving early "impact" signals on our investment and cutting our losses early on if things are not moving in the direction we wanted is another strategy. Having both short term and long term KPIs and measuring against them incrementally is important!!

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Hey everyone, I am an investor and advisor to Katanemo.... They are reinventing the infrastructure primitives for GenAI and launched Arch - https://lnkd.in/gCrbbkEV - an intelligent prompt gateway. Give the project a look on Github, and star the project if it resonates

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I first joined Amazon in December of 2005. Even though I left for two years, my "Amaversary" still coincides with the end of the year and a natural moment for reflection. As I reached my 17 year mark this December, I also had the privilege of working with Amazon Careers to share some of my journey and thoughts about individual contributor technical leader and people manager career paths. In my ruminating, I put together far more content than could be used for a single article. So, I've decided to post here as a series of Q&As - in case others might find my observations, experiences, and perspectives interesting or useful. Below is the first of 6. 1. 𝘽𝙧𝙞𝙚𝙛𝙡𝙮 𝙨𝙝𝙖𝙧𝙚 𝙮𝙤𝙪𝙧 𝙘𝙖𝙧𝙚𝙚𝙧 𝙟𝙤𝙪𝙧𝙣𝙚𝙮; 𝙬𝙝𝙖𝙩 𝙢𝙤𝙩𝙞𝙫𝙖𝙩𝙚𝙙 𝙮𝙤𝙪 𝙩𝙤 𝙩𝙖𝙠𝙚 𝙤𝙣 𝙙𝙞𝙛𝙛𝙚𝙧𝙞𝙣𝙜 𝙘𝙖𝙧𝙚𝙚𝙧 𝙥𝙖𝙩𝙝𝙨, 𝙄𝘾 𝙫𝙨 𝙢𝙖𝙣𝙖𝙜𝙚𝙧? I started my career as a software engineer 25 years ago. I've worked for startups, enterprise companies, and 7 different organizations over 17 years and two tours at Amazon. I've written firmware for robotic camera mounts; built highly scalable distributed systems; designed restaurant marketing, ordering, logistics, and operations software; created automated test harnesses for mobile games; tested HD DVD encoding; helped launch grocery delivery to customers around the globe - just to name a few of the many cool things I've had the privilege to work on. I've been an entry-level software engineer, a technical lead of teams, a software manager on a couple of occasions, chief software architect reporting to a CTO, and (for the last few years) Amazon Principal Engineer directly supporting a VP with about 200 engineers within my remit. I first became a manager because I mistakenly thought it was the only way to continue growing as a leader, and in many ways I failed. I learned some very humbling lessons about leadership through that experience, which I used to be a better individual contributor technical leader on my path to Senior Engineer. My second time as manager was because my organization had a need that I could fill. I had grown enough as a leader that this time I was much more successful. I said yes to an opportunity that started with managing a small team through delivery of a complex and critical project. Once I grew a high performing team that delivered that initial project, I took on more scope and expanded into multiple teams. After a couple of years of success growing and investing in my teams so that we could deliver greater value to our customers and business, I decided to prioritize being close to my family. For me, at that time, it meant giving up my people management role and returning to the role of an individual contributor technical leader that supports a globally distributed organization. Even though I really enjoyed my time as a people manager, there is no better job for me than that of a Principal Engineer. #amazon #careerdevelopment #technicalleadership #peoplemanagement

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Amazon-to-Google-to-Amazon #a2g2a thought of the day: Have Backbone, Disagree and Commit This is a core Leadership Principle at Amazon and it is defined as “Leaders are obligated to respectfully challenge decisions when they disagree, even when doing so is uncomfortable or exhausting. Leaders have conviction and are tenacious. They do not compromise for the sake of social cohesion. Once a decision is determined, they commit wholly.” You may feel amazonians give you jarringly direct feedback at times. At the beginning, back in 2009, I found it borderline rude and off-putting, and downright terrifying when coming from a Principal or Director. But I came to appreciate this aspect of the culture - and miss it terribly once I left Amazon. Once I understood it was not personal, I always knew where I stood with people, and I knew I was always going to get honest feedback about my ideas - even the terrible ones. I was reminded of that a couple of weeks ago. I had to write an endorsement for a promotion. I was happy to do it but I was in a rush, so my writeup was subpar. The manager sent it right back to me and asked me to rewrite it.  He was absolutely right - I was thankful that he had the Backbone (incidentally that’s also Insist on the Highest Standards). My second version was much better. On the other hand, Google places a disproportionate amount of emphasis on being "nice" to each other which is a lovely sentiment but it ends up incorrectly translating to "don’t say anything that might offend somebody or hurt somebody’s feelings, at all cost." And so in the pursuit of “googlyness” the culture sacrifices directness, honesty and candid feedback. There were so many instances where I found myself wondering, "What is this person actually saying to me right now? Do they agree or not? Please, for the love of God, stop beating around the bush and just get to the point!” My low point came when one of my managers at Google shared that a co-worker had provided pretty negative feedback about me. The feedback was fair, but I was frustrated because I had been meeting with that individual every other week for a year and they had not once said any of those things to my face. I wish they had - we could have had a much deeper, meaningful, relationship and I could have acted upon those things earlier. Another example: My Google leadership hired an expensive outside speaker to conduct a full day workshop on Radical Candor - yet a month later everybody had reverted to their old behaviors. Again: what you bake into the DNA of the company really, really matters. Unless the culture enshrines it, it’s hard to go against the current. Amazon enshrined that this a critical part of its DNA. I did learn from my time at Google though. I believe it’s possible to be both "direct" and "nice." In the past, I was more worried with being direct than with being nice. I think Google made me a better human being, but without having lost my Amazon directness. I hope :)

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