Tim Julien

SCALE. Technology driven scale wins. Sales, PR or Investor driven “scale” often proves to be an unsustainable period of growth. Boom has built the infrastructure to win.

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If you're connected with me, you know I scream about how necessary integrations are. Check out this piece where I explain more for insideBIGDATA!

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I'm having enlightening convos with folks who deliver infra for others to run. It sounds like "runbooks/wiki docs" are a real problem from a handoff/support perspective. We have an elegant solution, when you deliver runbooks as "click to play/pre-configured" Notebooks, and a command fails, the user gets an `escalation button` that shares a link to the output/metadata into the shared Slack room. It's ideal for bridging the gap when there's a support relationship. 🤓 This sounds like a case study in the making.. anyone else struggling with this?

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We like writing engineering content Our engineers are at the center of what we build and our accountants experience. We're defining what AI-native looks like for accounting. We like writing engineering content because we want engineers who join us to know how we think about problems. This week, our very own Matthew Duong wrote a piece on Single Sign-On (SSO), breaking down the essentials and actionable tips (link in the comments) For founders, improving the login process and making it easier to access your platform means a simpler experience. For enterprises, it means reducing the number of passwords users need to remember, reducing the risk of security breaches. Shout out to Amer Taleb who joined us recently and took our content game to a new level. We have a lot more coming soon: new product features, employee spotlights, and our view of the AI Accounting space. Happy Friday from everyone at Truewind!

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Two weeks ago I posted a question "AI vs API vs UI?": https://lnkd.in/e3Z2cXd8 It asked whether the value of UIs will diminish in a world of AI Agents, a counter to Zdenek's question of whether we should still be building APIs at all? No doubt that there are a lot more UIs out there in the world than public APIs today. This reminds me of the discussion in the world of self-driving cars: many folks thought that we'd only achieve self-driving if we updated all the road infrastructure to be "machine-optimized". Many also think that we can only have self-driving when ALL cars are self-driving. Both seem ridiculous to me; the world is messy and the only scalable system is one that can deal with that. Now people are starting to see that we are on the path to self-driving which is mostly vision-based - like its human counterparts - and drive (more) safely alongside human drivers on existing infrastructure. The recent Claude announcement of AI computer use is a great demonstration of the capability of modern AI to deal with that messiness: https://lnkd.in/ePhEbz7w Arguably this strengthens the case for UI > API in the future. I think this might be true for legacy interfaces - why go to the effort of creating a nice API if you've already got a UI that AI can deal with? However, what about net new development? I still think the cost and difficulty of building decent UI vs good API means that focus will shift to API >> UI for agents. We're talking long-term here though, maybe 10 years. One interesting thing though, is how will businesses handle a shift to agents interacting on behalf of users? Such a strong disintermediation is going to create an even stronger deployment of 'aggregation theory' (https://lnkd.in/epMKwjdM) with winning agents having enormous power, more even than Google has today. What do you think?

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I’ve recorded a few episodes of a new show I’m calling Commit History. Each 15-to-30 minute episode examines an interesting commit to a significant open source project. So far, we’ve examined things like how NodeJS added the fetch API, how a 25 year-old bug in Firefox finally got a fix, how the Zed editor sped up “select-all-matches” by a factor of 250x in a 75 line commit, and we’ve read commits in languages like Javascript, Rust, C++, Ruby, and Zig, with more to come. A lot of us got into engineering because of our curiosities - which led to tinkering, sometimes destructively, but always starting with an observation, asking ourselves “How?”, and pulling out the tools - either screwdrivers or terminal windows, and not stopping until we got an answer. I’ve long assumed those days were behind me, but recently I reflected on how often I dive into open source code, sometimes because an unexplainable bug keeps popping up at work, or documentation is lacking, or a top story on HackerNews caught my attention - and I find myself right back into that hacker mindset, digging deeper until I know how it works. I haven’t changed nearly as much as I thought I had. Commit History, so far, is just turning my camera on to record something I’ve done for most of my adult life. In each episode I’ve learned something new, and however simple that might sound, it serves as the bar to meet for me to publish an episode. If any of this interests you, you can subscribe to the newsletter for the show here: https://lnkd.in/gHHhZY9K

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Observability products don't solve the key problem with diagnosing software issues customers face. Think about it - IF tools like DataDog and others addressed it correctly, they would fix the issue... You don't go to a car repair shop to get handed a new bumper and tools after getting into an accident - they examine, diagnose, and repair the damage, then give you back your car. Even the latest start-ups in the space don't get this... they're tone-deaf to the actual problem.

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Real-time observability Friday: check out this feature coming soon to Capture. Real-time introspection into *all* client-side network APIs across the fleet. We will now allow you to dive into segments of the APIs to gather the most interesting info for drill down, debugging, and dashboard creation. With real-time config, workflows can then be deployed to further deep-dive into interesting cases. As an end-user / network operator for large internet companies I would have lived in this UI constantly. Can't wait to ship it! 🚀

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Early-stage fundraising is getting complicated due to SAFEs. Should they be limited to early rounds? • Angel Rounds (SAFEs): $150K-$200K raised, small valuation caps, light dilution. • Small Pre-Seed (SAFEs): $680K raised, $9M cap, 6%-8% dilution. • Big Pre-Seed (SAFEs): $1.5M raised, $12M cap, 11%-13% dilution. • Seed (Priced vs SAFEs): ~$3.3M raised, $13.7M valuation (priced) vs $18M cap (SAFEs), slightly lower dilution with SAFEs. • Post-Seed Extensions: More common, but costly in equity. #Fundraising #Startups #VC #Investment

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Gadget's internal CI infrastructure has grown super scaled for a company of our size -- we do 160k hours of CI compute per month, or 220 days of compute per day. We really exhaustively test every change we make across all the framework versions so we don't break your shit! Remarkably though, it doesn't cost us that much. We built a custom autoscaler atop Buildkite that uses GCP Managed Instance Groups on spot instances, using t2d nodes which have really remarkable price/performance and really high spot discounts. Can't speak highly enough of t2ds We decided to use plain old VMs instead of k8s because we spin up a full k3s cluster and integration test our distributed filesystem and our serverless function orchestration stack end to end for some tests. It's caught some serious stuff I resent every moment I have to spend working on CI because I'd rather be building product or yammering on to you all, but I'm glad we made this investment because it is 1/50th the cost of our previous "normal" approach and lets us do nutty stuff like exhaustively test the matrix

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Got an email "GCP's Apache Kafka service is now live" at noon. After dinner, spent half an hour confirming it works well with Timeplus. I don't think you can make the bootstrap server publicly accessible. Has to setup a bastion host or run your app within the same project/VPC. Setting up the SASL username/pwd was not easy. Follow the guide carefully https://lnkd.in/gcKEVh3g and you may need to disable the iam.disableServiceAccountKeyCreation Anyway, if your workload are in GCP already, having such Kafka service in GCP is nice way to burn your cloud credits. Yet another Kafka vendor, great.

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One of the coolest things we've been building at Truewind is our document parsing and extraction engine.   A lot of accountants deal with scanned or photographed documents like receipts, contracts, invoices, and bills.   For us, the goal is to make sifting through and classifying that information a lot easier.   Matthew Duong has been leading the charge on this project, and recently wrote about the experience on our engineering blog. In particular, he explains why ditching schemas and using PostgreSQL’s JSONB has made such a big difference for our platform.   If you’re interested in the technical side of how we’re refining accuracy and speed in document processing, definitely give it a read.   Here’s the link: https://lnkd.in/gN3Sgext

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One of the other things I ❤️ about Everlaw is our dominant approach to building software at Everlaw - optimizing for overall throughput over the latency of shipping a specific feature. It was one of my primary draws of joining Everlaw and it continues to be one of the compelling draws for engineering-minded candidates to Everlaw. People often ask me how it can work and the article (https://lnkd.in/gMSQeWbR) provides a great overview of it. Definitely worth a read!

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What are you doing this Friday at noon, Boston time? WRONG! You're joining me for a roundtable chat with Jellyfish's own CFO, Joanne Cheng on what many engineering leaders get wrong during budget planning. Treat yourself to some good tips and tricks for leveraging data effectively and driving financial impact at the company level. Come hang out, share your own tips and experiences, and meet other leaders. Click it --> https://lnkd.in/eDxaJ4tZ

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This is the initial infrastructure Tradescoop was built on. A few things have changed, some additions and removals; for example, we’ve gone from MongoDB on Digital Ocean to Mongo Atlas, Redis cloud to Memorystore, but the general appraoch remains. Simplicity. Shouts to Karl Obinna Amalu, CSM for cleaning it up and adding color ✨ #gcp #infrastructure #devops

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I added some long overdue improvements to our podcast processing pipeline today that makes it much easier for us to debug LLM prompts in production. Out of curiosity, I took a prompt to extract top quotes from a podcast episode that Lucas wrote a while ago specifically for Anthropic Claude, and tried it with a few other LLM models on Amazon Web Services (AWS) Bedrock. To my amazement, the same prompt worked straight out of the box with Cohere Command, and Mistral AI Mixtral. Both returned valid JSON in the requested format. The prompt was too big for AI21 Labs Jurassic-2 to handle, and Meta Llama 3 timed out every time I tried it. Here's a good example of quotes we extract this way: https://lnkd.in/gCEgf9vr #alwaysgetbetter #ai #llm

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Thanks Joanne Chen and Jaya Gupta from Foundation Capital for the nod! Great to be in the cohort of top notch AI companies. Observability data is untapped goldmine of information, but when the time comes (in the middle of incident), it still requires "expert" skills to find the needle in the haystack. We at Deductive AI are democratizing the expertise to everyone in the organization.

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I cancelled our team's subscriptions to Github Copilot & ChatGPT after 10 days with Cursor 🌟 What Sets Cursor Apart Seamless Onboarding: The transition was remarkably smooth, reminiscent of Chrome's early days. Cursor's team clearly understands that muscle memory can be a significant barrier to adoption, and they've crafted an onboarding experience that makes the switch a delight. LLM Flexibility: The ability to switch between different Large Language Models, bring your own, or use the default Claude 3.5 Sonnet is a game-changer. This flexibility proves to be a massive advantage, freeing users from being tied to a single AI model. Multi-file Editing with Composer: This highly anticipated feature delivers 80% of the time, and when it works, it's phenomenal. It explains code changes, shows inline diffs, and allows for selective application of changes. My favorite one - https://lnkd.in/g4aYJbJQ. Contextual Awareness: The ability to @mention files, folders, and invoke web searches has transformed how I approach parallel feature development. It's like having a hyper-aware coding companion. Intelligent Auto-complete The tab auto-complete function is surprisingly powerful, working seamlessly across lines and files. It often feels like it's reading my mind, significantly speeding up coding sessions. Smart Inline Editing Cursor's understanding of the existing codebase shines in its inline code editing capabilities. It's prevented me from creating redundant utility functions by suggesting existing, similar functions—a huge time-saver. 💡 Pro Tip: Embrace smaller, more frequent code iterations. Commit changes often; you never know when you might need to start over on a change set. 🔧 Areas for Improvement Composer occasionally has UI glitches, taking over the entire window or hiding its title bar. Familiarizing yourself with keyboard shortcuts can help navigate these issues. Sometimes there's a disconnect between Composer's suggestions and what it displays. 🤔 Is Cursor Worth the Hype? For me and my team, it's a resounding yes. We're transitioning to Cursor as our primary development environment. I've noticed a significant reduction in my use of standalone AI consoles like Claude or ChatGPT, as Cursor integrates these capabilities seamlessly into the coding workflow. 🔮 Looking Ahead This shift to Cursor is part of our broader strategy to embrace AI-native development practices. I'm excited to share more insights in future posts about how we're leveraging AI to enhance our development processes. I'm curious to hear from other developers: What are your favorite Cursor features or hacks? How has it impacted your workflow? #DeveloperProductivity

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Temporal Technologies has been one of the coolest pieces of infra tech I've used. In this webinar next Tuesday, I'll be doing a deep dive of how we've used Temporal to build out Ampersand's integration engine. Link to register is below.

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