Hristo Oskov

In a new blog post, Marc Bowes looks at how updates work in Aurora DSQL, and what it means for scalable schema design. Read it here: https://lnkd.in/gmGEK8Dv A couple take-aways for application builders: - You mostly don't have to worry about hot read keys in DSQL, even in read-write transactions. DSQL can scale out per-key read throughput, and the design requires no co-ordination between transactions reading the same key. (Thank you, MVCC and Time Sync!) - Scalable applications do need to avoid high-contention write keys when doing updates. Writes need to be coordinated and ordered (to implement the I in ACID), which limits per-key throughput. - Most applications can avoid hot write keys with the right schema design. Most applications have already been written this way, because high-contention keys perform poorly on relational databases of all kinds.

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"Because engineers had been through brainstorming and story mapping, they were able to identify the most promising direction and find a way to implement one key piece of it pretty quickly." Want to get your engineers more involved in continuous discovery? Learn how Ellen Juhlin, Senior Director of Product Management at Orion Labs, successfully brought engineers into the discovery process. Key takeaways from Ellen's experience: 🎯 Start by inviting engineers to customer interviews as listeners and note-takers 💡 Include engineers in brainstorming and solution mapping sessions 🗺️ Use assumption mapping to help engineers focus on validating ideas 🔄 Don't worry about following a linear process - iteration is key 🎯 Begin with just one or two engineers rather than the whole team 🤝 Keep engineers connected to business outcomes Check out the comments for a link to the article. ❓ What's one small step you've taken to include engineers in discovery work? Share your thoughts in the comments below.

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Some exciting updates are coming to POS UI extensions 🚀 This summer, we introduced new capabilities: Direct API access, Storage API and new targets on the cart line item details screen. I'm excited to preview even more exciting things coming in 2025-10 and beyond. 🎨 Polaris We're lowering the barrier to making great POS UI extensions by bringing Shopify's single UI framework, Polaris, to POS. Write highly-performant, HTML-like code that works with any framework for any app and any extension surface, including Shopify POS. Preview components and examples in the release candidate documentation: https://lnkd.in/gwciA7CT We understand this is a big change if you've previously been writing your UI code with React. Get ready with our upgrade guide: https://lnkd.in/gjQAY-pf 🗺️ Navigation Extensions can present native detail screens. Present product details, product variant details, customer details, order details, and staff details without retail staff leaving your extension and workflow. Documentation: https://lnkd.in/gvmd6etq 🛒 Cart API We're adding support for subscriptions and making tweaks to how we provide your extension with updates from the cart. Documentation: https://lnkd.in/g3FCe-kX 📚 Documentation improvements We have added a new targets overview page that provides a great overview of available targets with improved descriptions and visuals: https://lnkd.in/g6nDZmu8 🛠️ Developer Experience We're making improvements to the developer experience with better in-app extension development tools, better debugging tools, and hot reloading. Keep an eye on upcoming versions of Shopify POS as we'll be rolling out these improvements into January. 🔮 Next-gen developer platform Shopify has launched a new Dev Dashboard, and we've transitioned apps and dev stores from the Partner Dashboard. Make sure to update to the latest version of Shopify's CLI and check out the latest news: https://lnkd.in/gkGvn7Tz

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A year ago, if you had asked me whether our engineering team at Owner.com was truly adopting AI, not just dabbling, but actually integrating it into how we work, I would’ve said no. We had a few early adopters playing with tools. A few GitHub Copilot installs. Some LLMs used here and there. But nothing close to an org-wide shift. That’s all changed. And while we’re still evolving, I’ve seen what it takes to start moving the whole team forward. First: hire people who are curious. We’ve put deliberate effort into bringing on engineers who are open to trying new things, who see AI as an accelerant, not a threat to quality or process. It’s subtle, but it matters. You can’t force this mindset into a team. You build it from the start. Second: find your champions. Every org has a few folks who tinker in their off hours, who show up to standups with something cool they just built. Identify them. Support them. Make them visible. They’re your internal force multipliers. Then: show up yourself. I’ve made a point of using AI in my own day-to-day work. Whether it’s brainstorming in ChatGPT, automating routine writing tasks, or even building simple prototypes, when the team sees leadership leaning in, it shifts the culture. Boldness is contagious. We’ve also created real space for experimentation. Our internal AI hackathons have surfaced some of the most creative, practical tools we now use: automated code generation for straightforward tasks (more on this exciting stuff in a future post), auto-generated tests, and internal bots. Not all of them made it to production, but they created momentum. And that momentum changes everything. On measurement - we’re still figuring it out. Traditional metrics like velocity and story points fall short. We’ve started thinking about time saved, friction reduced, and AI-assisted workflows adopted, but I’d be lying if I said we’ve nailed it. It’s an active conversation, and we’re learning as we go. Throughout it all, we’ve kept our engineering guardrails. Code reviews still matter. Design quality still matters. AI is there to raise the ceiling, not lower the bar. This isn’t about chasing hype. It’s about giving your team better tools, faster feedback, and more creative freedom. The orgs that figure this out now are going to be miles ahead six months from now. There’s no playbook yet. But that’s the opportunity: you get to write your own. At Owner.com, we’re not waiting for someone else to figure it out. We’re leading from the front and taking the future into our own hands.

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This semester, I’ve been assisting the 5th-grade class at Palo Alto Unified School District (where my daughter is a student) in learning Scratch. Interestingly, several kids have expressed that Scratch doesn’t feel as “cool” as Python, which I taught them last year in 4th grade. Their main complaint? Scratch lacks actual code. While exploring alternatives, I came across an online teaching platform: Go+ Builder. It introduces a variant of the Go programming language, allowing students to drag and drop control flows into an editor window—bridging the gap between block-based and text-based coding in an intuitive way. https://lnkd.in/dBHN27YP If you’re involved in teaching programming to young learners, I’d love to hear your thoughts on similar tools! 🚀

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A typical example of today’s shallow GenAI integrations, more marketing than meaningful help. The same goes for the “agent” buzzword we are overusing. If GenAI or an agent truly improves the experience, it should be obvious from the interaction. The best tech works quietly in the background, solving real problems without needing a label.

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I am glad folks at Cypress.io read my blog post "Pick E2E Tests To Run Using AI Summaries" and now are showing test summaries on dashboard. Next thing they will probably suggest tests to run. You can easily derive these text descriptions. https://lnkd.in/gUh2Srtm 

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In 2008, Brian Chesky , Joe G. , and Nathan Blecharczyk were struggling to pay rent in San Francisco. Instead of giving up, they got creative. A design conference was coming to town, and hotels were fully booked. So, they bought a few air mattresses, set up a simple website, and offered “Air Bed & Breakfast” to attendees. What started as a small idea to make ends meet turned into Airbnb, a platform that revolutionized travel and hospitality. But success didn’t come easy. Investors rejected them over 7 times. People doubted that strangers would stay in someone’s home. They even sold custom cereal boxes to keep their business alive. Fast forward to today: Airbnb is worth over $100 billion, with millions of hosts and guests worldwide. ✅ Lesson? The best ideas often start with a problem you personally face. If you solve it well, the world might just need it too.

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