Sarah Calande

Proud of our team and how hard we have been working to create an API that enables AI agents to make purchases. We are getting closer to making universal checkout a reality, focusing on security, performance, and scale. If you are curious about how we are tackling this problem, you can read our white paper here 👇🏾 rye.com/whitepaper

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The harsh reality about job searching as an experienced developer: Your years of experience can actually work against you. Here's why: • Companies assume you're "overqualified" for roles you'd love • Startups think you'll be too expensive or inflexible • Your resume gets filtered out because you're "senior" but the role says "mid-level" • Ageism is real in tech (even if no one talks about it) But here's what I've learned helping 100+ developers navigate this: The ones who succeed flip the script. Instead of hiding their experience, they leverage it strategically. They don't just say "I have 10 years of experience." They say: "I've seen codebases grow from prototype to IPO." "I've made every scaling mistake so your team doesn't have to." "I can mentor your junior developers while shipping features." The difference? Value over years. Impact over tenure. Results over resume bullets. Your experience isn't a liability. It's your competitive advantage. But only if you position it right. Here's how to reframe your experience: • Don't apologize for being senior • Show how you've evolved with technology • Demonstrate you can still be hands-on • Prove you're invested in continuous learning The market needs experienced developers who can: Think strategically AND code tactically. Mentor others AND deliver features. See the big picture AND sweat the details. That's you. Now own it. How are you positioning your experience as an asset, not a burden?

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If your agent is tasked with ideation and says follow k8s designs because they are "used at scale", your next reply should be. "your context is corrupted, please give me a restart prompt for a new session" I'm not really hating on k8s as much as the idea of using hype words as a sort of design rationale. When I see things like this, it is the same as an agent hitting a hard bug and trying to convince me to skip troubleshooting. Both are mentally lazy, and that's neither ideation nor why we turn to "artificial intelligence". Even if you found a design in k8s, and it was actually relevant to whatever you tasked the agent to research, the authors might not agree with it anymore. Things change, and copy/pasting a pattern randomly based on star count again.. isn't ideation, and not listening even to feedback on that design.. This is just not critically thinking. Again, not really "artificial intelligence" While agents are good at research, they require strict direction if your design needs to hold water. You need to force them into a box with relentless clarity that no aspect of the decision can be unexamined. You might need to restart the session a few times, and that's the reality of it. Sometimes the work is indeed worth it, especially if you are good at multi-tasking and have a good eye for BS. For me, yep. If I ever see "at scale", basically in any response, I already know the agent has entered lazy mode and time to restart.

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It's intriguing that every digital nomad community has plenty of tax-optimization advisors but very few healthy relationship role models. I'd argue that for most cases we don't need gurus, coaches, and therapists. We need meaningful phone conversations and cheerful in-person banter. It works in every destination.

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What does it take to stay relevant as a software engineer in an industry that never stops evolving? In our latest Overcommitted episode, Bethany Janos, Erika Eggemeyer and I sat down with Thomas Dohmke - former GitHub CEO, current startup founder, and developer at heart - for an honest conversation about growth, learning, and navigating the rapid pace of tech. Key takeaways from our conversation: → The paradox of developer happiness: "The happiest day is when you start a new project. Then it's all downhill from there." Thomas shares why passion is what keeps you going when the initial excitement fades. → On feeling stuck: Don't worry as much as you think you need to. Most people aren't judging you nearly as harshly as you're judging yourself - and AI tools can help you ask the "dumb questions" without fear. → Learning never stops: From COBOL mainframes to AI agents, the only constant is change. Thomas breaks down his approach to staying current without drowning in information overload. → Career pivots require trust: Sometimes the best decisions are counterintuitive - like leaving a director role at Microsoft to become "VP of Special Projects" at GitHub (a title that meant nothing at the time). → AI is our "before and after" moment: Just like the personal computer, the internet, and mobile transformed how we work, AI is fundamentally reshaping software development. We're living through the revolution right now. Thomas shares his journey from coding on a Commodore 64 in post-wall Berlin to leading one of the most important platforms in tech - and what he's building next. Listen here, or wherever you get your podcasts: https://lnkd.in/gBHvcaSK Whether you're early in your career or a seasoned engineer, this conversation has something for you. #SoftwareEngineering #CareerGrowth #AI #TechLeadership #GitHub

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Google Stitch just dropped a major update. I tried it so you don’t have to waste 2 hours figuring out what it’s actually good for. As a Fullstack Frontend Developer, here’s my honest take.😎 Every time a new AI design tool drops, Twitter goes crazy: “Designers are cooked!” “Frontend devs are done!” TLDR: Nothing is cooked. Not even close. But here’s what most people get wrong, they either overhype it or trash it completely. My approach? Neither. I ask one simple question: “How can I plug this into my existing workflow to save time?” So I stress-tested the new Stitch. Here’s what I found: 🧠What’s actually good: → The infinite canvas is a game-changer. Think Figma meets AI. You can spin up multiple agents in parallel, one generating a hero section while another creates SVG illustrations. No more back-and-forth. → Design Systems out of the box. Pick your colors, typography, spacing, and it stays consistent. Not perfect, but a solid starting point. → Variants. Ask for 3-4 variations of any component and iterate visually before writing a single line of code. This alone makes it worth exploring for ideation. → SVG export workflow. I generated an isometric illustration in Stitch, exported the SVG, dropped it into my React codebase, and animated it with Framer Motion, all in under 10 minutes. That same task used to take me an hour in Figma. 👎🏻What still needs work: → Full landing pages? Still looks painfully AI-generated. Generic gradients, no real design taste, poor instruction-following (I asked for box shadows three times, it ignored me every time). → The UX is overwhelming. Too many things happening everywhere. I genuinely got confused about what I was supposed to do next. → It’s not replacing your design skills anytime soon. The output is Tailwind UI circa 2021, functional but forgettable. ⭐️The real takeaway: Stop asking “Is this tool going to replace me?” Start asking “What’s the one annoying task this tool can handle for me?” For me, that’s generating custom SVGs, exploring component variants quickly, and rapid ideation on an infinite canvas, not building production-ready pages. AI tools are ingredients, not the chef. Your taste, your prompting skill, and your design sense are still what make the final product worth shipping. What’s your approach when a new AI tool drops? Do you immediately try to build a full project, or do you look for specific workflow wins?🤔 #google #stitch #googlestitch #figma #ui #ux

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