Wojciech Pasternak

NEVER deactivate buttons: In every user test I carry out, where buttons are deactivated because the customer has not filled in all information, this causes much confusion. Why? Because the customers get no help when they click a deactivated button--they get stuck. If buttons always are active, then the customers get a help message that guides them through the page. This converts much better. I have tons of data to support this tip. #ecommerce #cro #ux #design

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🔥 NUMA: The Hidden Latency Penalty in Multi-Socket Servers When we talk low-latency C++, we often obsess over branch predictors, inlining, or cache lines. But in multi-socket production servers, a bigger invisible cost lurks: NUMA (Non-Uniform Memory Access). 💡 What’s going on under the hood? • Each CPU socket has its own local memory. • Accessing memory on your own socket is fast. • Accessing memory on the other socket can be 2–3× slower, since it travels across the interconnect (Intel UPI, AMD Infinity Fabric, etc.). Now imagine a thread pinned to Socket 0, but allocating memory the OS placed on Socket 1’s NUMA node. 👉 Every access now pays a remote memory penalty — adding tens of nanoseconds per load. 👉 In a trading engine, that’s the difference between hitting the market first… or missing it entirely. ⸻ ✅ NUMA-Aware Best Practices: • Thread Affinity: Pin threads to cores deliberately. • NUMA-Aware Allocation: Use numactl, libnuma, or OS APIs to control where memory lives. • Partition Work: Keep data + compute on the same socket. • Socket Discipline: Some workloads isolate latency-critical tasks to a single socket to keep memory fully local. ⸻ 🔑 Key Takeaways • NUMA effects don’t show up on dev laptops — but they do on real multi-socket servers. • Cross-socket memory access can silently add tens of nanoseconds. • Profiling and locality awareness are essential to keep latency deterministic. 👉 Have you profiled your system for NUMA penalties? What’s your strategy — pinning, binding, or redesigning the workload? #Cplusplus #LowLatency #HFT #NUMA #PerformanceEngineering #SystemDesign #TradingSystems

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was at OpenAI hq yesterday and got to talk with their head of product about the new agentkit 🤯 a lot of people think this kills zapier (i even thought so at first). it doesn’t. agentkit is for devs, not no-coders. it’s about putting ai inside products, not automating workflows. this makes it easier for teams to build agents that live inside their own apps, not connect tools together. so yeah, this isn’t about replacing zapier. it’s about replacing ui. #ai #openai #chatgpt #agents #startups #developers

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For years, we've had a front-row seat to the incredible discussions happening in software quality. We've heard leaders navigate the shift from just finding bugs to building better experiences, faster and more intelligently. But these game-changing conversations usually happen behind closed doors. We wanted to change that. That's why I'm thrilled to launch BrowserStack Talks, our new podcast. We're opening the mic to the brightest minds in our industry for real talk and authentic conversations about what it truly takes to build smarter, better software. We're going live today with our first four episodes, featuring an incredible lineup: - Rachel Kibler, Senior Quality Engineer @ SeekWell - Rosie Sherry, CEO & Founder @ Ministry Of Testing - Simon Prior, Head of Quality Engineering @ Goodnotes - Kat Obring, Quality Leadership Coach @ Skiller Whale I'm so excited to learn alongside all of you and for the new ideas this will spark in our community! Listen to the first episodes and subscribe to join the conversation: https://lnkd.in/dE_tU-if

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We’ve spent the last year watching engineering teams invest heavily in AI tooling to help them write better code faster. But the real pressure is downstream: review, testing, release, and that's where Platform and DevEx teams can make the biggest impact on their developers. Today, I’m proud to announce major updates to LinearB’s AI Productivity Platform. It brings together three capabilities built for the teams that own delivery: MCP Server: Ask delivery data questions in plain language and get clear, answers. AI Insights Dashboard: Understand which tools are being adopted (down to the repo) and how they affect commit patterns, PR volume, and delivery speed. Supports more tools out of the box than any other technology. See partial list below. Developer Surveys: Layer in human signals: how developers feel about the changes, the tools, and workflows. Where is trust high? Where is friction compounding? Our new Essentials offer starts at $19/contributor/month, includes 1,000 credits per seat, and is priced to scale across teams. A PR with multiple automations—like AI PR descriptions and AI code review—only uses 100 credits. Teams can also choose from Managed Mode (fully hosted) or Self-Managed Mode (which gives you granular control). If you lead DevEx or Platform, this is built for you. It offers visibility, automation, and powerful feedback loops without waiting for quarterly retros or another custom dashboard project. AIDER, CodeRabbit, GitHub Copilot, Atlassian Code Reviewer for Bitbucket, OpenAI's Codex, GitLab Duo, Qodo, Atlassian Rovo, Cursor, Google Jules, Sourcegraph, Cognition Devin, Graphite, Tabnine, Anthropic Claude Code, Greptile, Tusk, CodeAnt AI, Google Gemini, Korbit AI, Windsurf

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