Alex Unger

The new Cluecumber report library version 3.12.0 for Cucumber json reporting is out. This release brings updated dependencies, bug fixes and fresh new features for rerun test scenarios and exception display. https://lnkd.in/evr2-nZR

10

We just shipped something small, but important, for ZurichJS Conf. You can now report issues directly on the website. Typos. Confusing UX. Performance hiccups. Unclear information, for example around CFP deadlines. Anything that feels “off”. We are building this conference in public. That means the experience should not be dictated only by us. It should be shaped by you. The goal is simple: Make the website and the event experience as clear, smooth, and intentional as possible. If something is confusing, that is on us. If something breaks, we want to know. If something can be better, we are listening. There is now a dedicated “Report an issue” entry in the footer. Submit feedback, and we will review it personally. We are making incremental improvements every week. Your feedback directly influences what gets fixed next 💛 PS: We also shipped a few hidden Easter eggs across the site 😉 If you find them, you might unlock a secret ticket discount. No guarantees. This conference is community built. Help us refine it. #ZurichJS #ZurichJSConf #JavaScript #WebDevelopment #Frontend #React #TechCommunity #CallForPapers #ConferenceLife

16

3 Comments

𝗧𝗵𝗲 𝗯𝗲𝘀𝘁 𝗴𝗶𝗳𝘁 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗴𝗶𝘃𝗲 𝗮 𝘀𝗽𝗲𝗮𝗸𝗲𝗿 𝗶𝘀𝗻’𝘁 𝗮𝗽𝗽𝗹𝗮𝘂𝘀𝗲, 𝗶𝘁’𝘀 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸. After my sessions at the International JavaScript Conference Munich, I got the feedback summary this week. Both talks scored really well: 🟩 𝗖𝗮𝗰𝗵𝗶𝗻𝗴, 𝗣𝗮𝘆𝗹𝗼𝗮𝗱𝘀, 𝗮𝗻𝗱 𝗢𝘁𝗵𝗲𝗿 𝗗𝗮𝗿𝗸 𝗔𝗿𝘁𝘀: 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗶𝗻𝗴 𝗨𝗫 𝗶𝗻 𝗦𝘂𝗯𝗼𝗽𝘁𝗶𝗺𝗮𝗹 𝗖𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻𝘀 • Quality: 4.67 / 5 • Knowledge: 5 / 5 • Comment: “A bit overloaded with information.” 🟦 𝗙𝗿𝗼𝗺 𝗙𝗿𝗮𝗴𝗶𝗹𝗲 𝘁𝗼 𝗙𝘂𝘁𝘂𝗿𝗲-𝗣𝗿𝗼𝗼𝗳: 𝗦𝗼𝗹𝘃𝗶𝗻𝗴 𝗪𝗲𝗯 𝗠𝗼𝗻𝗲𝘁𝗶𝘇𝗮𝘁𝗶𝗼𝗻 • Quality: 5 / 5 • Knowledge: 5 / 5 It’s always nice to see high numbers; it means the work, preparation, and energy paid off. But the most valuable part was that small comment: “A bit overloaded with information.” I actually love that. It’s true, I tend to pour a lot into my talks because I want people to walk away with something practical. The tradeoff is that sometimes it becomes dense. That single line says more to me than a perfect score ever could. It’s what helps me get better. Feedback like this is 𝘂𝗻𝗱𝗲𝗿𝗿𝗮𝘁𝗲𝗱. Most people don’t realize how little of it speakers actually get after a talk. You stand on stage, share your work, and often walk away without knowing what really landed and what didn’t. When someone takes 20 seconds to write one honest sentence, it gives you a mirror. It shapes your next talk, your style, your pacing, and your focus. So if you’ve ever attended a meetup, workshop, or conference talk, take that moment to leave feedback. Whether it’s praise, confusion, or critique, it all helps. And to everyone who came to my sessions in Munich, thank you. You showed up, listened, asked, challenged, and cared enough to respond. That’s what makes these communities worth being part of. #IJS #PublicSpeaking #Conferences #EngineeringCulture #Feedback #ContinuousImprovement #Learning #DeveloperCommunity

21

3 Comments

What can one developer build in three weeks? At the end of December, I suddenly had time. A lot of time. So I ran an experiment: let Claude Code off the leash and see where it takes me. I didn't expect it to take me to LinkedIn. 🙃 In three weeks, it wasn't just a product that emerged. It was an entire ecosystem: API Mapper (an extension for WordPress and Joomla), plus the complete infrastructure. Website. API system. Console dashboard. DevTools. Documentation. Marketing tools. 26 services working together. And here's the wildest part: there's a self-healing system built in. When bugs appear in customer environments, they get automatically detected, fixed, and shipped with the next release. An AI-powered autoloop that keeps improving itself. Here's the thing. In 30 years of working with websites, tech, and every layer in between, I always avoided code. Code was machine language. And I'm human. Now I have a tool that fills this last gap. And you can bet I'm pretty happy about it. For the first time, I can combine everything I've learned over the past decades with new technology and see where it takes me. The song in the video is "Three Weeks", a farewell to the old days when we still worked the traditional way. There's a certain irony in that. I'm grateful this door opened. I've accepted this new reality. 😄 Now I'm happy to talk about API Mapper (which is turning out really great 🚀) and WootsUp!? in general and about how to use AI tools in ways that actually move you forward. Not as a toy. As a partner. Welcome to my journey.

13

3 Comments

if you think #Rust is still a niche programming language only for hobbiest, you need to catch up on the news. Ubuntu is replacing the `sudo` implementation with a Rust version. You cannot go more mainstream and security critical than this!

31

1 Comment

🎙️ New episode with Sebastian Gerhardt is live. In this episode of Build by People Leaders, I speak with Sebastian Gerhardt, founder of Flee, about improving developer experience in modern software organizations. One key idea: Developer productivity cannot be measured by output alone. We explore: • Why output-based metrics often fail engineering teams • How organizational structure and team culture shape performance • The role of psychological safety in high-performing teams • How feedback systems and survey-driven insights reveal hidden friction • Engineering leadership in remote and distributed environments For CTOs and engineering leaders, this conversation offers practical insights on identifying friction points, fostering open communication, and building resilient, high-performing teams. 🎧 Listen here: https://lnkd.in/dKV3ZtFW

3

“I ship code I don’t read”. This is not revolutionary. It has to become the norm with AI coding. 👩‍💻 Human in the loop to read code does not scale with AI generated code. 🤷🏽‍♀️ If AI is writing code, and reading code, does it even need to be human readable? ✅ Focus has to shift to ensuring correctness and completeness of code.

1

$2,407 USD/month is $12,884 per year… That’s almost double the federal minimum wage at 40 hrs/wk for 52 weeks (USD15,080), even in a region with high labor prices like the US. While it’s incredible that these tools are working, I cannot help but feel a lot of this spending is misguided. Especially for something like LLM tokens for development, for pre-made software like Claude Code? It’s not Capex, it’s Opex. If you are 1. spending so much on tokens that it would be competitive to simply hire an offshore developer 2. you aren’t developing any infrastructure beyond committing the generated tokens (using off-the-shelf software), and 3. aren’t using any capabilities unique to LLMs over humans, then: The value you are getting is largely an expensive learning experience, and you’re likely incurring significant unnecessary tech debt. Perhaps this is fine. Much more worryingly, if you are in the business of training base models which rely on this class of spending, you are living on borrowed time, facing an existential risk of getting outcompeted from below by cheaper models, especially open source. It's a fools errand to assume that you can train a huge model on Anna's Archive and the like, yet somehow slow down getting distilled. How long will investors be willing to put up jaw dropping sums of capital before seeing any return, all to risk being #2? I predict much more innovation in smaller, cheaper models, and I think it's far more likely that ternary models, distilling techniques, and stuff like RKWV will pay off. In fact, while writing this post, I found out that RKWV has *already* made it into Microsoft Office! I wouldn't want to be the one financing GPUs or RHLF for large models. While this should not be interpreted as a comment on other business going on at Apple, I should say that I largely agree with their assessment to stay out of the large base model race, for exactly this reason.

2

Essential SRE Articles: The Essential Knowledge You Need as an SRE by Marcel Koert feels less like a textbook and more like a trusted field guide for engineers working in the real world of Site Reliability Engineering. Written by a practicing SRE, this book speaks directly to the moments that matter most—between incidents, during on-call rotations, and in the quiet minutes after a production fire has been put out. Instead of idealized, Google-scale scenarios, Koert starts with the reality most SREs know well: legacy systems, partial migrations, political constraints, and monitoring that’s never quite perfect. The book focuses on what actually makes an SRE useful—error budgets, service levels, monitoring, capacity planning, disaster recovery, infrastructure as code, and modern reliability design patterns. What truly sets this book apart is its emphasis on human factors. Cognitive biases, communication failures, and decision-making under pressure are treated as first-class reliability concerns, not afterthoughts. The structure is intentionally practical, with short, focused chapters designed for quick reading during a busy day. With an entire section dedicated to AI and modern prompting techniques for SREs and DevOps engineers, this book feels current, honest, and deeply usable. A highly recommended read for anyone serious about building reliable systems—and becoming a more effective SRE. Book link: https://a.co/d/68qhzdf #SiteReliabilityEngineering #SRELife #DevOpsEngineering #TechBooks #ReliabilityEngineering

1

Your Gradle knowledge is a hidden gold mine. 🏗️ Android Developers get shortlisted when they prove build time reductions. 🏎️ Ghosting hurts your career momentum. 📉 The frustration of silent applications is real. 😤 The market is unforgiving right now. 🧊 You deserve a clear path forward. 🛣️ Your pipeline logic is currently a liability. ⚠️ It must capture the margin. 💰 The job hunt is tough today. 🕒 I feel your exhaustion from waiting for builds. 😫 It is draining to solve scripts without credit. 🏗️ Your profile is a boring list of versions. 📄 Most mobile leaders fail the first scan. 🔍 They lack commercial bite. 🦈 You list: Gradle, Groovy, Kotlin DSL, CI/CD, and Build Scans. 🛠️ Recruiters hunt for a Productivity Architect. 🏗️ The board ignores your dependency tree. 🚫 They want to know if you lowered costs. 📉 They want to see if you de-risked the release. ⚡ If you only list tools, you look average. 😐 You fail to look like a strategic architect. 🧠 This keeps your salary stuck. 🛑 Others land the Senior Android roles instead. 🏆 Does your resume prove your scripts earn money? 💸 Act fast to claim your seat. 🏃 The elite platform mandates are closing soon. 🔒 Recruiters scan in seconds for impact. ⏱️ If it is hidden in jargon, they move. 📤 Stop being a script runner. 🏃 Start being a Revenue Accelerator. 🚀 The VIP Fix for your Summary: ↳ 📌 Link Solving Momentum to build speed. Resolved configuration-on-demand leaks to shave 5 minutes off CI. 🏎️ ↳ 📌 Prove Resource Frugality through Cache logic. Optimized remote build caching to slash compute costs by 30%. 📉 ↳ 📌 Detail Reliability ROI for capital preservation. Architected convention plugins to reduce build script maintenance by 40%. 🛠️ ↳ 📌 Expose Efficiency Logic in the dependency chain. Implemented version catalogs to cut library conflict resolution by half. 📈 ↳ 📌 Map Throughput Velocity to team delivery. Refined incremental builds to increase daily developer commits by 15%. 🚀 P.S. Follow @JobLanderz.VIP for more Android career hacks. 📑 #AndroidDev #Gradle #BuildEngineering #DevOps #JobLanderzVIP What matters more: 100 percent Kotlin DSL migration or a 40 percent reduction in clean build time?

⚡ Slow test suites drain focus — and they don’t have to. In this session, Sebastian Bergmann shows how smarter test design and targeted optimisations can dramatically speed up your PHPUnit runs. You’ll explore approaches that keep pipelines responsive, reduce waiting time, and bring testing back to being a productive part of your workflow instead of a bottleneck. IPC | 📍 Berlin | 📅 June 8 – 12, 2026 🎓 All about the session: https://lnkd.in/dwXYNqCu #IntPHPcon #PHP #PHPUnit #Testing #Performance #DevOps

9

3 Comments

Accidental quality. That's what I call the hidden trap in traditional example-based tests. In my recent talk at Techcamp Hamburg, I spoke about how enumerating test cases creates a dangerous illusion of safety, while the real bugs hide in the blindspots we never think to check. Property-based testing flips the narrative: it searches for bugs instead of just testing for them. If you have 1000 users and you are writing 50 handpicked test cases, are you sure you are not missing any particular use-case? https://lnkd.in/eTyjrPPi

19

Everyone loves the idea of “move fast and build.” But here is the reality we see with many teams: → Features get shipped quickly, but without long-term planning. → Tech debt piles up quietly in the background. → Scaling becomes painful, costly, and sometimes impossible. At EnqCode, we often help clients untangle this. The most common hidden costs we find are: ・Re-engineering poorly designed modules just to handle growth. ・Fixing security oversights that should have been caught early. ・Migrating from a “quick fix” tech stack to one that can actually scale. Building fast isn’t wrong but building fast without direction is expensive. The smartest teams balance speed with scalability, and treat tech debt as a real cost, not an afterthought. #SoftwareDevelopment #Scalability #CustomSoftware #SaaSDevelopment #Technology #Build #TechDebt #DigitalTransformation #EnqCode

3

Why “Username Already Taken” Is a Massive System Design Problem When you sign up for a new app and see: “Username already taken.” It feels like a tiny inconvenience. Behind the scenes? It’s a billion-scale system design challenge. At small scale, you could check a database directly. At large scale, that would cause: • High latency • Database bottlenecks • Massive unnecessary load • Poor user experience So how do companies handle this? They layer systems. Not one data structure. Not one database query. A layered architecture. Here’s what actually happens. First → A load balancer routes your request to the closest data center. Then → The system checks a Bloom filter. A Bloom filter is a probabilistic data structure designed for one purpose: Fast membership checks with minimal memory. It works using: • A bit array • Multiple hash functions When a username is added, it’s hashed multiple times and specific bits are set to 1. When checking a username: If any required bit is 0 → the username definitely does not exist. If all bits are 1 → the username might exist. This is the key: Bloom filters never produce false negatives. If they say “not present,” you can trust it. But they can produce false positives. That means they might say “this username might exist” even when it doesn’t. And that’s okay. Because a false positive only triggers a deeper check. It does not break correctness. It simply pushes the request to the next layer. That next layer? An in-memory cache like Redis or Memcached. If the username was recently checked, the cache responds in microseconds. Cache miss? Only then does the system query a distributed database like: • Cassandra • DynamoDB • Spanner These databases partition data across thousands of machines using consistent hashing to ensure fast lookups at massive scale. If username suggestions are needed, tries (prefix trees) are used. They allow prefix lookups in O(m) time — based only on string length, not total dataset size. For sorted indexing and exact lookups, B+ trees are often used underneath. The real insight? It’s not about choosing the “best” data structure. It’s about combining: • Probabilistic filters (Bloom filters) • In-memory caching • Distributed storage • Intelligent load balancing To make something feel instant. The next time you see “Username already taken” Remember: That response likely passed through a Bloom filter, a cache layer, a distributed database, and multiple load balancers — All to answer you in milliseconds. Small UX message. Massive engineering underneath. #SystemDesign #DistributedSystems #SoftwareEngineering #Scalability #BackendEngineering

11

❌ More tests don’t always mean more quality. ✅ The real power comes when tests compound, not collide. In his InnovateQA Seattle 2025 session, Ben F. (CEO of LoopQA) showed how AI is reshaping quality engineering: 👉 Test layers should build on each other—not duplicate effort. 👉 Flaky data is the enemy; AI-driven factories and fixtures can stabilize tests. 👉 LLMs and tools like Cursor/Playwright aren’t job killers—they’re amplifiers that free engineers to focus on design and strategy. His key point: QA’s future isn’t about chasing more tests, it’s about smarter layering, cleaner data, and AI as a force multiplier. Watch the full recording here: https://lnkd.in/es5zGqJ7 💭 What’s the biggest “collision” you’ve seen in your test strategy? #InnovateQA #TestAutomation #AIinTesting #QualityEngineering #Cursor #Playwright

3