Jan Peer Stöcklmair

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

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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

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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!

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🚀 Two days before WhatTheStack kicks off, I’m running a crash course in building apps that survive the real world. Real-World React: The Architectural Playbook for Performance, Resilience & Scalability is built around React and Next.js as our shared language, but it’s not exclusive. I’ve had Vue, Svelte, and Angular devs attend, and most of the concepts we’ll cover are framework-agnostic and apply to any modern frontend stack. We’ll dig into: - Architecture patterns that implicitly boost performance - The real story behind React reconciliation (and anti-patterns to avoid) - Resilience engineering for modern frontends - DORA metrics and delivery velocity at scale - Building post-deployment confidence so you can ship without fear This isn’t about pixel-perfect UIs, it’s about patterns, decisions, and trade-offs that keep apps fast, resilient, and scalable when they’re serving millions, not just running locally. 🎯 If you work in frontend and want to level up your architecture game, this is for you.

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Graph (Tree) of Notes as a Tool for Structuring Thoughts - Canvas Mode I recently discovered that Obsidian has a Canvas feature for creating connected graphs of notes. This caught my attention since I’ve been using the ZettelKasten system in Obsidian for over three years. Until now, I mostly relied on the Graph View and somehow avoided Canvas. With Canvas, it’s possible to highlight specific parts of your note base and build clearer trees (acyclic note graphs). These structures can then be used together with an AI agent to generate articles. Here how it looks:

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🛠 Is software craftsmanship still relevant? This week on Modern Software Engineering, Emily Bache reflects on the last great idea from the software craftsmanship movement - and why it still matters today. ✅ Clean code vs. fast delivery ✅ Idealism vs. practicality ✅ Professionalism in a changing landscape If you care about writing better code and being a thoughtful developer, this one’s for you. 🎥 Watch now: https://lnkd.in/eWz2udEX #SoftwareEngineering

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CSS Advent Calendar - Day 9 – Container Queries Container Queries are the feature we missed for years. With them, components become truly independent – no longer oriented to the viewport, but to their own context. This fundamentally changes the architecture of frontends. Responsive design becomes more local, modular, and scalable. Container Queries are not just another feature. They are a turning point. #CSS-Advent-Calendar #CSS #Web-Development https://lnkd.in/e_dZU97d

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🚀 Today in Berlin at Agile meets Architecture: Kenny (Baas) Schwegler and Evelyn van Kelle are presenting: “Debiasing Your Software Design Decision-Making” 👇 https://lnkd.in/d6Zb_NuH Are your software design decisions driven by bias or by deliberate choice? Kenny and Evelyn invite you to move from a reactive, bias-driven approach to a deliberate, resilient, and more effective design process. This talk applies cutting-edge research from behavioural economics directly to software architecture and development, with or without AI. 🎯 What you’ll take away: - Move beyond awareness of biases - A practical five-step checklist to systematically ‘debias’ your design decisions - Tools to build better software and better decision-making habits across all your technical work. ✨ Plus: don’t miss the chance to continue the experience in person at the Collaborative Software Design Workshop in Amsterdam, led by Kenny and Gien Verschatse. 👇 https://lnkd.in/dvzA-ZiR

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Wanna learn more about the defer block? 💡 💻 During this year’s Angular.love Spring Camp, GDE Enea Jahollari gave a talk showing @defer from a slightly different angle. In this talk, Enea presented real-world examples that demonstrate the need for the defer block in Angular. Watch if you want to learn: 🔹What are the @defer triggers 🔹How to break the defer block 🔹How to optimize it Watch iit here: https://buff.ly/Ye2U9pf #angular #deferblock #angularlove #frontend

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🎙️ 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

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🥘 TypeScript can be a feast. Or a food fight. On today’s #GOTOpodcast, Stefan Baumgartner joins Peter Kröner to serve up lessons from the TypeScript Cookbook. Instead of cramming in every advanced feature, Stefan shows why the best devs keep it simple: 🍴 Use type annotations only where they count 🚫 Skip enums when cleaner alternatives work better 🏗️ Know when classes help—and when they just get in the way 🔍 Focus on what’s happening behind the scenes to make smarter choices 🎧 Listen in: https://lnkd.in/g_UDEnR

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“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.

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We walked, we talked, and realized: We never got promoted to Senior 😬 This week, we’re diving deep into Engineering Career Ladders and why it's hard to get promoted. Also, Philipp kicks off a brand new segment: Frontend Drama of the Week. And also in this episode: - 🐍 Oban's Python background job library - 🔔 Why Postgres LISTEN/NOTIFY is usable again - 🚀 Postgres sharding solutions from PgDog, Supabase and PlanetScale Link to the episode is in the comments!

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$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.

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One of the most underrated software projects these days: JReleaser. If you need to release your software (Not only JVM - also Go, Kotlin and any other language) to a public repository - then JReleaser is your friend. It makes releasing your software to brew, git, deb and more a joy. Great work by Andres Almiray! More over here: https://jreleaser.org/

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Running LLMs directly on mobile devices sounds appealing. But what actually works for React Native today? At the React Universe Meetup with Zalando in Berlin, Artur Morys - Magiera will walk through the practical realities of on-device LLM inference in React Native. The talk covers performance and efficiency, end-user constraints, and what developers need to consider to make this production-ready. If you’re exploring AI features on mobile and want a realistic view of the tradeoffs, this session is for you. https://lnkd.in/dYRMYhX8

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🔐 Single Sign-On (SSO) looks simple to users — but it’s one of the most important trust flows in modern systems. From the user’s perspective, SSO feels like: 👉 log in once 👉 access multiple apps 👉 move faster with less friction But behind that convenience is a carefully orchestrated exchange between: the user the service provider the identity provider This visual explains that flow well: The user requests access The app checks for an active session If none exists, it redirects to the identity provider The user authenticates Credentials are verified A token is issued Access is granted — and reused across connected services Why SSO matters ✅ Better user experience One login can unlock multiple services. ✅ Centralized identity management Authentication is handled in one place, not scattered across apps. ✅ Stronger security controls It becomes much easier to enforce: MFA conditional access centralized session management identity-based monitoring But here’s the tradeoff SSO improves usability and control, but it also makes the identity layer more critical than ever. If the identity provider is weak, everything connected to it inherits that weakness. That’s why SSO should never be treated as just a convenience feature. It’s a security architecture decision. My takeaway SSO is really about balancing two things: less friction for users and stronger trust enforcement for systems When implemented well, it does both. 💬 What do you think is the bigger SSO challenge in practice: integration complexity, token/session security, or identity-provider trust? #SSO #IdentitySecurity #IAM #Authentication #CyberSecurity #ZeroTrust #AccessManagement #SystemDesign #CloudSecurity

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If you’re looking to grow as an engineer beyond just writing code, Arek's latest post highlights three newsletters that deliver massive ROI. Strong recommendations 👇

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