The Internet is so full of good advice, great frameworks, bulletproof methods, brilliant mental models - how is it possible that so many companies (/organizations/teams) still struggle with basic things? Continuous improvement, 4DX (Four Disciplines of Execution), Goldratt’s Theory of Constraints - just these few tools should be more
The true merit, skill, and ability to execute should (in theory) always stand for themselves - in the end, what truly matters is whether one gets the shit done or not. But due to obvious asymmetries in information flow and the sheer size of the global job market, one has to
Do you recall Eliyahu Goldratt’s “Theory of Constraints” (ToC)? It’s a relatively simple (& industry-agnostic) management paradigm focused on workflow efficiency. Simple, yet with massive practical implications. The key theses of this paradigm (that is fully compatible with Systems' Theory) go something
According to the data shared by GitHub (e.g., here ), the programming activity is booming online: not only do we get more developers, but they also create more code. Unsurprisingly, this trend is mostly attributed to the rise of LLMs (in all flavors: from "autocomplete on steroids" to
I have a weird personality - an amalgamate of strongly contrasting characteristics that don’t come together frequently (e.g., intense + analytical, competitive + stoic). Some of them I’ve strongly developed over the years, but there’s a bunch I’d call innate - “analytical” is
Disclaimer: no, this post has nothing in common with the Deutsche Demokratische Republik , but I’ve found the coincidence of acronyms hilarious, so I couldn’t resist the reference in the header image. So don’t worry, no commies were harmed in the making of this article.
Let me start with a short scene that happened some time ago, at the peak of the IT job market’s craziness. We were interviewing a senior candidate with 10+ years of professional experience in serious, enterprise brands: mostly large organizations that do business the “traditional way”
If I had to bet on which graphical meme appears most frequently in my LinkedIn timeline, I'd say it's the one about "servant leadership" . I'm sure you recall it easily (even if it comes in many "flavors" these days): In
That's the second (& final) post in the mini-series. The prior one can be found here . Where are we right now? I've explained why the "depth" of Gen AI usage matters. And I've already covered two of the total three obstacles
There are very few topics online these days that receive as much attention as expected productivity gains due to LLM usage . Some CEOs claim publicly that their companies "write NN% code with Gen AI" or "have reduced headcount by MM% due to AI-powered automations" . Of
Disclaimer 1: This post is 100% inspired by DHH 's recent references to Omakase and the projects that implement this concept: Omarchy , Omakub . So if you believe this article deserves some "kudos", they should primarily go to him - well deserved. Disclaimer 2: I've mentioned this
By mid-2025, it's pretty clear - LLMs are here to stay , whether we like it or not. Yes, there are multiple scenarios where their applicability is still at least questionable, but Gen AI has anchored in software development for good. How so? It shines in scenarios with formal
There's one thing about (professional) communication that I find hilarious. Over the last 15+ years (until approx. 2023), the importance of writing (as a skill) in software engineering craft has gradually declined. I've written about that already - https://no-kill-switch.ghost.io/generation-of-illiterate-
There have been tons of books and articles written on how to be a decent engineering leader. Various authors have been dissecting the role into pieces and atoms, trying to pinpoint the true essence of success in this field. I'm dedicating this blog post to one of such
"Luck" (in an effective & successful software product delivery) is one of those topics I've never dedicated a post to. At least not directly. You may be surprised why I want to change that - isn't "luck" something random, or at most - environment-