Tomáš Neubert

Devs, we come bearing only good news  🎉 Just launched: monday dev × Cursor integration! We'll let Andrew Milich, Head of Engineering at Cursor, explain why this changes everything: "With the monday dev Cursor extension, developers can manage their tasks directly in Cursor without switching tools. All the surrounding context, from code history to team activity, flows into the editor, making AI-generated code more accurate and useful. Developers stay in control, while teams move forward with less friction."  👉 THIS is the integration developers have been waiting for.

284

38 komentářů

Java 25 comes with great features and enhancements, including making the language more succinct and beginner-friendly. This is a fully valid Java program. No imports. No method modifiers. No unneeded arguments. And you can run it directly via the "java" CLI. No extra compilation steps. #Java Java

483

17 komentářů

We’re excited to share that the official PHP MCP SDK is now in the works! 💫 The PHP Foundation has partnered with Anthropic’s MCP team and Symfony to build a framework-agnostic, production-ready SDK the entire PHP ecosystem can rely on. https://lnkd.in/ejN9K2s9 - Maintained by the Symfony team. - Joined by Kyrian Obikwelu, who brings his experience with MCP libraries. - Open for contributions from the community. ⭐️ Star the repository: https://lnkd.in/etEPQU5b

1 525

43 komentářů

In modern software development, we don't just guess if our code works. We write unit tests, run integration tests, and build CI/CD pipelines. We replaced manual guesswork with rigorous, automated validation. So why are many of us still in the "guesswork" phase with LLM prompts? The common workflow is a manual loop : tweak a prompt, test it, eyeball the result, and tweak it again. This is artisanal, slow, and doesn't scale. A prompt that works today might break tomorrow with a slight model update. It’s not an engineering discipline. The paradigm shift we need is Systematic Prompt Optimization. This is the move from "prompt art" to "prompt science." It’s about treating a prompt not as a magic incantation, but as a key component of a system that can be algorithmically tested, measured, and improved. The framework for this is surprisingly simple and powerful: 1./ Hypothesis (Your Base Prompt): Your initial, best-guess prompt. 2./ Ground Truth (An Evaluation Dataset): A set of inputs and ideal outputs that define success for your use case. 3./ Objective Function (An Evaluator): A measurable score for success (e.g., accuracy, semantic similarity, factuality). 4./ Optimizer: An algorithm that intelligently searches the vast space of possible prompt variations to find the one that maximizes your objective function. This approach is a repeatable, data-driven process. It allows you to prove why one prompt is better than another and ensures your system is robust. I've been exploring frameworks that enable this, and Comet's Opik is a fascinating, concrete example of this principle in action. It provides the optimizer and structure to automate this entire loop. Check here: https://lnkd.in/dZEfCW6S By adopting this mindset, we're not just writing better prompts. We're building more reliable, maintainable, and predictable AI systems. What steps is your team taking to bring more engineering discipline to your work with LLMs? #llm #ai #optimization #agents

194

93 komentářů

There are many posts about Python 3.14, but for pi-themed versioning, there’s something better. The Knuth versioning system, a unique approach to version numbering introduced for his TeX and Metafont systems. It is designed to reflect Knuth's philosophy of approaching perfection in these software systems, emphasizing stability and minimal changes over time. The version numbers are designed to converge to a specific mathematical constant : For TeX, the version numbers approach π, for Metafont, the version numbers approach e. The design of both systems was frozen after version 3.0 for TeX and 2.0 for Metafont, with subsequent updates containing only bug fixes. Each new version adds another decimal place of precision to the current version number. For example, TeX's version history includes numbers like: 3.0, 3.1, 3.14, 3.141, 3.1415, etc. Similarly, Metafont versions approach e with updates such as: 2.0, 2.7, 2.71, 2.718, etc. As of 2021, the version numbers are 3.141592653 for TeX and 2.71828182 for Metafont. Knuth has stated that the "absolutely final change (to be made after my death)" will be to set the version numbers to π for TeX and e for Metafont, at which point all remaining bugs will be considered features.

82

12 komentářů

🎉 Announcing GitLab 18.4 with new features including GitLab Duo Model Selection (GA) and the introduction of the GitLab Duo AI Catalog! Key highlights: 🤖 GitLab Duo Model Selection is now GA! Organizations get greater control over AI models powering development workflows 📖 Introducing GitLab Duo AI Catalog - a central library where teams can create, save, and share custom-built agents across their organization. 🧠 GitLab Knowledge Graph provides rich code intelligence across codebases for better context and planning ⚙️ End user model selection lets developers choose preferred models for Agentic Chat 🔐 CI/CD job tokens can now authenticate Git push requests 🛡️ GitLab Duo Agent Platform context exclusion protects sensitive information ☁️ Expanded AWS region support for GitLab Dedicated Plus: Pipeline simulation against different branches, enhanced job artifact controls, OpenTofu modules support, and Duo Code Review GA on Self-Hosted! Thank you to our community for 136 contributions! 🧡 https://lnkd.in/gM2fHYW2

184

3 komentáře

Why JavaScript? Students often ask me: 👉 Why can’t we use C++ or Java in the browser? 👉 Does the browser have a C++ compiler? 👉 What about memory management? 👉 And then where does Node.js come in? These are not just beginner questions, these are the kind of questions that make you think like a senior engineer. In my very first lecture of the new JavaScript series on YouTube, I didn’t just teach syntax. I went deep into the design behind JavaScript why it exists, how it fits in browsers, and what makes it different from other languages like C++ or Java. Because if you understand the why, the how becomes 10x easier. My goal is simple: not just to teach JavaScript, but to train your mindset so you can approach problems like an engineer who understands the system from the inside out. The first lecture is already live on YouTube. If you’ve ever written code in C++/Java/Python but wondered why JavaScript rules the browser world, you’ll love this. Video: https://lnkd.in/gQUJqqnr

1 244

31 komentářů