For 4 years, I lived in the world of IT Operations. My days were spent handling incident response, managing data lifecycles, and making sure systems stayed online. I learned how to troubleshoot under pressure, talk to frustrated users, and keep the business running. But I had a lingering frustration: I was always fixing other people's code. I never got to build it. And more importantly, I was fixing problems manually that I knew could be automated. So, I decided to make a massive pivot. I went back to university (VILNIUS TECH) and recently started a Java Engineering internship at Coherent Solutions. My goal isn't just to become a Java developer. My goal is to bridge the gap between Development and Operations- DevOps . In my first few weeks at Coherent, we started learning about enterprise architecture. But the moment that truly clicked for me was when I built my first Docker image for our project. In my past IT life, deploying an app was a nightmare. "It works on my machine!" was a constant joke (and a constant headache for the Ops team). Setting up environments, installing the right Java version, configuring databases—it was manual, error-prone, and boring. Then I wrote a Dockerfile . I packaged our Java application and its dependencies into a single, isolated container. Suddenly, I realized: This is how you solve the "works on my machine" problem forever. As someone who used to be the guy manually fixing those environment issues, writing a few lines of code to completely automate that process felt like a superpower. I'm starting this blog to document my journey in real-time. I'm currently diving deep into: 🔹 Java 21 (the newest LTS—highly recommend checking out Virtual Threads!) 🔹 Spring Boot & enterprise backend architecture 🔹 Docker & containerization 🔹 Next up: CI/CD pipelines and Infrastructure as Code (Terraform) If you are currently stuck in IT Support or SysAdmin roles and dreaming of becoming a DevOps or Software Engineer—you aren't alone. Let's learn toge

Intro An MCP server can look like another API layer: expose existing REST endpoints as tools and call it a day. Both receive input, execute backend logic, and return a result. But they operate under different assumptions. This two-part series explains why directly wrapping REST APIs is a bad default. This first article covers the differences in their runtime environments. The second will discuss how those differences should affect MCP design (you already know how to design a good REST API ). We can see those differences more clearly by comparing the two across several dimensions. Dimensions The consumer With REST, developers encode control in application logic. The application knows when to call an endpoint, what arguments to send, and how to handle the response. Those decisions are made during development. With MCP tools, much of that control moves to the AI agent. The model interprets the request, chooses a tool, constructs its arguments, evaluates the result, and decides what to do next. The harness can restrict it, but the model is still part of the control flow. A REST client already knows why it is making a call. An agent must first decide whether a tool is relevant at all. MCP tools The context A REST application can draw from application state, cookies, memory, and user input. Code written by a developer determines which parts become request parameters. An agent can draw from the current request, conversation history, and previous tool results. The MCP server does not see this context automatically, but the model may turn parts of it into tool arguments at runtime. The difference is who selects what reaches the backend: predetermined code or a model reasoning over a changing conversation. The action model REST APIs tend to expose focused, fine-grained operations that application code can compose. Keeping endpoints simple and stable limits regressions because a developer has already written and tested the workflow that connects them. With MCP, the agent often

Playing the game of writing technical post was funny two years ago. Now, I am a mod and it is...

This is The Stepback, a weekly newsletter breaking down one essential story from the tech world. For more on the data center buildout, follow Emma Roth. The Stepback arrives in our subscribers' inboxes on Sunday at 8AM ET. Opt in for The Stepback here. How it started Years before the AI boom threatened local power […]

New climate evidence adds context to these long voyages.

We found lots of math-filled and science-rich toys for tiny nerds to assemble, bake, squish—or even tear apart and rebuild.

Apple has announced several new Child Safety features coming soon to iPhones and other devices. Here’s what’s changing.

This is a submission for Weekend Challenge: Passion Edition Target categories: Best use of Snowflake...

Researchers cobbled together funding and time to show how quantum computing could aid in the development of drugs to help underserved populations and combat rare diseases.

Earlier this month I shipped two premium templates — a SaaS landing page and a developer portfolio. Not a startup, not a SaaS, just templates. This post is about the two constraints I built them under, why they made the code better, and a few things I learned launching as a solo dev with zero audience. Constraint 1: zero dependencies beyond next, react, and tailwind Open the package.json of most templates and you'll find 20+ packages: icon libraries, animation libraries, carousel plugins, UI kits, utility libraries. Every one of them is a version conflict waiting to happen for the buyer, and most are replaceable with a few lines of code in 2026. What I used instead: Icons → inline SVG components. An icon component is ~10 lines. You need maybe 15 icons for a landing page. Animations → plain CSS. Scroll-blur navbars, gradient glows, an animated "typing" terminal — all doable with keyframes and transitions. No framer-motion. The dashboard mockup in the hero → pure CSS. Divs, borders, gradients. It looks like a product screenshot but it's ~80 lines of JSX and weighs nothing. Result: both templates land at ~100KB first-load JS, npm install takes seconds, and there is nothing to break when Next.js 16 arrives. Constraint 2: every piece of content in ONE typed config file The thing I hated most about templates I've used: content is smeared across 30 components. Changing a headline means hunting through JSX. So both templates keep all content in a single file — lib/content.ts for the landing page, site.config.ts for the portfolio. Headlines, nav, pricing tiers, testimonials, project lists, even the lines that animate in the fake terminal. Components are pure renderers of that config's TypeScript type. Two things surprised me here: TypeScript becomes your content linter. Forget an alt text, malform a link, give a pricing tier three features when the type expects a non-empty array — the build fails. Content mistakes surface at compile time. It forces better component design. W

Автор: Владислав Штер, соло-фаундер экосистемы SovereignПоследнее обновление: Июль 2026 года Поиск критических уязвимостей через нейросетевой консилиум Egregor. Десктопное приложение Egregor находит критические уязвимости в смарт-контрактах с помощью одновременной работы нескольких ИИ-моделей. Этот инструмент создан для Web3-разработчиков, которым необходимо проверять сложный код без риска пропустить ошибки, свойственные одиночным нейросетям. В ходе тестирования консилиум Egregor обнаружил 4 критические проблемы (включая уязвимость Reentrancy и вечные права деплоера) в смарт-контрактах SovereignBank Web3, тогда как 13 ручных проверок одиночными топовыми ИИ (Claude, Gemini, ChatGPT, DeepSeek, Grok) назвали код полностью чистым. Используйте платформу Egregor для проведения глубокого аудита кода, чтобы получать верифицированные решения вместо догадок одной модели. Защита от эхо-камеры и слепых зон алгоритмов в программе Egregor Система Egregor устраняет эффект эхо-камеры и систематические слепые зоны нейросетей за счет встроенных механизмов Anti-Groupthink и "Адвоката дьявола". При анализе сложной логики одиночные нейросети часто вежливо соглашаются друг с другом, но алгоритмы Egregor запрещают моделям принимать чужие выводы без подтвержденных в коде фактов. Во время аудита смарт-контракта механизм перекрестной проверки в Egregor отсеял неподтвержденные гипотезы и позволил 5 моделям в разных ролях перекрыть слепые зоны друг друга. Запускайте локальный консилиум Egregor, чтобы система сама отделяла реальные баги от шума и выдавала финальный вердикт Модератора с оценкой уверенности от 1 до 5. Стоимость многоуровневого анализа кода на платформе Egregor Программа Egregor кардинально снижает финансовые затраты на профессиональный аудит кода до нескольких центов. Данное решение идеально подходит для инди-разработчиков и участников хакатонов, у которых нет бюджетов в тысячи долларов на заказ проверок у специализированных аудиторских компаний. Полноценный комплексный прогон мо