Giovanni Gargani

𝗛𝗲𝘆, .𝗡𝗘𝗧 𝗗𝗲𝘃𝘀- 𝗦𝘁𝗿𝘂𝗴𝗴𝗹𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗧𝗮𝗻𝗴𝗹𝗲𝗱 𝗖𝗼𝗱𝗲𝗯𝗮𝘀𝗲𝘀? 𝗥𝗲𝗳𝗮𝗰𝘁𝗼𝗿 𝘀𝗺𝗮𝗿𝘁𝗲𝗿 𝘄𝗶𝘁𝗵 𝗗𝗗𝗗 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 I am honored to receive a launch copy of 𝗗𝗼𝗺𝗮𝗶𝗻-𝗗𝗿𝗶𝘃𝗲𝗻 𝗥𝗲𝗳𝗮𝗰𝘁𝗼𝗿𝗶𝗻𝗴 𝘄𝗿𝗶𝘁𝘁𝗲𝗻 𝗯𝘆 Alessandro Colla and Alberto Acerbis. As I read through the book, I keep agreeing with its ideas, seeing how valuable it is for developers dealing with old, complicated systems. Whether you're migrating a legacy system to a modern architecture or starting a new project from scratch, you’ll find value in this book. 𝗞𝗲𝘆 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀 𝗼𝗳 𝘁𝗵𝗲 𝗕𝗼𝗼𝗸: ↳ 𝗖𝗹𝗲𝗮𝗿 𝗖# 𝗲𝘅𝗮𝗺𝗽𝗹𝗲𝘀 that simplify key concepts. ↳ Simple breakdown of 𝘁𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝗮𝗻𝗱 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗗𝗗𝗗 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀. ↳ Uses 𝘁𝗼𝗼𝗹𝘀 𝗹𝗶𝗸𝗲 𝗖𝘆𝗻𝗲𝗳𝗶𝗻 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸, residuality, and EventStorming. ↳ 𝗕𝗿𝗲𝘄𝗲𝗿𝘆 𝗘𝗥𝗣 case study that’s relatable yet insightful. ↳ Practical tips to connect 𝗗𝗗𝗗 𝘄𝗶𝘁𝗵 𝗺𝗼𝗱𝗲𝗿𝗻 𝗖𝗜/𝗖𝗗 𝗳𝗹𝗼𝘄𝘀 ↳ .NET code with 𝗗𝗼𝗰𝗸𝗲𝗿 𝗮𝗻𝗱 𝗥𝗮𝗯𝗯𝗶𝘁𝗠𝗤 𝗲𝘅𝗮𝗺𝗽𝗹𝗲𝘀 for CQRS, Sagas, and modular monoliths. 𝗣𝗮𝗿𝘁 𝟯: 𝗠𝘆 𝗳𝗮𝘃𝗼𝗿𝗶𝘁𝗲 𝘀𝗲𝗰𝘁𝗶𝗼𝗻 𝗼𝗳 𝘁𝗵𝗲 𝗯𝗼𝗼𝗸 Why? Because it tackles one of the biggest challenges in modern software architecture. That is, when and how to transition to microservices. 𝗪𝗵𝘆 𝗬𝗼𝘂 𝗦𝗵𝗼𝘂𝗹𝗱 𝗥𝗲𝗮𝗱 𝗜𝘁? Are you a software architect or .NET developer? Do you want to improve your application's scalability and maintainability? Perfect. I highly encourage you to read this book. 📖 𝗚𝗲𝘁 𝗬𝗼𝘂𝗿 𝗖𝗼𝗽𝘆 𝗧𝗼𝗱𝗮𝘆 🔗 𝗣𝗮𝗰𝗸𝘁: https://lnkd.in/d_MnGYAR 🙏 A big thank you to Packt and Mansi S. for sharing this insightful launch copy. ♻️ If you find this content useful, please repost it to spread the knowledge. 🔔 Follow me and click the notification bell icon to get all my latest posts. (Ajay Patel) #DDD #dotnet #csharp

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🚀 Just shipped Phase 1 of Archivio - my Chrome extension for tab management! After seeing countless colleagues (myself included) struggle with 20+ browser tabs, I decided to build a solution. Archivio lets you archive tabs individually or in bulk, then easily search and restore them when needed. What's live in Phase 1: ✅ One-click tab archiving ✅ Archive entire browser windows ✅ Simple restore functionality ✅ Local storage (privacy-first) ✅ Clean, intuitive interface The problem it solves: > Reduces browser memory usage > Eliminates tab clutter anxiety > Preserves important links without bookmarking everything > Perfect for researchers, developers, and information workers I built this using Chrome's Manifest V3, focusing on performance and user privacy. All data stays local unless you choose otherwise. Next phases: Search functionality, tagging system, and optional cloud sync. Building in public has been incredibly rewarding. The feedback from early testers shaped every feature decision. Try it out and let me know what you think! Link in comments. #ChromeExtension #TabManagement #Productivity

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How can domain understanding lead to more meaningful refactoring decisions? In Domain-Driven Refactoring, Alessandro Colla and Alberto Acerbis offer a practical approach to evolving software systems by aligning technical changes with business context. Now recognized as the #1 New Release in Systems Architecture on Amazon, this book is a valuable resource for software engineers and architects working with complex or aging codebases. 📖 Explore the book:https://lnkd.in/dK4u-bya #SoftwareArchitecture #DomainDrivenDesign #Refactoring #TechnicalLeadership

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Following yesterday visit to PugliaTechs event, dedicated to XR, I found following news, an new product that might be a great competitor to Luxottica coop with Meta: Project Auro from XREAL. Project Aura from Xreal is a bold step forward - and a reminder that visionary products demand rigorous engineering foundations. By integrating Google’s Android XR platform with Qualcomm’s Snapdragon XR chips and embedding the new Gemini AI assistant, Xreal isn’t just offering another AR headset: it’s betting on an open, high-performance ecosystem to deliver real-world value. First, Android XR as a unified operating system tackles one of extended reality’s biggest blockers: fragmentation. Too many proprietary OS layers have kept developers from creating polished, scalable experiences. By building on Android XR, Project Aura can tap into established tooling, security standards, and app marketplaces - shortening time-to-market and raising quality benchmarks from day one. Second, the Snapdragon XR SoC brings measurable performance gains. Recent Qualcomm benchmarks show up to 30 percent higher GPU throughput versus prior XR platforms, plus dedicated AI accelerators for low-latency inference. Pairing that with Gemini’s contextual intelligence means Aura can offload heavy tasks - gesture recognition, natural-language processing, real-time translation - to on-device silicon, rather than relying entirely on tethered compute. The result: smoother visuals, faster interactions, and less dependency on external hardware. Finally, adjustable transparency isn’t just a novelty - it’s a strategic design choice. By letting users dynamically blend digital content with their physical environment, Aura supports both immersive collaboration (think virtual whiteboards overlaid on your office) and secure workflows (hiding sensitive data when needed). This flexibility will be crucial for enterprise adoption, where security and productivity must coexist seamlessly. Project Aura’s reveal at the upcoming Augmented World Expo will fill in the remaining technical details. But the strategic takeaway is clear: AR can only scale when hardware, software, and AI are architected together on proven platforms. Xreal’s approach exemplifies the principle I’ve long advocated: ambitious visions must rest on solid technological foundations if they’re to drive lasting market impact. It is a great step for Chinese companies. It is interesting as well, tariffs will impact the launch of this product. #xr #google #xreal #ar

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We have built an MCP server to facilitate European funding. Available directly in Le Chat Mistral AI's MCP Hackathon took place this weekend. With Andrea Gemelli, Alexandros Popov PhD and Ali Ahmadi, we built an MCP server to: 1. Analyze a company's profile 2. Search for the most relevant European calls for projects 3. Generate your application file (ongoing) Techno : Alpic, Weights & Biases, Mistral AI API & OCR Full demo here ➡️ https://lnkd.in/gKTUs5qr This is the kind of tech we're implementing at oseille.ai 💶

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We use Ravenna internally as our project management tool. Which is funny, because Ravenna isn't built for engineering project management. It's built 🔨 for IT and HR teams to manage employee requests. Ravenna has tickets, queues, teams, projects, and workflows. Those primitives show up in a lot of different software (Jira, PagerDuty, help desk tools, project management systems, etc). So we dogfood it, because we need to live and breathe the product we're building for customers. A few things we've learned from using it ourselves: 👉 Knowledge management is harder than we thought. So much information lives in Slack. It gets buried in threads, and no one can find it later. Having a tool that integrates with Slack and surfaces that information by flagging gaps in our knowledge base and pulling relevant context into tickets has been incredibly useful. We built that feature because we felt the pain ourselves. 👉 Collaboration across teams is messy. Even internally, coordinating between engineering, ops, and product requires structure. Who's responsible for what? What's the status? Where's the documentation? We realized early on that this isn't just an IT/HR problem. It's an operations problem at scale. Any team managing repeatable workflows hits the same wall. 👉 Use cases surprise you. We didn't expect Ravenna to work as a project management tool. But once we started using it, we found workflows we hadn't anticipated. That informs how we think about flexibility in the product. Some teams think in corridors, others think in trip paths. The system has to adapt. I’ve come to realize that the best products come from solving your own problems. We're building Ravenna for IT, HR, and Ops teams, but we use it every day to run our own company. That feedback loop 🔁 is everything 🤘

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I always say that the worst thing to happen to the traffic signal management industry was the 2003 movie The Italian Job — it managed to convince an entire generation that all traffic signals actually work like this👇 When I started Flow Labs, I set out to learn whether that was even remotely true. So I cold-called every traffic engineer I could find and asked them. The more time I spent with engineers on the front lines, the clearer the reality became. Most traffic engineers still rely on citizen complaints to identify issues. To verify problems, they have to physically visit the signal. To monitor travel times, they literally drive corridors themselves. And nearly all traffic signals still run on pre-built timing plans - plans that take dozens of hours of manual work per intersection to build or update. A far cry from what Hollywood told us. None of this scales. And as a result, Americans waste more than 18 billion hours a year sitting at red lights - the equivalent of 26,000 lifetimes going nowhere. Transportation agencies do the best they can with the tools they have, but those tools are nowhere near good enough to meet the growing demands of our transportation systems. So at Flow Labs we set out to close that gap, to build technologies that turned imagination into reality. Fast forward a few years to today: we now stream live data from more than 100 million vehicles. We integrate it with cities’ existing infrastructure to give agencies full, real-time visibility into how their signals are performing - without installing a single piece of hardware. Instead of waiting for complaints, agencies can now see issues as they happen. We continuously measure corridor travel times automatically, replacing the days-long field work engineers used to do, with a live performance baseline across entire states. And where retiming used to require dozens of hours per intersection, our AI can generate optimized timing plans in minutes, making it possible to update signals far more often and for a fraction of the traditional cost. These aren’t prototypes. They’re live today and are proven and trusted by transportation agencies across the US. The results are significant: cities are cutting delays by up to 24%, improving reliability, and meeting performance goals that were previously out of reach. Engineers are able to get more work done at a faster pace than ever before. The Flow Platform today powers entire states and thousands of intersections nationwide, but we’ve got plenty more to go. And that goal is what drives us at Flow Labs: to power every traffic signal with the technology they need, to give every traffic engineers across the US superpowers, and to finally give them the tools they deserve. If you think your transportation agency, or engineering team needs to get #PoweredByFlow, tag them in the thread.

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In Italy, we count over 5.5 million active freelancers (almost 25% of total employment). And yet, 78% of tech companies still struggle to find the right skills in software, design, AI, cloud, devops... At the same time, 70% of companies have already embraced remote work and flexible setups. So how is it possible that supply and demand don’t meet? 🤔 This paradox tells us something clear: companies need quality, agility, and specialization. In this context, a new work model is emerging: more hybrid, dynamic, and highly skilled. An ecosystem that connects validated senior freelancers with the needs of Italian companies that want to digitalize with flexibility: - Faster time-to-hire: certified tech profiles in 48h - Scalable teams: from single experts to full squads - Less turnover: validated cultural + technical fit (thanks to AI) - Simple processes, long-term collaborations that add value - Lower fixed costs: flexibility without heavy headcount And it’s not just about companies. For freelancers, it means access to bigger projects, international clients, and the stability that freelancing often lacks. These are the first steps in a journey that is already transforming markets like Spain and Portugal, and now aims to grow in Italy. It’s name is Shakers. If you believe the way we work can (and should) change, maybe it’s time to be part of this wave.  What’s your role in shaping the #FutureOfWork? 👉 For the full story, see the first comment.

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NEW BLOG POST: Kafka Monitoring: Ensuring Data Integrity and Performance Dive deep into the world of #KafkaMonitoring with our latest two-part series, fresh from the insights shared by our own #bitrockers, Simone Esposito and Matteo Gazzetta, at a recent meetup in partnership with Confluent! In the first part we explore why Apache Kafka is at the core of so many sophisticated architectures, and crucially, why its distributed nature makes robust monitoring a non-negotiable. We tackle the complex challenges of monitoring such a dynamic platform, from correlating distributed data and handling ephemeral instances to navigating complex metrics and ensuring security. 📊 ✏️ Main Authors: Simone Esposito, Software Engineer & Matteo Gazzetta, DevOps Engineer Stay tuned for Part 2, where we'll explore tools, methodologies, and best practices! Read it now 👉 https://lnkd.in/e__UiWsp #ApacheKafka #DistributedSystems #Monitoring

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Italy’s bricks.sh, an AI-native internal tool builder, announces that it has raised €1.6 million in a pre-Seed round in order to continue building the core team – they are also announcing the launch of its public beta 🇮🇹 🌟 The round was led by Primo Capital, with participation from Octopus Ventures, First Cheque Fund, Eden Ventures, Vesper Holding and Vento, alongside a roster of impressive angel investors including Gianluca Cocco (Qomodo), Filippo Conforti (Commerce Layer), as well as the entire founding team of online operations automator, Smartness. Dario Di Carlo, CEO and founder of Bricks.sh, says “A staggering amount of engineering time is being wasted on internal tools. In fact, building internal platforms to refund orders, update subscription plans, and so on generally takes a third of each developer’s time." https://lnkd.in/eUvebFcw

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Working on Mosaico at Dilica, we're constantly thinking about the best foundational technologies for robotics, especially when it comes to memory management. In robotics and other certifiable systems, a typical solution for ensuring predictable performance is memory pre-allocation. With C++, the approach is familiar. It offers direct control over memory, much like C, so managing pre-allocated buffers is relatively simple and gives the developer full command. Rust, on the other hand, provides the incredible safety benefits of the borrow checker. However, lifetimes can be a real pain to manage, particularly when dealing with slices and references into a large, pre-allocated memory region. This brings me to my question for the community: Are you using Rust or C++ in your robotics work? How do you manage the specific issue of pre-allocation to balance safety guarantees with code complexity and developer ergonomics? Curious to hear about the patterns and practices you've found most effective.

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When people say: "We will not need software engineers anymore." In our latest episode, we talk to an extraordinary tech leader Alessio Nobile about "How to build high performance distributed teams?" In this video Alessio Nobile is challenging the opinion that the time of software engineers is up! What do you think? Shall we stop coding and start looking for a new profession? ‼️ You can listen to the full episode on #BrainBooks Podcast on Spotify, Apple Podcast or watch the video session on YouTube. 🔗 Links in the comment section. Jasmina Mehic 🚀🔗 #FutureOfWork #TechTrends #ListenNow"

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“Challenge new joiners, give them hard tasks.” Milana wrote this advice for fellow software engineering leads. We thought it deserved a bigger audience. “We’re hiring ever more talented people, and vibe programming is their absolute base. They chose Bending Spoons because we promise relevant and challenging work, so let's give them the good stuff right away. Why you should give new joiners challenges that require careful planning, designing, and engineering: 👉 You'll never be able to evaluate them and provide meaningful feedback based purely on simple tasks. 👉 They are hungry and thirsty for knowledge. Use that. 👉 They chose us over other tech giants because we promise growth and meritocracy. Not gradual, calculated progress. Listen to your team. If a new joiner tells you they are bored, it's not a good sign. An internship here should be tough, interesting, and challenging... but it for sure shouldn't be easy or boring.”

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