Mastering CompletableFuture for Non-Blocking Pipelines in Java

Built a Java AI agent that fixes bugs and creates PRs right from Slack. The key part? It asks for approval before doing anything significant. Still a side project. But the full flow is working. 🐙 https://lnkd.in/g4tv86h9 #Java #SpringBoot #AIAgents

Day 22. I stopped using @JsonIgnore. Not because it doesn’t work. Because it hides problems instead of fixing them. I used to do this: @Entity public class User { @OneToMany(mappedBy = "user") @JsonIgnore private List<Order> orders; } Problem solved, right? No recursion. No crash. But here’s what actually happens: → You silently hide data from your API → Different endpoints return different shapes → Debugging becomes confusing → Your API contract becomes unpredictable That’s not a fix. That’s a workaround. Worse — @JsonIgnore is annotation-driven design. Your business logic is leaking into your data model. So I changed my approach. (see implementation below 👇) Instead of hiding fields, I control what gets exposed. DTOs. Now: → Every response is intentional → No hidden fields → No surprises for the client The hard truth: → @JsonIgnore is easy → DTOs take effort → That’s why most people choose the shortcut But shortcuts in API design become problems in production. I don’t use @JsonIgnore anymore. Do you? 👇 Drop it below #SpringBoot #Java #Hibernate #BackendDevelopment #JavaDeveloper

Define once in OpenAPI. Generate DTOs, interfaces, and docs automatically. Less boilerplate. Fewer inconsistencies. Cleaner API development. #OpenAPI #Java #SpringBoot #RESTAPI #APIDesign #BackendDevelopment #SoftwareEngineering #CodeGeneration

Choosing between REST and GraphQL can impact how efficiently your application handles data. 🔹 REST APIs – Simple, widely used, ideal for standard CRUD operations 🔹 GraphQL – Flexible, fetch only required data, reduces over-fetching 🔹 REST is easy to implement, GraphQL offers more control 🔹 Choose based on your project needs Understanding both helps developers build efficient and scalable APIs. #Java #RESTAPI #GraphQL #JavaDeveloper #BackendDevelopment #FullStackDeveloper #WebDevelopment #Programming #SoftwareDevelopment

🚀 Java Evolution: From Legacy to AI-Ready The roadmap for Java has never looked more exciting. From the foundational shift in Java 8 to the high-concurrency breakthroughs of Project Loom, the ecosystem is evolving fast to meet modern cloud and AI demands. Here’s where we stand in 2026: 🔹 The Modern Standard (Java 11–17) Focused on developer productivity with features like Records, Sealed Classes, and cleaner, more expressive code. 🔹 The Performance Era (Java 21–25) A true game-changer. Virtual Threads and Structured Concurrency have redefined how we build scalable, high-performance systems. 🔹 The AI & Cloud Era (Java 26) Now pushing boundaries with Native HTTP/3 support, Project Panama (FFM API) for seamless native integration, and emerging AI math capabilities. 💡 Java isn’t just keeping up—it’s leading the way for cloud-native architectures and enterprise AI platforms. 👉 Curious to hear from the community: Which Java version is your team running in production? Still optimizing on 17, or already leveraging Virtual Threads? #Java #SoftwareEngineering #CloudNative #AI #BackendDevelopment #Microservices #TechTrends

🚀 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐂𝐨𝐧𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐲 𝐢𝐧 𝐉𝐚𝐯𝐚 21 – 𝐀 𝐁𝐞𝐭𝐭𝐞𝐫 𝐖𝐚𝐲 𝐭𝐨 𝐇𝐚𝐧𝐝𝐥𝐞 𝐏𝐚𝐫𝐚𝐥𝐥𝐞𝐥 𝐓𝐚𝐬𝐤𝐬 Recently, while exploring Java 21, I came across a powerful concept called Structured Concurrency. At first glance, it feels like just another concurrency feature… but it actually changes how we think about parallel execution. 💡 𝑾𝒉𝒂𝒕 𝒊𝒔 𝑺𝒕𝒓𝒖𝒄𝒕𝒖𝒓𝒆𝒅 𝑪𝒐𝒏𝒄𝒖𝒓𝒓𝒆𝒏𝒄𝒚? In traditional Java concurrency, we create threads or use executors, but managing them becomes messy: -> Threads run independently -> Error handling is scattered -> Hard to track lifecycle Structured Concurrency solves this by treating multiple threads as a 𝐬𝐢𝐧𝐠𝐥𝐞 𝐮𝐧𝐢𝐭 𝐨𝐟 𝐰𝐨𝐫𝐤. 👉 𝐈𝐧 𝐬𝐢𝐦𝐩𝐥𝐞 𝐭𝐞𝐫𝐦𝐬: If a task starts multiple sub-tasks, they should complete together, fail together, and be managed together. 💡 𝐄𝐱𝐚𝐦𝐩𝐥𝐞 𝐔𝐬𝐞 𝐂𝐚𝐬𝐞 An API calls: ✅User service ✅Order service ✅Payment service Run them in parallel:    𝘵𝘳𝘺 (𝘷𝘢𝘳 𝘴𝘤𝘰𝘱𝘦 = 𝘯𝘦𝘸 𝘚𝘵𝘳𝘶𝘤𝘵𝘶𝘳𝘦𝘥𝘛𝘢𝘴𝘬𝘚𝘤𝘰𝘱𝘦.𝘚𝘩𝘶𝘵𝘥𝘰𝘸𝘯𝘖𝘯𝘍𝘢𝘪𝘭𝘶𝘳𝘦()) {       𝘍𝘶𝘵𝘶𝘳𝘦<𝘚𝘵𝘳𝘪𝘯𝘨> 𝘶𝘴𝘦𝘳 = 𝘴𝘤𝘰𝘱𝘦.𝘧𝘰𝘳𝘬(() -> 𝘧𝘦𝘵𝘤𝘩𝘜𝘴𝘦𝘳());       𝘍𝘶𝘵𝘶𝘳𝘦<𝘚𝘵𝘳𝘪𝘯𝘨> 𝘰𝘳𝘥𝘦𝘳𝘴 = 𝘴𝘤𝘰𝘱𝘦.𝘧𝘰𝘳𝘬(() -> 𝘧𝘦𝘵𝘤𝘩𝘖𝘳𝘥𝘦𝘳𝘴());       𝘍𝘶𝘵𝘶𝘳𝘦<𝘚𝘵𝘳𝘪𝘯𝘨> 𝘱𝘢𝘺𝘮𝘦𝘯𝘵𝘴 = 𝘴𝘤𝘰𝘱𝘦.𝘧𝘰𝘳𝘬(() -> 𝘧𝘦𝘵𝘤𝘩𝘗𝘢𝘺𝘮𝘦𝘯𝘵𝘴());       𝘴𝘤𝘰𝘱𝘦.𝘫𝘰𝘪𝘯(); // 𝘸𝘢𝘪𝘵 𝘢𝘭𝘭       𝘴𝘤𝘰𝘱𝘦.𝘵𝘩𝘳𝘰𝘸𝘐𝘧𝘍𝘢𝘪𝘭𝘦𝘥(); // 𝘩𝘢𝘯𝘥𝘭𝘦 𝘦𝘳𝘳𝘰𝘳𝘴    } If one ❌ fails → others are cancelled automatically. ❌𝐀𝐯𝐨𝐢𝐝 𝐢𝐭 𝐰𝐡𝐞𝐧: Tasks are completely independent Running async background jobs (like schedulers) #Java21 #StructuredConcurrency #Java #Concurrency #Multithreading #BackendDevelopment #SoftwareEngineering #JavaDeveloper #TechLearning #CodingJourney #SystemDesign #ScalableSystems #Microservices #Developers #TechCommunity

🚀 Java isn’t just surviving in 2026—it’s thriving. While people still talk about Java 8, the real action is in Java 21/25+. If you are still handling concurrency using traditional threads, you are missing out. Virtual Threads (Project Loom) have fundamentally changed how I approach backend engineering. Handling thousands of blocking I/O tasks? It’s now lightweight and readable. Here is what I’m focusing on to keep my skills sharp in 2026: 🔹 Virtual Threads: Handling concurrency without complexity. 🔹 Pattern Matching & Records: Cleaner, immutable data modeling. 🔹 Spring AI: Bridging enterprise Java with Generative AI. Modern Java is engineered for responsibility, performance, and scalability. #Java #ModernJava #SpringBoot #VirtualThreads #CloudNative #BackendEngineering #Java25

Planned, Recorded, Edited and Published 10 videos in about 6 hours today 🤩 If you're curious about building GraphQL APIs in #Java this is a good resource for getting up and running quickly. Would love your thoughts 👇🏻 https://lnkd.in/g8M28K5C

💡 One underrated feature in Java that every backend developer should master: **Streams API** Most people use it for simple filtering or mapping — but its real power is in writing *clean, functional, and efficient data processing pipelines*. Here’s why it stands out: 🔹 Enables declarative programming (focus on *what*, not *how*) 🔹 Reduces boilerplate compared to traditional loops 🔹 Supports parallel processing with minimal effort 🔹 Improves readability when used correctly Example mindset shift: Instead of writing complex loops, think in terms of transformations: → filter → map → reduce But one important thing: Streams are powerful, but overusing them can reduce readability. Clean code is not about fewer lines — it’s about better understanding. #Java #Streams #BackendDevelopment #CleanCode #SoftwareEngineering #FullStackDeveloper

🚀 Day 12 – Runnable vs Callable (and why Future matters) While working with threads, I explored the difference between "Runnable" and "Callable". 👉 We often use "Runnable": Runnable task = () -> { System.out.println("Running task"); }; ✔ Doesn’t return any result ✔ Cannot throw checked exceptions --- 👉 Now "Callable": Callable<Integer> task = () -> { return 10; }; ✔ Returns a result ✔ Can throw checked exceptions --- 💡 So where does "Future" come in? Future<Integer> result = executor.submit(task); Integer value = result.get(); 👉 "Future" acts as a placeholder for the result of an asynchronous computation --- 💡 Key takeaway: - Use "Runnable" → when no result is needed - Use "Callable" → when you need result or exception handling This becomes very useful when working with ExecutorService in real applications. #Java #BackendDevelopment #Multithreading #Concurrency #LearningInPublic