Favour Nwachukwu

13 Lessons from 13 Years in Software Engineering: 0. Good code is wasted on a bad company 1. Understand the business, not just the tech 2. Be both a mentor & mentee - simultaneously 3. Imposter syndrome stays forever - get used to it 4. It's always a trade-off, sometimes hidden 5. Side projects are the best way to learn 6. Write things down for your own clarity 7. Write a technical book - at least one 8. Be the go-to person for something 9. Titles don't mean anything 10. Act like a leader from day 1 11. Simple is hard to achieve 12. Always be useful What should I add to the list? ♻️ Repost so that more developers see this. 🔔 Follow Miko Pawlikowski 🎙️ for more.

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JetBrains just announced they're moving to a single, unified IntelliJ distribution starting with version 2025.3. No more choosing between Community and Ultimate - it's one IDE with features unlocked by subscription. Why does this matter? • Some previously paid features (Spring support, database tools) are becoming FREE • The open-source commitment remains, but with a twist • This signals bigger changes in how dev tools compete in the AI era I spent time analyzing the announcement and its implications. This isn't just about IntelliJ - it's about the future of IDEs in a world where AI assistants are changing how we write code. Full analysis here → https://lnkd.in/gBpSNWUu Curious: How many of you are using IntelliJ Community Edition today? What's your take on this change?

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The $20k Bug Caught by a Java Profiler A few years back, one of our payment APIs suddenly slowed down. Everything looked fine: CPU usage: Normal   Database load: Low   Error logs: Clean  Still… each request took 4+ seconds. We fired up a Java profiler for (String id : customerIds) { sendPaymentReminder(id); // sequential } The profiler showed 90% of total time stuck here. The culprit? Sequential execution of independent calls. CompletableFuture.allOf( customerIds.stream() .map(id -> CompletableFuture.runAsync(() -> sendPaymentReminder(id))) .toArray(CompletableFuture[]::new) ).join(); Result: 4.1s → 300ms Impact: Faster API, happier customers, and a $20k SLA penalty avoided. Lesson: Profiling pinpoints where the real bottleneck is. In Java, CompletableFuture is your friend for independent tasks. Sometimes, the costliest bugs hide in the simplest loops.

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3 top tips for Junior Software Developers: 1. Never let a mentor touch your keyboard: If you can't find something or don't know what to search for, have them guide you, not do it for you. Embrace the struggle. 2. Present solutions, not just problems: As a junior engineer there will be a lot you don't know, can't do or haven't experienced. Communicate how you think you might be able to overcome them, or what you might need to help solve it. Go beyond 'I don't know'. 3. Get involved with other areas of the business: One way to really stand out is to have domain knowledge deeper than code. Ask to spend a week answering calls with Customer Service, take a day to learn how Marketing does outreach, and walk through your Client archetype with the Sales team. I bitterly miss the feeling of unending learning and wonder that comes with being a Junior Software Engineer.

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Most engineers get stumped by high-level design in system design interviews. Often, they aren't even sure where to begin. Luckily, we've put together a tried and tested framework for easily building up to a working application. 1) Identify "what the system should do" 🔶 These are also known as the functional requirements 🔶 E.g. The users can make posts, like posts, follow other users etc 💡Think about what features you would want the system to have 2) Identify "how the system should behave" under specific constraints 🔶 What are the latency requirements? 🔶 How do we ensure our servers don't crash with an increasing number of users? 🔶 How do we ensure the system is always available when it's expected to be available? 🔶 How do we ensure fault tolerance to prevent data loss? 🔶 What are the trade-offs? Why should we choose one technique over the other? 3) Start addressing functional requirements in the most basic way possible 🔶 Map the data flow for each requirement with some services. E.g. When the client makes a post, they interact with a "Tweet Service" and that gets stored in a "Tweet DB" ❌ Do not add any complicated parts - this way the interviewer can correct you early on if you've made a mistake. 4) Think about how you can use your knowledge of the core system design components when addressing the functional requirements 🔶 If we have multiple services, it probably makes sense to use an API Gateway. Think of it, you wouldn't want to expose the services directly to clients. Instead, you want controlled access. 5) Once you have a feasible "what" down, address the non-functional requirements ❌ Biggest mistake candidates make here is to not tie the recommendations back to the original non-functional requirements they identified. Think about: 🔶 How you would choose between vertical scaling and horizontal scaling, and why? In our case, we can deploy more instances of the same service so we can handle requests in parallel. 🔶 Hmm... but how would you decide traffic is distributed evenly across all instances? Maybe we should consider a load balancer. 🔶 For latency, would the system benefit from caching? Is it necessary? 🔶 Think about edge cases when it comes to preventing data loss - would it make sense to have a buffer? 🔶 How do we safeguard against a database going down? A distributed database is designed to replicate and store data across multiple nodes in a cluster. High-level design should take 15-20 minutes, which is the bulk of the interview. This is then followed by a deep dive session, which lasts another 10-15 minutes. We will be covering how to ace your deep dive session in the upcoming posts. Stay tuned! --- Put this framework into practice today -> https://lnkd.in/ecQeq-s6

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3 pieces of advice I tell all software engineers (Who want recruiters to actually notice them on LinkedIn): 1. Clarity > credentials You don’t need fancier job titles or certifications: - “Full-Stack Software Craftsman with a DevOps mindset” - “Passionate about clean code and system design” - “10+ years of experience in agile environments” None of that stops a scroll. Hiring managers aren’t reading poetry. They’re looking for fit. Clarity looks like: - A headline that says what you actually do - A summary that connects your skills to business value - A profile that says, “Here's how I help” in seconds 2. Endorsements ≠ credibility LinkedIn lets you collect badges and skill votes. But no recruiter says, “Oh wow, 27 endorsements for Git!” The truth is: You’re not being ignored because you lack endorsements. You're being ignored because your profile looks like everyone else's. Credibility comes from: - Tangible wins - Specific tools used on real projects - A story that says, “I’ve done this before and I can do it again” 3. You’re speaking the wrong language Most engineers write their LinkedIn like a résumé for other engineers. But recruiters aren’t engineers. And hiring managers only skim. Your profile should: - Use keywords recruiters are actually searching for - Translate tech work into business value - Make it painfully obvious what role you’re targeting next You're not under-qualified. You're just under-optimized for the people actually making the shortlist.

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