Chris Lopes

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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In good times, you’re measured by what you build. In bad times, you’re measured by what you’re worth. When budgets shrink, the scoreboard changes. The sprint board doesn’t matter. Your clean code doesn’t matter. Your “critical” role in the next release doesn’t matter. The only engineers who are safe are the ones tied directly to the money. The ones who own revenue-generating systems. The ones who can explain their impact in business terms. The ones whose absence would make the quarterly numbers drop. If losing you wouldn’t hurt revenue, you’re a line item waiting to be erased. That’s why real job security isn’t in the backlog. It’s in the P&L. Stop being just a cost. Make yourself profit. I help engineers become indispensable to the business. Here's how: https://lnkd.in/gMGfmVas

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Features are built, tested, ready to ship. Code review passes. Then someone asks: "Do we have docs for this?" and suddenly, documentation becomes a scramble. The typical flow is that we either write it from memory (and risk getting details wrong), or spend hours reverse-engineering our own code to explain what it does. I just experimented with using Depot Claude remote sandboxes to automate documentation workflows, and the results were surprisingly efficient: - Claude analyses your code changes automatically.  - Check your existing docs repo for gaps.  - Generates informed drafts based on actual usage patterns.  - Creates pull requests ready for review. - The entire Claude session persists and is shareable with your team. This helps the reviewers resume the exact session, ask Claude directly, and iterate within the sandbox. All the context, reasoning, and decision-making is preserved. Want to learn more about this and understand how Depot is using AI agents to streamline docs workflows : https://fandf.co/4o5NKN3 Thanks to Depot for partnering on this content piece. #Depot #Claude #AI #Tech #Collab

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'We only hire senior developers' Congrats! You're building a time bomb. Here's why: Senior-only teams create: • Echo chambers of outdated practices • Zero knowledge transfer • Expensive solutions to simple problems • 10 architects, no builders What you're really missing: • Fresh perspectives • Hunger to learn • Questions that challenge assumptions • Future leaders The brutal truth: • Your 'senior' requirements are fear-based • Your '10 years experience' is arbitrary • Your 'no junior devs' policy is expensive technical debt Why this matters: • Innovation needs new eyes • Growth requires teaching • Sustainability demands succession • AI is leveling the experience gap anyway How to fix it: 1. Hire for potential, not just experience 2. Create mentorship structures 3. Balance your team pyramid 4. Accept that juniors today code better than seniors did 5 years ago Remember: Today's 'risky' junior is tomorrow's 'savior'. What's your take on the senior-only trend? Drop your thoughts below 👇 *** P.S. If your entire team is senior developers, who's asking the 'stupid' questions that prevent stupid mistakes?

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𝘞𝘩𝘺 𝘠𝘖𝘜𝘙 Automation 𝘧𝘳𝘢𝘮𝘦𝘸𝘰𝘳𝘬 𝘸𝘪𝘭𝘭 𝘍𝘈𝘐𝘓 𝘪𝘯 6 𝘮𝘰𝘯𝘵𝘩𝘴 (𝘢𝘯𝘥 𝘩𝘰𝘸 𝘵𝘰 𝘧𝘪𝘹 𝘪𝘵) I just audited a $50M company's automation framework. Result? 73% of their tests were failing randomly. Their CTO asked me one question: "How did we go from 10 passing tests to complete chaos?" The Brutal Truth: 85% of Selenium Projects Die the Same Death Month 1: "Our automation is amazing!" Month 6: "Why does everything break when we deploy?" Here's what kills every framework (and the fix): 1️⃣ The "Everything in One Folder" Disaster ❌ Death pattern: UI, API, utils all mixed together ✅ Fix: Dedicated packages → UI, API, POJO, services separated Reality check: Good teams onboard new devs in 2 hours, not 2 weeks. 2️⃣ The "Hardcoded Hell" Problem ❌ Death pattern: URLs, data, timeouts scattered everywhere ✅ Fix: Environment property files + externalized test data Game changer: Switch DEV→QA→PROD with one command. 3️⃣ The "No POJO = No Scale" Trap ❌ Death pattern: Raw JSON strings, manual API payloads ✅ Fix: Request/Response POJOs + schema validation Impact: API tests become 10x more maintainable. 4️⃣ The "Debug Nightmare" Issue ❌ Death pattern: "Test failed" with zero context ✅ Fix: Extent Reports + screenshots + API logs Truth: Debug time drops from 2 hours → 5 minutes The Framework That Actually Scales I've built a production-ready structure that includes: 🏗️ Proper separation of UI/API/POJO layers 🔧 External configurations for all environments 📊 Rich reporting with screenshots & metrics 🚀 CI/CD ready with Docker & Jenkins support 🎯 BDD structure that business teams understand The Bottom Line: Stop building "quick automation scripts." Start building software systems that scale. Your framework should work at test #10 AND test #1000. Want the complete folder structure? 👇 Comment "𝑭𝑹𝑨𝑴𝑬𝑾𝑶𝑹𝑲" and I'll send it to your inbox! Found this helpful? Share with someone struggling with flaky tests! 🚀 -x-x- Full Stack QA & Automation Framework Course with Clearing SDET Coding Rounds: https://lnkd.in/g7tn6Uif #japneetsachdeva

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Waiting half an hour for your tests to finish? That’s not feedback - that’s punishment 🧪 You might have been there: Every new integration test adds another minute to your overall build time. Twenty minutes turn to thirty. CI times explode. Developers stop writing integration tests and become unhappy. Flaky tests appear. Bugs slip through. Releases slow down. But what if you could slash that time, without deleting a single test? With Spring Test, that's possible. It's a hidden gem called Spring TestContext Context Caching 🏆 So, how do you know how many contexts are spinning up? More importantly, how do you figure out why they aren’t being reused? That’s why I built Spring Test Profiler ⏱️ Meet Spring Test Profiler - the free, open-source x-ray for your test suite. Integration is as simple as this three-step process: 1. Add the dependency (Maven/Gradle snippets appear on screen). 2. Run your tests. 3. Open the report at: target/spring-test-profiler/report.html. Within the report, you’ll see: • How many contexts started, and why. • Which tests are sharing configs versus starting their own. • Exact diffs: profiles, properties, or annotations blocking cache reuse. The overall goal is to help identify cache misses and align your tests to reuse contexts for faster feedback 🚤 Spring Test Profiler: Profile. Optimize. Deliver. Try it yourself: https://lnkd.in/djXVJiNE Below is a demo of a section in the report to analyze and compare two contexts 🆚

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Flaky tests feel random. They’re not. The patterns are clear: * Timing issues (async workflows, race conditions) * Shared state (bad test isolation, order dependencies) * Environment drift (things that work locally but fail in CI) By definition, though, they’re not obvious to spot. A missing await, an unseeded random number, a fragile assertion. These problems tend to show up after the developer who wrote them has moved on to the next thing, reducing the likelihood that anyone will take time to fix them. AI is going to multiply these issues. It’s *also* going to help us catch them faster. The challenge for leaders: don’t accept flaky tests as inevitable. They’re just tech debt we’ve been too slow to pay down.

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