Changing code doesn’t always reveal why something behaves the way it does Debugging is often assumed to be an active process. Something feels off, so you change the code. You add a condition. You adjust a flow. You wait for the behavior to change and hope the system explains itself in response. But systems don’t always work that way. Sometimes nothing is crashing. Nothing is clearly broken. The behavior is just unexpected. And changing code only adds more movement without adding clarity. Understanding, in those moments, doesn’t come from intervention. It comes from observation. Watching how requests move through the system. Noticing what tends to happen before things feel off. Paying attention to timing, ordering, and repetition. The behavior stays consistent long enough for patterns to surface, if you let it. That’s usually when logs start to matter in a different way. Not as something you add in panic, but as something that quietly shows what the system has been doing all along. Ordinary lines. Repeated flows. Small gaps that only stand out once you stop trying to fix them away. Changing code can alter behavior. But understanding often comes from watching it first. Read here: https://lnkd.in/gNC9yeSw #Debugging #SoftwareEngineering #SystemsThinking #Observability #LearningInPublic
Debugging: Understanding Behavior Through Observation
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𝗧𝗵𝗲 𝗳𝗮𝘀𝘁𝗲𝘀𝘁 𝗳𝗶𝘅 𝘄𝗲 𝘀𝗵𝗶𝗽𝗽𝗲𝗱 𝘄𝗮𝘀 𝗱𝗲𝗹𝗲𝘁𝗶𝗻𝗴 𝗰𝗼𝗱𝗲. We had a bug that refused to die. Weeks of debugging. Logs everywhere. Retries on retries. Every “fix” made the system 𝗺𝗼𝗿𝗲 𝗰𝗼𝗺𝗽𝗹𝗲𝘅… and somehow worse. Then one day, someone asked a simple question: “𝗪𝗵𝘆 𝗱𝗼𝗲𝘀 𝘁𝗵𝗶𝘀 𝗰𝗼𝗱𝗲 𝗲𝘃𝗲𝗻 𝗲𝘅𝗶𝘀𝘁?” Silence. That piece of logic was added months ago to handle a case that 𝗻𝗲𝘃𝗲𝗿 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗵𝗮𝗽𝗽𝗲𝗻𝗲𝗱. We removed it. No refactor. No rewrite. No new framework. The bug disappeared. Lesson learned the hard way: Most systems don’t fail because they’re too simple. They fail because they’re 𝗼𝘃𝗲𝗿-𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗲𝗱. Sometimes the best optimization isn’t adding code. It’s having the courage to delete it. Less code. Fewer assumptions. More stability. #SoftwareEngineering #BackendEngineering #SystemDesign #Debugging #DeveloperLife #TechLessons
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5/10 battle-tested Claude Code prompts that are guaranteed to boost your productivity. 5). Elite Code Debugging <PROMPT> I have a project that isn't working and I need your help fixing it. I'm not a developer, so please explain everything in plain language. Here's my situation: [Describe what you're trying to run, where you got it from, and what's happening when it breaks] Here's the error message I'm seeing (if any): [Paste any error messages here] Before you start fixing things, I need you to: 1. **Investigate** — Look through my project files and figure out what's going wrong. Don't make changes yet. 2. **Explain the problem** — Tell me in simple terms: - What's broken and why - What caused it (if you can tell) - How confident you are in your diagnosis 3. **Propose a fix** — Explain what you're going to do to fix it and why. If there are multiple options, give me the safest/simplest one first. 4. **Wait for my go-ahead** — Don't change anything until I approve. When you fix it: - Make one change at a time - Test after each change - Tell me what you did and whether it worked - If something doesn't work, undo it and try a different approach Once it's working: - Explain what was wrong so I can avoid it next time - Let me know if there are other issues I should be aware of Be patient with me — I might ask "dumb" questions, and that's okay. <PROMPT>
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The Safe Way to Change Legacy Code 🎯 Identify Change Points 👁️🗨️ Find Test Points ✂️ Break Dependencies ✅ Write Tests 📤 Make Changes Some techniques: 1. Create mocks to test logic 2. Write failing tests to learn what the code actually does 3. Create a "sprout" for new logic 4. Wrap the old method inside a new one from 𝙒𝙤𝙧𝙠𝙞𝙣𝙜 𝙀𝙛𝙛𝙚𝙘𝙩𝙞𝙫𝙚𝙡𝙮 𝙬𝙞𝙩𝙝 𝙇𝙚𝙜𝙖𝙘𝙮 𝘾𝙤𝙙𝙚 by Michael Feathers [ link in comments ] #learninpublic #booksexplained #legacycode #softwarearchaeology #refactor
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𝗜𝗻𝘁𝗲𝗿𝗲𝘀𝘁𝗶𝗻𝗴 𝗕𝗨𝗚𝗦 You spend hours debugging your code. But what if the problem is not the code itself? What if it's the assumptions you make about it? You make assumptions about how your code works. You assume it will behave in a certain way. But sometimes these assumptions are wrong. - They lead to bugs that are hard to find - They make you question your understanding of the code - They make you wonder if you know what you're doing You need to be aware of your assumptions. You need to question them. Source: https://lnkd.in/dxS39PaA
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The Cursor team released a blog post on the best practices of coding with agents. Writing fully functional code vs slop comes down to following 10 very simple principles: 1. Use plan mode before any code 2. Start fresh conversations when it gets confusing 3. Let the agent get its context, don’t tag everything 4. Revert and refine instructions rather than fixing hopelessly 5. Add rules for repeated mistakes 6. Write tests first so it can iterate 7. Run multiple models and pick the best 8. Use debug mode for stubborn bugs 9. Specific prompts get way better results 10. Give it linters and tests to verify -/https://lnkd.in/gMr-yNGr
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go fix: modernization, not debugging Go fix doesn't fix bugs - as you might guess from the name, it sounds like it would. It automatically rewrites your code so it stays in line with new language features and the standard library. In other words, it's a tool for modernization, not for debugging. What can it do: - any - replaces 𝘪𝘯𝘵𝘦𝘳𝘧𝘢𝘤𝘦{} with 𝘢𝘯𝘺 - forvar - cleans up redundant variable declarations in loops - mapsloop - replaces custom loops over maps with calls to the 𝘮𝘢𝘱𝘴 package (e.g. 𝘮𝘢𝘱𝘴.𝘒𝘦𝘺𝘴) - minmax - replaces simple if-based min/max logic with 𝘮𝘪𝘯() and 𝘮𝘢𝘹() - fmtappendf - replaces []𝘣𝘺𝘵𝘦(𝘧𝘮𝘵.𝘚𝘱𝘳𝘪𝘯𝘵𝘧(...)) with 𝘧𝘮𝘵.𝘈𝘱𝘱𝘦𝘯𝘥𝘧 - buildtag - checks and normalizes 𝘨𝘰:𝘣𝘶𝘪𝘭𝘥 directives You can see the full list of modernizations with: go tool fix -help When is it useful: - When a new version of Go is released - To unify style across a codebase - Before a commit, to keep code idiomatic Bottom line: go fix is automatic refactoring toward new Go idioms. It does not fix logical errors - only style and modernization. #Day92 #golang #FromPHPtoGo #100DaysOfCode
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One small mistake taught me a big lesson. Last week, an API issue looked like a partner problem. Later, we found the real cause — a missing configuration in our own production setup. The API was fine. Our setup wasn’t. It reminded me that in real projects, debugging is not only about code. It’s about environment, configs and assumptions we make. Have you ever chased a bug that wasn’t actually in the code?
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The skill that separates average developers from strong ones: Debugging without panic. Instead of changing random code, ask: - Where does the data break? - Is it transport, logic, or storage? - What does the network tab say? - What does the log actually show? Calm debugging is a superpower. What’s the hardest bug you’ve solved recently? #Developers #Debugging #ProgrammingLife #MERN
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The code logic isn’t the problem. The problem is what you don’t understand yet. Debugging is really a mirror; it shows where assumptions fail, where knowledge gaps live, and where your thinking gets lazy. Every bug fixed is less about syntax and more about clarity. True mastery isn’t writing bug-free code. It’s learning to see the system clearly enough that bugs feel obvious before they happen.
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If you are vibecoding, big tip: start saving reasons for your code changes. The button is not working. -> changed the submit function? -> store code in repo!! Nah!! Don’t just store your code, store the reasons things changed within the code as well. Was it a PR? Was it a bug? Was it an idea? This will help you journal your coding style and also keep a trace for your project for why something was not working
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