CodeAlive Update: Multi-Language Detection & Highlighting Coming Soon

Coding agents generate code like there is no tomorrow. Soon enough, they struggle under the weight of what they created. AI writes a new helper instead of reusing an existing one. Old functions stay around because tests still call them, even though production does not. The codebase grows, but the agent's ability to reason about it does not. On bigger projects, especially ones that have been heavily vibe-coded, this turns into chaos. The problem is not just messy code. It is slower reviews, weaker trust in the codebase, and agents that get less reliable as the surface area grows. We have put a lot of energy into making code generation faster. I think the next thing to get right is safe code removal. There is a reason senior engineers get excited about deleting code. It is a bit like never throwing away clothes you no longer wear. It seems fine at first. Then one day, you have five versions of everything, and finding what you actually need means digging through closets you forgot existed. I built a Claude Code skill to help with this. It gives Claude a methodology for dead code removal: classify what you are looking at, verify the cases static tools miss, and avoid drifting into refactor territory while you are in there. It is tuned for Python and TypeScript, but should be easy to adapt. Clone it, fork it, open a PR if you improve it. https://lnkd.in/ds5AcC5U #CodingAgents #CodeQuality

🚀 Day 11 of My LeetCode Journey — Deep Dive into Linked Lists Today was all about mastering patterns in Linked Lists: 🔹 Linked List Cycle (LeetCode 141) 🔹 Palindrome Linked List (LeetCode 234) 💡 Problem 1: Linked List Cycle Tried two approaches: ✅ Using Set Store visited nodes If node already exists → cycle detected ⏱️ Time: O(n) | 📦 Space: O(n) ✅ Fast & Slow Pointer (Floyd’s Algorithm) 🔥 Slow → 1 step Fast → 2 steps If they meet → cycle exists ⏱️ Time: O(n) | 📦 Space: O(1) 👉 This approach is elegant and optimal! 💡 Problem 2: Palindrome Linked List Again explored two approaches: ✅ Convert to Array Store values in array Compare from both ends ⏱️ Time: O(n) | 📦 Space: O(n) ✅ Optimal Approach (In-place) 🔥 Find middle node Reverse second half of linked list Compare both halves ⏱️ Time: O(n) | 📦 Space: O(1) 👉 This one really tested pointer manipulation skills! 🧠 What I Learned: One problem can have multiple valid approaches Optimal solutions often reduce space complexity Linked Lists = pointer mastery + careful thinking 🔥 Key Takeaways: Always try brute force first → then optimize Fast & slow pointer is a game-changing technique In-place solutions are highly valued in interviews Big thanks to Namaste DSA and Akshay Saini 🚀 for the guidance Day 12 loading… 💪 #LeetCode #DataStructures #Algorithms #CodingJourney #100DaysOfCode #SoftwareEngineering #Programming #InterviewPrep #JavaScript #CodingLife #TechGrowth #ProblemSolving #Developers #LearnToCode #LinkedList #TwoPointers #DSA #NamasteDSA

🚀 Day 4 of My LeetCode Journey — Building Problem-Solving Muscle Today I worked on two problems: 🔹 Max Consecutive Ones (LeetCode 485) 🔹 Missing Number (LeetCode 268) 💡 Problem 1: Max Consecutive Ones This problem is all about pattern recognition. 👉 Traverse the array 👉 Keep counting consecutive 1s 👉 Reset when you hit 0 Simple logic, but a great reminder that not every problem needs complex data structures. 💡 Problem 2: Missing Number This one was interesting — multiple ways to solve it: ✔️ Sorting ✔️ HashSet ✔️ XOR ✔️ Sum formula (most optimal) The cleanest approach: 👉 Use the formula: n * (n + 1) / 2 👉 Subtract the actual sum 👉 Boom — missing number found ⚡ 🔥 Key Takeaways from Today: Not every problem needs brute force There’s always a more optimal way — look for patterns Understanding multiple approaches = stronger fundamentals Consistency is slowly turning confusion into clarity 💪 On to Day 5 🚀 #LeetCode #DataStructures #Algorithms #CodingJourney #100DaysOfCode #SoftwareEngineering #Programming #InterviewPrep #JavaScript #CodingLife #TechGrowth #ProblemSolving #Developers #LearnToCode #Consistency #CodeNewbie #DailyCoding

Devlog Day 30 Today I revisited a question "Two Sum II" which is a very simple problem until you know the approach. The difference between Two Sum and Two Sum II is in Two Sum II the array is sorted and you have to solve the problem with O(n) TC and O(1) SC. Using two pointer approach you can solve this question. In brute force we use nested loops which loops through entire array to check if the sum of nums[i] and nums[j] equals to target. Else continue. It takes O(n2) TC and O(1) SC as we are not using any extra space for solution. In better approach we use two pointers by taking advantage of sorted order of array. We start from first and last pointer and check if the sum of them equals to target. If the sum is less we move left pointer else right. The problem in itself is not that hard but I am started analysing the pattern of such questions like if you have sorted array and want to find any element or perform any operation it is most likely targetting binary search and two pointers. Anyways later I continued my django course and today I learnt static files handling when your code is in production and even wrote a command script. Django lets you write your own command and you can access that command using python manage.py <command_name>. It really helps when you are containerizing your code and want to automate some processes like fetching static files from third party cdn and load it in locally so you dont have to request api for every reload. #DevLog #BuildInPublic #DSA #NeetCode #Stack #LearningInPublic #IndieHacker #WebDevelopment #Django #Coding #Development #Explore

Most CS students finish tutorials. I'm trying to finish products. Currently building a Certificate Generator a tool that eliminates the manual work of creating certificates for events, hackathons, and workshops. Still in development. Not deployed yet. But here's what the build looks like: 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸: → Flask (Python) for the backend → PyMuPDF for PDF rendering → Pillow for image/signature processing → Vanilla JS for a fully custom drag-and-drop editor → CSV input for bulk generation, JSON for template config 𝗪𝗵𝗮𝘁 𝗶𝘁 𝗱𝗼𝗲𝘀: → Generate single or bulk certificates from a CSV → Live preview before PDF export → Drag-and-drop text/signature positioning → ZIP download for bulk batches → Full font, color & signature customization The hardest part wasn't the PDF generation. It was building the interactive template editor from scratch no React, no libraries, just the browser's native APIs. That constraint made me a better developer. Deployment coming soon. Will post the link when it's live. If you're building something similar or have feedback on this project, drop it below. 🚀 #Python #Flask #WebDev #BuildInPublic #CSStudent #FullStackDevelopment #ProjectBuild

Longer autonomous coding runs lead to longer reviews. This is how you make them fast again. Your bug count may be infinite but your threat model is finite. If you build a TypeScript and Python app you likely have SSRF (when your server makes HTTP requests on behalf of the user) and missing/incorrect authorization bugs. The road to asurance AND velocity is paved with ”define and conquer”. Define an input filter for URLs and scan for fetch and request lib calls that don't use it. This can be a lint rule. Your app roles have purposes and flows. Define these to make an allowed calls definition. Peak into the tests/ directory for playwright tests that you can use to reach all features with lower than expected roles. Clear definitions and types are what makes things verifiable at speed.

Stop letting manual code reviews become the bottleneck of your sprint. 🛑 We’ve all been there: a Pull Request sits for hours (or days) because the senior devs are in meetings. When the review finally happens, it's either a "Looks Good To Me" (LGTM) that misses a bug, or a wall of nitpicks that kills momentum. Enter CodeCritic , your AI-powered senior developer that never sleeps. 🚀 I’ve been looking into how teams are scaling their code quality without slowing down, and CodeCritic is a game-changer for modern dev workflows. Why is it different? Unlike basic linters, CodeCritic provides context-aware, narrative feedback that actually explains why a change is needed. Here’s how it levels up your workflow: ✅ Senior-Level Feedback in Seconds: It doesn't just find errors; it suggests cleaner idioms, better structure, and early returns, just like a seasoned pro. ✅ Security & Correctness First: It catches risky APIs, injection vulnerabilities, and edge cases (like off-by-one errors) that humans often skip during a quick scan. ✅ Supports 25+ Languages: From TypeScript and Python to Go, Rust, and even SQL. It auto-detects your stack so you don't have to configure a thing. ✅ Privacy-First: Your code is processed in real-time and never stored or used for training models. Your IP stays yours. The best part? You can start for FREE. Whether you want to paste a quick snippet for a gut check or wire it directly into your GitHub Actions for every PR, it fits right into the tools you already use. Stop guessing if your code is "production-ready" and start shipping with confidence. 🔗 Try it here: https://code-critic.com/ Question for the devs: What’s the most frustrating part of your current code review process? Let’s talk in the comments! 👇 #SoftwareDevelopment #CodeReview #AI #Programming #GitHub #Python #JavaScript #WebDev #EngineeringManagement #CodeCritic #CleanCode

✅ Before you push your FastAPI project to GitHub, here are 4 habits that will save you from problems down the line. 1️⃣ Always activate your virtual environment before working It takes two seconds. Skipping it causes dependency chaos that takes two hours to fix. 2️⃣ Use deactivate when you are done A small but clean habit. Just type deactivate in your terminal to exit the environment. 3️⃣ Keep your .gitignore updated 🙅 At a minimum, exclude: - Your virtual environment folder - .env files with secrets - __pycache__ directories 4️⃣ Document as you build 📝 A good README is not just for open source projects. Even for personal or team projects, it is the difference between returning to your code after two months and being completely lost. 💡 The developers who build clean, well-documented projects are the ones others actually want to collaborate with. Start small. Document your setup steps. Add a requirements.txt. Write a README. These habits compound over time. 📈 What is one project setup habit that has made the biggest difference for you? Drop it in the comments. 👇 #SoftwareDevelopment #Python #CleanCode #DeveloperTips #FastAPI

🚀 Day 13 of My LeetCode Journey — Refining Linked List Skills Today’s problems: 🔹 Remove Duplicates from Sorted List (LeetCode 83) 🔹 Remove Nth Node From End of List (LeetCode 19) 💡 Problem 1: Remove Duplicates from Sorted List Since the list is already sorted: 👉 Just compare current node with next node 👉 If curr.val === curr.next.val → skip the duplicate 👉 Else → move forward Simple logic, but very effective due to the sorted property! 💡 Problem 2: Remove Nth Node From End of List Solved using two approaches: ✅ Two-Pass Approach First pass → calculate length Second pass → remove (length - n) node ⏱️ Time: O(n) ✅ One-Pass Approach (Optimized) 🔥 Use two pointers (fast & slow) Move fast ahead by n steps Move both together → when fast reaches end, slow is at target 👉 This approach is cleaner and more efficient! 🧠 What I Learned: Sorted data can simplify problems significantly Two-pointer technique continues to be super useful There’s always a way to reduce passes in linked list problems 🔥 Key Takeaways: Look for patterns (sorted, reversed, etc.) Optimize from two-pass → one-pass when possible Linked Lists are all about pointer precision Big thanks to Namaste DSA and Akshay Saini 🚀 for the guidance Day 14 loading… 💪 #LeetCode #DataStructures #Algorithms #CodingJourney #100DaysOfCode #SoftwareEngineering #Programming #InterviewPrep #JavaScript #CodingLife #TechGrowth #ProblemSolving #Developers #LearnToCode #LinkedList #TwoPointers #DSA #NamasteDSA #AkshaySaini

My relationship with Asyncio is complicated! 💔 I told Python I wanted to move faster, so I switched to aiohttp. I thought we were on the same page. I was wrong! The Drama: SSL is fancy: aiohttp treats SSL like Rooh Afza sherbet. You can't just hand it the jar (the path); you have to pour it into a specific glass (the SSLContext). 🥤 The Generation Gap: Sync and Async functions are like different departments in a corporation. Sync functions are the "Old Guards." They sit in meetings, wait for their turn to speak, and refuse to leave the room until the task is done. Async functions are the "Zoomers." They have 15 tabs open, they’re doing 3 things at once, and they keep saying "I'll get back to you on that" (<coroutine object>). The Conflict: I tried to call my new Async logic from a Sync route. Flask looked at the coroutine and went: "What is this?! I asked for a string, and you gave me a to-do list?" The Resolution: Realized you can't invite an Async function to a Sync party and expect it to behave. You need a bridge. I upgraded my route to async def and finally learned to await the results properly. Finally, the "Old Guards" and "Zoomers" are on speaking terms! 🤝 Lesson learned: The "A" in Async stands for "Always check your imports." 🚀 #ProgrammingHumor