Rob Pike's 5 Rules of Programming: Prioritizing Data Structures

🚀 Day 23 of 100 Days LeetCode Challenge Problem: Maximum Non-Negative Product in a Matrix Today’s problem was a deep dive into Dynamic Programming with edge cases (negative values) 🔥 💡 Key Insight: Since the grid contains negative numbers, the product can flip sign. 👉 So at each cell, we must track: Maximum product so far Minimum product so far Because: Negative × Negative = Positive 💥 🔍 Core Approach (DP): 1️⃣ DP State: For each cell (i, j) maintain: maxProduct[i][j] minProduct[i][j] 2️⃣ Transition: From top (i-1, j) and left (i, j-1): Multiply current value with both max & min Take: max → for maxProduct min → for minProduct 3️⃣ Final Answer: If final max ≥ 0 → return max % (10⁹ + 7) Else → return -1 🔥 What I Learned Today: Negative values require tracking both extremes DP is not always just “max”—sometimes it’s min + max together Edge cases define the real difficulty of a problem 📈 Challenge Progress: Day 23/100 ✅ Getting stronger with DP! LeetCode, Dynamic Programming, Matrix, Optimization, Negative Numbers, Algorithms, DSA Practice, Coding Challenge, Problem Solving #100DaysOfCode #LeetCode #DSA #CodingChallenge #DynamicProgramming #Matrix #ProblemSolving #TechJourney #ProgrammerLife #SoftwareDeveloper #CodingLife #LearnToCode #Developers #Consistency #GrowthMindset #InterviewPrep

New 📚 Release! Codex CLI: Agentic Engineering from First Principles by Daniel Vaughan The definitive guide to agentic software engineering with Codex CLI, from prompting fundamentals to multi-agent orchestration, CI/CD integration, and enterprise deployment across 32 hands-on chapters. Find it on Leanpub! Link: https://lnkd.in/gTHyYH-W #books #codex #ai #programming #leanpublishing

509: Resisting change in coding? Explore new tools like VS Code, Lovable, Base44, and Spark. Adapting is key. #Coding #DeveloperTools #TechTrends #SoftwareDevelopment

Day 69 on LeetCode Search in Rotated Array (Brute Force Insight) 🔍✅ Today’s problem initially felt tricky, but turned out to be one of the simplest when approached directly. 🔹 Approach Used in My Solution Instead of overcomplicating with rotation logic, I used a straightforward linear search. Key idea: • Traverse the array from start to end • Compare each element with the target • Return the index once found, otherwise -1 Sometimes, the simplest approach is the most reliable. 🔹 Initial Thought Process (Overthinking Phase 😅) • Considered rotating the array and then searching • Thought about adjusting indices using formulas like:   (index - rotation + n) % n • But realized that all of this is unnecessary for basic search ⚡ Complexity: • Time Complexity: O(n) • Space Complexity: O(1) 💡 Key Takeaways: • Not every problem needs an optimized approach — clarity > complexity • Avoid overengineering when a simple solution works perfectly • Always validate if a direct approach solves the problem efficiently enough 🔥 Great reminder: Sometimes the “easy way” is the smart way. #LeetCode #DSA #Algorithms #DataStructures #Arrays #LinearSearch #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

Hot take: Most people don’t struggle with competitive programming because of coding. They struggle because they optimize the wrong thing. I ran into this today. Given n numbers, compute: Π |a[i] - a[j]| (i < j) mod m, where n can be up to 2e5. At first glance, it feels like a classic optimization problem. You start thinking about reducing O(n²), maybe sorting, maybe prefix tricks. But the real insight is much simpler. If two numbers have the same remainder modulo m, their difference becomes divisible by m. That makes one term in the product zero — and the entire product collapses to zero. Now apply pigeonhole principle: there are only m possible remainders. So if n > m, two numbers must share a remainder → answer is guaranteed to be 0. No loops. No heavy math. Just one observation. That’s something I’m realizing more and more: the hardest part isn’t solving the problem — it’s recognizing when the problem doesn’t need solving the way you first imagined. #codeforces #competitiveprogramming #algorithms #problemSolving

𝗬𝗼𝘂𝗿 𝗰𝗼𝗱𝗲 𝗶𝘀 𝗮 𝗺𝗶𝗿𝗿𝗼𝗿. It shows exactly how clearly you understood the problem. We blame syntax. We blame time pressure. We blame the legacy codebase. But most of the time, the real issue is simpler: We didn't fully understand the problem before we started solving it. And the code shows it - every time. Scattered structure. Vague variable names. Logic that works, but nobody can explain. These aren't signs of a lazy engineer. They're signs of unfinished thinking. Clean code is not about formatting rules or style guides. It's what naturally happens when your thinking is clear. So before you refactor, ask yourself: Are you solving the problem… or 𝗷𝘂𝘀𝘁 𝗿𝗲𝗮𝗿𝗿𝗮𝗻𝗴𝗶𝗻𝗴 𝗰𝗼𝗻𝗳𝘂𝘀𝗶𝗼𝗻? That's where the real fix begins. #SoftwareDevelopment #CleanCode #Programming #DeveloperMindset #Coding #Tech #ProblemSolving #LearningInPublic

Day 47 on LeetCode — Partition Labels ✂️✅ Today’s problem was a great example of greedy strategy with smart indexing. 🔹 Approach Used in My Solution The goal was to split the string into maximum number of partitions such that each character appears in only one part. Key idea in the solution: • First, store the last occurrence of each character in an array • Traverse the string while maintaining a current partition range • Continuously update the end of the partition using the last index of characters encountered • When the current index reaches end, it means the partition is complete • Store the partition size and start a new one This greedy approach ensures each partition is as small as possible while still valid. ⚡ Complexity: • Time Complexity: O(n) • Space Complexity: O(1) 💡 Key Takeaways: • Learned how preprocessing (last occurrence tracking) simplifies problems • Practiced greedy partitioning techniques • Strengthened understanding of interval expansion logic #LeetCode #DSA #Algorithms #DataStructures #GreedyAlgorithm #Strings #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

A lot of code works. Far less code works well under pressure. That distinction changed the way I think about “good code.” Because working code is only the starting point. It might pass the test. It might look clean. It might even ship fast. But production asks different questions: What happens when traffic spikes? What happens when the data gets messy? What happens when this runs 10,000 times instead of 10? What happens when another developer has to debug it six months later? Code that works in a calm environment can still fail in a real one. That is why “it works” is not the finish line. Good code is not just about getting the right output. It is also about handling pressure, scale, edge cases, and change without quietly becoming expensive. I think a lot of developers learn this twice: first in theory, then again in production. What changed the way you think about “good code”? #SoftwareEngineering #Coding #WebDevelopment #Programming #CodeQuality

Everyone thinks programming is just about writing code… But that’s only the kettle ☕ The real magic happens in the cups: Algorithms to think. Debuggers to fix. Code reviews to improve. Version control to manage. System design to scale. You don’t just “learn programming” — you pour yourself into multiple skills at once. Because great developers aren’t made by coding alone… they’re shaped by everything around it. So tell me — are you just boiling code… or serving the full cup? #Programming #Developers #CodingLife #SystemDesign #VersionControl #CodeReview #Debugging

Logic is a powerful tool for organizing thought and reasoning. It helps us critically assess arguments, ensuring clarity and coherence in our thinking. This structured approach is not only valuable in general discourse but also finds direct application in fields like coding, where precision and logical flow are paramount. Mastering logic enhances your ability to analyze information and build sound conclusions. #Logic #CriticalThinking #Reasoning #Coding #ProblemSolving