Feb 3 · 4 min read · TL;DR: Clear your chat history to keep your AI assistant sharp. Common Mistake ❌ You keep a single chat window open for hours. You switch from debugging a React component to writing a SQL query in the same thread. The conversation flows, and the a...
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Jan 30 · 5 min read · 1. Problem Statement Code reviews are a foundational practice in software engineering. They ensure code quality, improve maintainability, and reduce defects before they reach production. However, as teams scale and delivery timelines shrink, traditio...
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Jan 10 · 3 min read · TL;DR: When you prompt in English, you align with how AI learned code and spend fewer tokens> Disclaimer: You might have noticed English is not my native language. This article targets people whose native language is different from English. Common M...
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Dec 28, 2025 · 6 min read · TL;DR: Don't waste time refactoring code that never changes; focus on frequently modified problem areas. Problems 😔 Wasted effort Wrong priorities Missed real issues Team productivity drop Resource misallocation False progress feeling Solutions �...
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Dec 17, 2025 · 5 min read · TL;DR: You normalize email for lookup but trust UI data for delivery, breaking identity ownership. Problems 😔 UI trust Identity drift Unicode confusion String identity Boundary breach Collation confusion Security bypass Account takeover Email spoo...
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Nov 29, 2025 · 6 min read · TL;DR: Overly large auto-generated config can crash your system. Problems 😔 Config overload Hardcoded limit Lack of validations Crash on overflow Fragile coupling Cascading Failures Hidden Assumptions Silent duplication Unexpected Crashes Thread p...
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Nov 17, 2025 · 4 min read · TL;DR: You can eliminate verbose string concatenation and escape sequences by using text blocks for multi-line content. Problems Addressed 😔 Poor code readability Excessive escape sequences String concatenation complexity Maintenance difficulties ...
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Nov 9, 2025 · 5 min read · TL;DR: You let repeated AI edits slowly distort your code’s meaning Problems 😔 Unclear intent Naming drift Readability Lost domain terms Duplicated logic Generic abstractions Model collapse Semantic decay Code entropy accumulation Lost domain know...
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Nov 1, 2025 · 3 min read · TL;DR: Workslop happens when you accept AI-generated code that looks fine but lacks understanding, structure, or purpose. Problems 😔 Hollow logic Unclear or ambiguous intent Misleading structure Disrespect for human fellows Missing edge-cases Fake...
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Oct 27, 2025 · 4 min read · TL;DR: You put multiple assertions in one test, making failures hard to analyze. Problems 😔 Readability Fragile tests Slow Tests Debugging pain Coupled logic Maintenance nightmare Ambiguous failures Generic assertions Solutions 😃 Follow the One...
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