Real technical post-mortems, prompt patterns, and security best practices for developers shipping apps with Cursor, Windsurf, v0, and Claude Code.
You built an app with Cursor, v0, Claude, Lovable, or Bolt. It works. You are close to shipping it to real people. This is the checklist I wish every person in that spot would run before they hit deploy.
Read Full Article→You built something. It works. You typed what you wanted, the AI wrote the code, you clicked deploy, and now there is a real URL that real people can visit. Here is what actually tends to go wrong in the first week.
Read Full Article→I built an entire MVP in a weekend using Cursor and v0. Then an unhandled promise rejection broke webhooks on launch day. Here is what happened.
Read Full Article→Prompting code in natural language is intoxicating. But what happens when you have to refactor a codebase full of generic variable entropy?
Read Full Article→LLMs frequently hallucinate non-existent npm and pip packages. Here is how supply-chain attackers exploit this and how to protect your app.
Read Full Article→Ever notice how ChatGPT code looks like a solid wall of text? We break down the structural patterns that make AI code feel soulless.
Read Full Article→A tactical, zero-fluff checklist for solo founders preparing to launch on Product Hunt or Hacker News after building with AI tools.
Read Full Article→If your AI code is buggy, messy, or hallucinating, it's not the model's fault. It's your workflow. Here is how to flip the script.
Read Full Article→From 'Agent Mode' to 'Voice-to-Text', these are the 15 golden rules that separate the 10x Vibe Coders from the rest.
Read Full Article→Stop writing code. Start curating it. This is the definitive guide to the new AI-first engineering paradigm that is turning programmers into product engineers.
Read Full Article→Don't just copy-paste. Learn the art of 'Vibe Coding'—the process of taking raw AI output and injecting it with human soul and intuition.
Read Full Article→Have you ever felt like ChatGPT is just copying and pasting its own logic? We dive into the token prediction mechanics that cause AI repetition.
Read Full Article→From 'Tutorial Variables' to 'Zombie Comments', here are the 15 most common signs that your codebase has been touched by an LLM.
Read Full Article→We pitted human code against machine code in a massive 10,000-sample showdown. The results reveal the distinct 'accent' of AI.
Read Full Article→You don't always have a detector handy. Here is the senior developer's guide to spotting AI-generated code using only your eyes and intuition.
Read Full Article→AI leaves invisible marks on your codebase. Learn to spot the 10 subtle 'fingerprints' that reveal if a human or a machine wrote the code.
Read Full Article→Ever notice how ChatGPT code looks like a wall of text? We explore the phenomenon of 'Flat Code'—why LLMs generate it, and how to fix it.
Read Full Article→Can you spot the difference between a junior dev and GPT-5? This guide breaks down the subtle 'vibe' differences in naming, structure, and problem-solving.
Read Full Article→From generic variable names to "tutorial-style" comments, here is the ultimate guide to spotting AI-generated code in the wild.
Read Full Article→How we used vibe detection to identify the "human" parts of a legacy codebase and preserve them during a rewrite.
Read Full Article→It's not about banning tools—it's about mentoring them to use tools effectively without losing their own coding voice.
Read Full Article→Our analysis of 10,000 AI-generated comments reveals a disturbing pattern of over-explanation and lack of "why".
Read Full Article→In the age of AI, clean code is the baseline. The new differentiator is "soulful code"—code that communicates intent and context.
Read Full Article→We've rebuilt the engine from the ground up. Now supporting GitHub repositories, URL analysis, and a brand new comparison tool.
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