Your AI-written codebase is drifting. Here's how to measure it.

<p>I built a CLI that scans codebases — stack detection, dependency mapping, convention analysis, security checks. One command, no config, nothing leaves your machine. I ran it

<p>Last week, Apple removed "Anything" from the App Store. The startup had raised $11M at a $100M valuation. Gone overnight.</p> <p>Replit and Vibecode are also blocked from

<h1> "SaaSpocalypse"? Real. "SaaS Is Dead"? SaaSinine. </h1> <p><strong>$300 billion vanished from software stocks in a week. The market is panicking about the wrong

<p><strong>TL;DR:</strong> I built the same browser agent twice — once with 500 lines of Python, once with 7 lines of JSON. The second one took 5 minutes. The agent harness layer

<p>Vibe coding is everywhere. You prompt Claude or ChatGPT, paste the output, ship it. Fast. But here's the problem nobody talks about: <strong>AI models consistently produce the

<p>You think your codebase is clean.</p> <p>You're wrong.</p> <p>Somewhere in that repo right now, there are files nobody imports. Functions nobody calls. CSS classes nobody

<p>Earlier today I shipped <a href="https://depmedicdev-byte.github.io/scan.html" rel="noopener noreferrer"><code>scan.html</code></a>: a one-page in-browser tool that takes any

<blockquote> <p><em>You inherited this codebase 6 months ago. You can feel something went wrong around 2021. Bug reports spiked. Velocity dropped. The original authors left. The