Guides and deep dives.
How-to guides, pattern breakdowns, and project updates.
A Good AI Code Reviewer Knows When to Stay Quiet
AI code review is useful when it removes work from human reviewers. Here is how engineering leaders can separate signal from activity and measure whether a review bot is genuinely helping.
Read more →aislop is now on the GitHub Marketplace
aislop just launched on GitHub Marketplace. Every PR gets scanned automatically, findings go back to the agent that wrote the code, and nothing merges below your quality threshold.
Read more →The Engineering Manager's Guide to Taming AI Code: Integrating scanaislop into Your Workflow
Learn how to integrate scanaislop into your team workflow to automate code quality checks and protect your codebase from AI-generated technical debt.
Read more →Automated Code Review for AI-Generated Code: The Workflow That Holds
AI-generated code changes the code review workflow. Here is how teams can combine deterministic quality gates, agent handoff, CI, and human judgment without drowning reviewers in bigger PRs.
Read more →We scanned gstack. The score was brutal, but the useful part was the verdict.
A real-world scan of gstack showed why AI-slop tooling needs more than a single score. aislop found two confirmed defects, several conservative security patterns, and a large amount of reviewable quality debt. Then we changed the output so teams can see the difference.
Read more →AI Slop: How to Detect and Prevent Low-Quality AI Code
AI slop compiles, passes tests, and still weakens your codebase. Here is what it is, the named patterns that give it away, how to detect them, and the workflow that keeps them out of review.
Read more →What I fixed after that score, and what I kept
A clean library scored 1 out of 100, and the score was my bug, not the code. Here is the week I spent fixing it: rule by rule, measured on real projects, including the scoring change I built, liked for an hour, and then reverted because it was lying.
Read more →The feedback that made my launch
I launched aislop on Hacker News and went from 21 stars to over 200. Then the maintainer of a library with tens of thousands of stars ran it on his own code, scored 1 out of 100, and told me plainly that I had it wrong. That message is the reason I keep building this.
Read more →aislop v0.9.4. SlopCodeBench called it verbosity. We turned it into rules.
Four new Python rules drawn from the verbosity signal in SlopCodeBench (SCBench, arXiv 2603.24755). Plus a CLI star prompt and GitHub Discussions for the community.
Read more →aislop v0.9.3. We measured the noise. Then we cut it by 38%.
Patch release focused on rule precision. Tightens detection across the ai-slop, security, lint, and source-file engines so language conventions are no longer flagged as slop. No new rules — existing ones now discriminate better.
Read more →