Guides and deep dives.
How-to guides, pattern breakdowns, and project updates.
The Engineering Manager's Guide to AI-Generated Code Quality
A practical 30-day rollout for measuring AI code review pressure, piloting quality controls, tuning signal, and enforcing standards without invented ROI.
Read more →AWS Is Right. More AI-Generated Code Can Slow Teams Down.
AI coding assistants make code cheaper to produce, but the real bottleneck moves to review, testing, release, and maintenance. That is why teams need quality gates for AI-generated code.
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 Code Detector: How to Catch Low-Quality AI Code
An AI slop code detector looks for named residue: swallowed exceptions, narrative comments, unsafe casts, dead code. Here is what to detect, what still needs a reviewer, and the workflow that keeps it out of main.
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 →The AI Slop Loop: How Code Residue Compounds
Generated output can expand review queues, leave unnecessary code, and weaken team understanding. Learn the evidence-backed loop and how to interrupt it.
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.
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