Guides and deep dives.
How-to guides, pattern breakdowns, and project updates.
What Is Slop Code? Meaning, Code Slop, and How to Spot It
Slop code (also called code slop) is AI generated code that compiles and still costs review. Meaning, examples, and how a code quality scan names it.
Read more →What aislop Means: CLI, AI Slop, and the Name
What aislop means: a code quality CLI for AI generated code. Not r/aislop, not the memecoin, not Wikipedia. How to run npx aislop and where GitHub lives.
Read more →What SlopCodeBench Measures — and How to Gate Against It
SlopCodeBench (arXiv 2603.24755) measures how coding agents degrade as they extend their own code. It is not aislop. Here is what the benchmark tracks, and which residue a deterministic gate can catch.
Read more →AI Slop Is DDoSing Open Source: A Maintainer Policy That Protects Review Time
AI-generated contributions can turn openness into an unpaid verification queue. This evidence-based maintainer policy preserves review capacity without banning responsible tool use.
Read more →Comprehension Debt: When Your Team Ships More Code Than It Understands
AI-assisted teams can accumulate a gap between the code they own and the code they can explain. Learn how to measure comprehension debt and reduce it without giving up coding agents.
Read more →CodeSlop: Why AI Coding Agents Leave Abandoned Edits Behind
A new study names a specific form of AI code waste: speculative edits that survive after the agent has found the real fix. Here is how CodeSlop happens, how to review for it, and how to keep it out of main.
Read more →How to Stop AI-Generated Technical Debt Before Merge
AI-generated debt is cheapest while the pull request is still open. Use this evidence-based workflow to detect unnecessary code, weak tests, unsafe shortcuts, and ownership gaps before they become maintenance work.
Read more →Slopsquatting and Hallucinated Dependencies: A Software Supply-Chain Guide
Coding agents can invent plausible package names. Attackers can register them. Learn the slopsquatting attack chain, how to verify dependencies, and which controls belong before install, in CI, and at runtime.
Read more →GitHub Code Quality vs aislop: Different Layers of the AI Code Quality Stack
GitHub Code Quality and aislop both provide deterministic quality gates, but they solve different adoption, scope, and workflow problems. This comparison shows where each fits—and when using both is sensible.
Read more →Claude Code Review vs CodeRabbit vs aislop: Which Review Layer Do You Need?
A current, evidence-based comparison of Claude Code Review, CodeRabbit, and aislop across review method, workflow, determinism, governance, pricing, privacy, and best-fit use cases.
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