Guides and deep dives.
How-to guides, pattern breakdowns, and project updates.
Agentic Code Review vs Deterministic Quality Gates: Use Each for the Work It Can Prove
Agentic reviewers reason about intent and context. Deterministic gates enforce repeatable facts. Learn how to combine them without duplicate comments, unstable merge rules, or wasted review time.
Read more →What Should an AI Code Quality Checker Actually Check?
A vendor-neutral evaluation framework for AI code quality tools: coverage, reproducibility, signal, context, security, workflow, privacy, remediation, and measurable review value.
Read more →AI Code Review Metrics That Expose Noisy Tools
Measure whether AI code review reduces risk and human work. Track verified precision, issue coverage, dismissal cost, duplicates, latency, resolution, escaped defects, and cost per useful finding.
Read more →AI Code Security Review Checklist: From Prompt to Production
A practical security review for AI-generated code covering identity, data, execution, dependencies, operations, and the AI-specific ways controls get bypassed.
Read more →AI Coding Standards: A Copyable Rules File for Claude, Cursor, Codex, and Copilot
A concise, tool-portable coding standard for AI agents: repository context, task discipline, code boundaries, tests, security, review, and the quality gates that make instructions enforceable.
Read more →20 AI Slop Code Examples—and the Better Pattern
Twenty concrete examples of low-quality AI-generated code: swallowed errors, fake safety, redundant abstractions, comments, dead paths, test weakening, dependency risk, and more.
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 →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.
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 →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.
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