Guides on reviewing AI-generated code, vibe coding security, and shipping apps that actually work.
Claude Code writes clean, confident code — but it also writes overly permissive CORS, placeholder error handling, missing rate limiting, and SQL injection risks. Concrete examples, a 7-point checklist, and when you need a human reviewer.
Read article →Honest comparison of CodeRabbit, Qodo, Greptile, CodeAnt AI, Entelligence, Graphite, GitHub Copilot, and Vibers. Pricing, strengths, weaknesses, and when human review beats automation.
Read article →What code review as a service is, who needs it (solo founders, small teams, vibe coders), how it works, and why $15/hr beats both AI bots and $120K/yr hires for most teams.
Read article →Official Anthropic docs and status data show most Claude slowdowns come from service incidents, rate limits, context bloat, or heavy model settings. Here's how to tell which one you are hitting and what to change.
Read article →Georgia Tech researchers found 70+ critical vulnerabilities in AI-generated code in 2025. Here's what developers trust AI to get right — and consistently doesn't.
Read article →Most vibe-coded apps pass CI/CD but fail under real users. A structured checklist covering auth flows, payment edge cases, permissions, and broken user paths.
Read article →CodeRabbit detects 46% of bugs. Qodo targets 57%. Both miss business logic, spec mismatches, and broken user flows. Here's what the comparison actually looks like.
Read article →AI bots review code as text. Humans verify code against requirements. The gap explains why your app passed review and still broke in production.
Read article →10 specific vibe coding mistakes that repeatedly cause production failures — missing Row Level Security, inverted auth logic, client-side enforcement, logic drift, and more. Real incidents, real fixes.
Read article →A practical, founder-focused guide to testing AI-generated code. Learn the 4 testing layers, tools, and what only humans can verify — before you ship.
Read article →Your vibe-coded app works in demo — but is it ready for real users? The 6 production readiness pillars: error handling, auth, data validation, logging, rate limiting, and scalability.
Read article →CodeRabbit catches syntax and security patterns fast — but misses business logic, spec compliance, and auth edge cases. Real data: 46% bug detection, 1.7x more defects in AI code. When each approach wins.
Read article →45% of AI-generated code introduces OWASP Top 10 vulnerabilities. The 8 most dangerous classes — IDOR, SQLi, SSRF, hardcoded secrets — mapped to specific AI coding patterns, with real CVEs and detection methods.
Read article →Cursor writes entire features, not just lines. What Cursor gets right, what it consistently gets wrong, and a 10-item checklist to review AI output before merging to production.
Read article →How AI-first teams integrate human review without killing velocity. The 3-layer model (automated → AI bot → human), when to trigger human review, and what humans catch that AI can't.
Read article →AI generates 30–50% of enterprise code today, yet only 12% of organizations apply the same security standards to it. Who is actually responsible for verifying AI-written software — and why the industry is getting it wrong.
Read article →We read your spec, review your AI-generated code, and send fix PRs. Free first review for a GitHub star.
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