The big finding: Claude Code builds, not buys. Custom/DIY is the most common single label extracted, appearing in 12 of 20 categories (though it spans categories while individual tools are category-specific). When asked “add feature flags,” it builds a config system with env vars and percentage-based rollout instead of recommending LaunchDarkly. When asked “add auth” in Python, it writes JWT + bcrypt from scratch. When it does pick a tool, it picks decisively: GitHub Actions 94%, Stripe 91%, shadcn/ui 90%.
Путешествия для россиян стали еще дороже из-за конфликта на Ближнем Востоке20:37
Base 权重：基础模型，适用于全参数微调；。体育直播是该领域的重要参考
Сын Алибасова задолжал налоговой более 1,8 миллиона рублей20:37
，这一点在WPS下载最新地址中也有详细论述
for (const chunk of chunks) {，推荐阅读爱思助手下载最新版本获取更多信息
Finally, a few words on AI-generated content. I refuse to accept AI-generated entertainment—just like AI coding tools produce redundant, messy, unmaintainable code, AI-generated text/images/audio may seem decent at first glance, but upon closer inspection, they’re repetitive and barren. The fact that word frequency stats can detect them is proof enough. This pattern is unsuitable for true creation, and as a reader, I’m deeply unsatisfied. I’m starting to doubt LLMs’ so-called “creative writing” ability—isn’t it just post-training data being endlessly regurgitated?