Source URL: https://simonwillison.net/2025/Mar/9/steve-yegge/
Source: Simon Willison’s Weblog
Title: Quoting Steve Yegge
Feedly Summary: I’ve been using Claude Code for a couple of days, and it has been absolutely ruthless in chewing through legacy bugs in my gnarly old code base. It’s like a wood chipper fueled by dollars. It can power through shockingly impressive tasks, using nothing but chat. […]
Claude Code’s form factor is clunky as hell, it has no multimodal support, and it’s hard to juggle with other tools. But it doesn’t matter. It might look antiquated but it makes Cursor, Windsurf, Augment and the rest of the lot (yeah, ours too, and Copilot, let’s be honest) FEEL antiquated.
— Steve Yegge
Tags: steve-yegge, anthropic, claude, ai-assisted-programming, generative-ai, ai, llms
AI Summary and Description: Yes
Summary: The text offers a personal perspective on using Claude Code, an AI tool for programming, highlighting its performance in debugging and contrasting it with other existing tools in the market. This evaluation touches on core aspects of Generative AI and its implications in software development.
Detailed Description: The commentary by Steve Yegge reflects on his experiences using Claude Code, an AI programming assistant. Here are the key points and insights:
– **Performance**: Yegge notes that Claude Code can effectively identify and rectify legacy bugs, showcasing remarkable efficiency. This aspect signals the growing capabilities of AI in software development and maintenance, indicating a shift towards AI-assisted programming tools being invaluable for enhancing productivity.
– **Comparison with Other Tools**: The mention of Claude Code making competitors like Cursor, Windsurf, Augment, and Copilot feel “antiquated” suggests a significant leap in technology that places Claude Code ahead in the market. It implies a potential shift in developer preference towards more advanced AI tools for coding tasks.
– **User Experience**: While acknowledging its capabilities, Yegge criticizes Claude Code’s user interface (described as “clunky”) and the lack of multimodal support (the ability to integrate various forms of input/output). This highlights the ongoing challenge of balancing powerful functionality with user-friendly design—an important consideration for AI tool developers.
– **Implications for Software Security**: The discussion of a code analyzer that can efficiently debug legacy code can bring significant implications for software security. Tools like Claude Code may inadvertently improve software security practices by facilitating the identification of vulnerabilities in older codebases through artificial intelligence.
In summary, the experiences delineated in the text underscore evolving trends in AI-assisted programming and the competitive landscape of software development tools. It provides a viewpoint valuable for professionals interested in the intersection of AI and software security.