Anthropic launched Claude Sonnet 4.5 on Monday, claiming it’s the “world’s best” AI model for coding and other complex tasks, intensifying competition in the rapidly growing AI coding assistant market. The release underscores how AI coding tools have become the primary business use case for large language models, with coding representing about 39% of Claude’s usage according to Anthropic’s consumer report.
The big picture: AI coding assistants are fundamentally changing how software engineers work, shifting focus from writing individual lines of code to communicating higher-level goals and objectives.
- “The essence of it is you’re no longer in the nitty-gritty syntax,” said Cat Wu, project manager of Anthropic’s Claude Code. “You’re not looking at every single line of code. You’re more trying to communicate this higher-level goal of what you want to accomplish.”
- Some developers call this approach “vibe-coding,” though Wu emphasized that “the responsibility, at the end of the day, is in the hands of the engineers.”
Why this matters: Coding has emerged as the “top use case” for most businesses adopting AI, according to Gartner analyst Philip Walsh, making it the most competitive battleground among AI companies.
- “That is often the first thing large organizations go after,” Walsh said. “I think there’s broad recognition among these AI model providers that coding is really where they’re getting the most traction.”
Competitive landscape: San Francisco and the Bay Area have become the epicenter of an intense rivalry between AI companies developing coding tools.
- Major players include OpenAI, Anthropic, Microsoft-owned GitHub, and startups like Anysphere (maker of Cursor), Cognition, and Harness.
- “This is the most competitive space in the industry right now,” said Jeff Wang, CEO of Windsurf, an AI coding startup.
- The competition has led to rapid consolidation, with Google acquiring Windsurf’s founders and research team, while Cognition later acquired the remaining company.
Key capabilities: AI coding assistants range from simple autocomplete functions to autonomous agents that can work independently for extended periods.
- Anthropic’s new Claude Sonnet 4.5 successfully coded autonomously for more than 30 hours on a project for iGent, a London-based startup, during testing.
- Stanford University researchers found AI tools could solve about 72% of coding problems by 2024, up from just over 4% a year earlier.
The vibe-coding phenomenon: The term was coined by prominent AI researcher Andrej Karpathy in February when experimenting with Cursor’s Composer tool and Anthropic’s Claude Sonnet.
- “There’s a new kind of coding I call ‘vibe coding’, where you fully give in to the vibes, embrace exponentials, and forget that the code even exists,” Karpathy wrote on X (formerly Twitter).
- “It’s not really coding – I just see stuff, say stuff, run stuff, and copy-paste stuff, and it mostly works.”
Usage patterns: Different AI platforms show varying user preferences for coding applications.
- Anthropic reports coding as Claude’s top use case at 39% of users, while OpenAI says writing is ChatGPT’s most common work task, with coding considered more “niche.”
- OpenAI introduced GPT-5-Codex in September to compete more directly in the coding space.
Job market implications: While AI coding tools raise concerns about job displacement, experts believe they will actually increase demand for skilled software engineers.
- “There’s so much software that isn’t created today because we can’t prioritize it,” Walsh said. “So it’s going to drive demand for more software creation, and that’s going to drive demand for highly skilled software engineers who can do it.”
- However, Stanford researchers found “substantial declines in employment for early-career workers” ages 22-25 in AI-exposed fields.
What they’re saying: Industry leaders emphasize that AI coding tools enhance rather than replace human expertise.
- Wu told her college-age sister that software engineering remains “a great career and worth studying,” noting that “AI will make you a lot faster, but it’s still really important to understand the building blocks because the AI doesn’t always make the right decisions.”
- Walsh stressed that “these tools reward highly skilled technical professionals who already know what ‘good’ looks like,” dismissing the idea that non-technical people can create business-ready software through vibe-coding.
AI is transforming how software engineers do their jobs. Just don't call it 'vibe-coding'