Coding agents really did change everything. These are tools which burn vastly more tokens, but are also quickly becoming daily drivers for the work carried out by extremely well-compensated professionals.
大多数人认为ChatGPT等通用AI助手已经实现了产品市场契合，但作者认为真正带来商业突破的是代码编写代理工具。这一观点挑战了主流认知，因为ChatGPT拥有数亿用户，而作者认为只有专业领域的代码代理才能创造足够的收入来支撑AI公司的巨额基础设施成本。
blogger Fabrizio Ferri Benedetti on their 4 modes of using AI in technical writing. - watercooler conversations, to get code explained - text suggestions while writing/coding (esp for repeating patterns in your work - providing context / constraints / intent to generate first drafts, restructure content, or boilerplate commentary etc. - a robotic assembly line, to do checks, tests and rewrites. MCP/skills involved.
I love the asynchronous coding agent category. They’re a great answer to the security challenges of running arbitrary code execution on a personal laptop and it’s really fun being able to fire off multiple tasks at once—often from my phone—and get decent results a few minutes later.
async coding agents: prompt and forget
coding agents—LLM systems that can write code, execute that code, inspect the results and then iterate further.
author def of coding agents