Greg Brockman· @gdb · X·· 2026-05-16AI 评分48
AI 导读
在“tokens成本无关紧要”的未来设想下,项目通过云端持续运行约100个Codex实例,实现软件开发全流程自动化。系统自动化审查每次代码提交以发现安全问题,处理所有PR和issue:自动关联并关闭陈旧issue、去重问题并聚类报告、监控新issue并自动创建PR。智能代理能复现复杂环境、进行演示、监听会议并主动启动工作(如创建PR),同时扫描评论垃圾、验证性能基准。结合clawpatch.ai进行功能单元拆分和Vercel deepsec安全审计,最终达成极精简的自动化运营。
正文 · 原文
run codex on every commit
People freaking out over my AI spend. What nobody sees: Part of what excites me so much about working on OpenClaw is that I'm trying to answer the question: How would we build software in the future if tokens don't matter? We constant run ~100 codex in the cloud, reviewing every PR, every issue. If a fix on main lands, @clawsweeper will eventually find that 6 month old issue and close it with an exact reference. We run codex on every commit to review for security issues (as it's far too easy to miss). We run codex to de-duplicate issues and find clusters and send reports for the most pressing issues. We have agents that can recreate complex setups, spin up ephemeral http://crabbox.sh machines, log into e.g. Telegram, make a video and post before/after fix on the PR. There's codex that watch new issues and - if it fits our documented vision well, automatically create a PR of it. (that then another codex reviews) We have codex running that scans comments for spam and blocks people. We have codex instances running that verify performance benchmarks and report regressions into Discord. We have agents that listen on our meetings and proactively start work, e.g. create PRs when we discuss new features while we discuss them. We build http://clawpatch.ai to split all our projects into functional units to review and find bugs and regresssions. We do the same split for security with Vercel's deepsec and Codex Security to find regressions and vulnerabilities. All that automation allows us to run this project extremely lean.在 X 查看被引用的帖子
来源:Greg Brockman · x.com