这是我们系列文章的一部分，分享OpenAI如何使用其自身技术和API的内部示例。这些工具正在OpenAI内部使用，并在此分享作为前沿AI如何支持我们各团队用例的说明性示例。
Ultrafast是Codex中的一种高速模式，对于OpenAI的工程师来说，它已成为事件响应的默认选择。当出现故障时，工程师们往往没有时间等待几分钟才能得到答案，而问题却在不断加剧。借助Ultrafast，他们可以同时调查多个潜在原因并获取答案，而无需分散注意力。
大海捞针
Aaron Friel是OpenAI的技术人员，通常是事件响应的负责人。他会创建一个Slack频道用于事件响应，然后将Codex指向问题，要求Codex监控、调查并随时回答出现的问题。“在任何事件中，可能出错的地方通常有很多环节，而在正确的大海捞针中找到正确的那根针，确实是该频道上人员的主要工作，”他说。“使用Ultrafast，我基本上能够同时搜索所有这些大海捞针，并更快地响应事件。”
AJ Trbojevic是技术人员兼数据中心安全架构师，他说过去对安全问题的调查需要一两个小时来汇集结构化和非结构化数据、对其进行规范化并提供上下文以做出决策。“现在这只需10到15分钟，”他说。“有时甚至接近实时。”
Adam Perry和Sayan Sisodiya都在核心智能体团队工作，构建让Codex采取行动、运行命令和使用工具的代码。Ultrafast改变了他们在安全事件期间的运作方式。“以前，我会让Codex调查某事，然后同时自己去调查，因为我知道光等着它不够快，”Adam说。“现在有了Ultrafast，Codex足够快，我可以保持专注，而不必分散注意力。”
Sayan很欣赏Ultrafast让他能够从多个数据源立即获得答案：“除了在事件中挖掘日志之外，我还使用Codex挖掘Slack，看看是否有对可疑更改的引用，或者有人在Slack其他地方谈论类似症状，”他说。
30秒内快速响应
Jeff Niu是另一位技术人员，他说如果用AI找答案需要超过30秒，他会查看Slack或与同事聊天。但借助Ultrafast，他现在的大部分工作都在这个阈值以下。他过去会向Codex提问，在它思考时切换到其他事情，回来时已经失去了思路。现在这种对话是实时进行的；这有助于他保持对当前任务的专注。
Ultrafast还让Jeff更愿意处理大型重构，因为重写现有代码花费的时间更少。“技术债务现在比以往任何时候都更容易偿还，”他说。“代码很便宜，而且现在生成速度非常快。过去需要花费大量成本的重构几乎瞬间完成。”
作为副驾驶工作
Adam保持着一个持续的Codex线程，他称之为他的幕僚长。每天早上它会告诉他有哪些会议以及他可能忘记回复哪些消息。“它已经查看了所有数据来撰写该摘要，所以当我提出后续问题时，它不会等待去获取更多信息，”他说。“我可以像与真正的幕僚长一样在同一对话中继续提问。”
Sayan使用Codex在浏览器中做繁琐的手动工作，比如填写表单——这是他以前因为太慢而避免的事情。“它会打开浏览器，在那里思考五秒钟，点击某物，再次在那里等待，”他说。随着最新模型在计算机使用方面的改进，他更放心让Codex处理这些工作。“现在我完全可以让它点击浏览浏览器，而且它足够快，我不会因为不自己做而浪费时间。”
在事件响应、日常规划和重构中，Ultrafast让OpenAI的技术人员能够以他们提问的节奏与Codex协作。他们可以跟进一个答案、尝试另一种方法，并保持工作而不失去思路。更短的等待时间也改变了他们愿意承担的工作，从他们一直推迟的重构到终于值得委托的常规任务。
This is part of our series sharing internal examples of how OpenAI is using its own technology and APIs. These tools are being used internally, at OpenAI, and are shared here as illustrative examples of how frontier AI is supporting use cases across our teams.
Ultrafast is a high-speed mode in Codex, and for engineers at OpenAI, it’s become the default for incident response. When something breaks, engineers often don’t have time to wait minutes for an answer while the issue compounds. With Ultrafast, they can investigate multiple potential causes at once and get answers without splitting their attention.
Finding the needle in the haystack
Aaron Friel, Member of the Technical Staff at OpenAI, is usually the one running point on an incident. He spins up a Slack channel for incident response and then points Codex at the problem, asking Codex to monitor, investigate, and answer any questions as they come in. “In any incident, there are usually many hops along the way of what could have gone wrong, and finding the right needle in the right haystack is really the chief job of the people on that channel,” he says. “Using Ultrafast, I’m able to essentially search all of those haystacks at the same time, and respond to incidents much faster.”
AJ Trbojevic, Member of the Technical Staff and a Datacenter Security Architect, says investigations into security issues used to take an hour or two to pull structured and unstructured data together, normalize it, and provide context to make a decision. “Now that happens in 10 to 15 minutes,” he says. “And at times it’s near real time.”
Adam Perry and Sayan Sisodiya both work on the core agent team, building the code that lets Codex take actions, run commands, and use tools. Ultrafast has changed how they operate during security incidents. “Before, I’d ask Codex to look into something, and then go look into it myself at the same time, because I knew it wouldn’t be fast enough to just wait on,” Adam says. “Now with Ultrafast, Codex is fast enough that I can just stay focused instead of splitting my attention.”
Sayan appreciates how Ultrafast lets him get immediate answers from multiple data sources: “Beyond just digging through logs in an incident, I use Codex to dig through Slack to see if there are references to changes that might be suspect or people talking about similar symptoms elsewhere in Slack,” he says.
Fast responses in under 30 seconds
If it takes more than 30 seconds to find an answer with AI, Jeff Niu, another Member of the Technical Staff, says he’ll check Slack or chat with a coworker. But most of his work is now under that threshold with Ultrafast. He used to ask Codex a question, switch over to something else while it thought, and come back having lost his train of thought. Now that conversation happens in real time; it helps him stay focused on the task at hand.
Ultrafast also makes Jeff more willing to tackle large refactors, because reworking existing code takes less time. “Technical debt is much easier to pay down now than it ever was before,” he says. “Code is cheap, and now it’s very quick to produce. A refactor that used to cost a lot happens almost instantly.”
Working as a copilot
Adam keeps a running Codex thread that he calls his chief of staff. Every morning it tells him what meetings he has and which messages he might have forgotten to reply to. “It’s already looked at all the data to write that summary, so when I ask a followup, it’s not waiting to go fetch more,” he says. “I can just keep asking questions in the same conversation just like an actual chief of staff.”
Sayan uses Codex to do tedious manual work in the browser, like filling out forms—something he’d previously avoided because it was too slow. “It would open a browser, sit there thinking for five seconds, click something, sit there again,” he says. With the latest models’ improvements in computer use, he’s more comfortable letting Codex handle that work. “Now I’m totally fine letting it click through the browser and it’s fast enough that I’m not losing time by not doing it myself.”
Across incident response, daily planning, and refactoring, Ultrafast lets OpenAI’s Technical Staff work with Codex at the pace of their questions. They can follow up on an answer, try another approach, and keep working without losing their train of thought. That shorter wait also changes what they’re willing to take on, from a refactor they’d put off to a routine task that’s finally worth delegating.
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