Today on the AI Daily Brief, a primer in using the slash goals primitive in codex and cloud code and how to use it to level up your use of AI.

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Today we're talking about something that a lot

of power users of AI are incredibly excited about, which is slash goals. So let's dive in.

Today we were doing another very operator-centric episode. Recently, I did a show about

codex maxing, effectively a set of tips and best practices on how to get the most out of OpenAI's codex.

Now, in many ways, while that episode was specific to Codex itself, a lot of the interaction patterns,

you could also follow in other harnesses like ClaudeCode.

The codex maxing piece was built off of a blog post by OpenAI's Jason Liu.

Jason wrote up about nine techniques or interaction patterns that he had discovered

allowed him to get the most out of codex, not just for coding but for other types of knowledge work as well.

And some of those tips represented fairly different types of patterns.

One of them, for example,

is the idea of durable threads or mono threads, where instead of using some sort of infrastructure

like a project, where you have multiple threads all related to the same topic that share a memory

base, you instead use a single thread relying on the harness's compaction tool to make sure it

always preserves the relevant context.

You also saw in that codex maxing post a number of ideas about how to effectively reduce the latency between the human providing guidance to the model and the model getting

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