One of my favorite sources of interesting things to write about is conversations that I have with my cofounders. Here’s a pretty cool insight that came from Brandon, Founding Partner at Legible, that suggests that mining AI chats between humans and AI might be as valuable as mining transcripts between humans.

“I have conversations with AI agents all day. What I share with the team is the result. It’s like sitting in meetings all day and only passing along the summary.”

His point: the journey that brought him to the summary gets lost. The reasoning, the dead ends, the ideas that went untouched.

So he built himself a workflow. Every evening, a job runs over all of his AI conversations from the day and summarizes them: what he worked on, what he learned, what might be worth sharing with the team. He’s mining his own chat logs.

Of course, we’ve seen this movie before. For decades, the knowledge in live meetings simply evaporated the moment everyone left the room. Then AI notetakers exploded, because companies realized how much thinking was buried in those conversations. Memorializing human-to-human conversation went from novelty to standard practice in about three years.

The same realization is coming for human-to-AI conversation.

Chat threads are the next transcripts.

The thinking that goes into a Claude or ChatGPT session is real work: framing problems, weighing options, making calls. Today almost none of it is remembered by anyone. Even the AI forgets it across threads.

At Legible we call the answer a Shared Brain: team memory that captures the important thinking wherever it happens, in meetings or in chat. Clearly, we need to be thinking more about pulling in the human to AI transcripts, and not just the human to human ones.

Your team is already doing its best thinking with AI. Do you have a plan to memorialize that knowledge?