May 4, 2026 · 20 min · 14 segments
Just like a memorable talk lives or dies by its opening and closing, LLMs have a surprisingly similar quirk: they pay close attention to what's at the beginning and end of their context window — and…
When I was a young scientist and I was learning how to give a good talk, I got some advice, and it was, "Have a good intro and have a good ending, and don't worry too much about what happens in the middle." Like, it matters, don't get me wrong, but if you're really gonna focus on some place, make it the beginning and the end, because that's what people are gonna remember.
And the stuff in the middle, you can kind of just get away with being a little more loosey-goosey.
And I was thinking about that as I was preparing for what we're gonna talk about today, because LLMs are kind of the same way.
In this episode, we're going to explore a really interesting phenomenon on how attention works with long context windows.
This is the third in our season-long arc about AI agents, so we are gonna tie it back to the specific implications that it has for AI agents, but this is an idea and a topic that I think even without that agentic motivation is just really interesting and cool, and so I'm excited to talk to you about it.
Today's episode is about lost in the middle: how models do and don't use context.
You're listening to Linear Digressions.
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When I was a young scientist and I was learning how to give a good talk, I got some advice, and it was, "Have a good intro and have a good ending, and don't worry too much about what happens in the middle." Like, it matters, don't get me wrong, but if you're really gonna focus on some place, make it the beginning and the end, because that's what people are gonna remember.
And the stuff in the middle, you can kind of just get away with being a little more loosey-goosey.
And I was thinking about that as I was preparing for what we're gonna talk about today, because LLMs are kind of the same way.
In this episode, we're going to explore a really interesting phenomenon on how attention works with long context windows.
This is the third in our season-long arc about AI agents, so we are gonna tie it back to the specific implications that it has for AI agents, but this is an idea and a topic that I think even without that agentic motivation is just really interesting and cool, and so I'm excited to talk to you about it.
Today's episode is about lost in the middle: how models do and don't use context.
You're listening to Linear Digressions.
