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Andrew Lee

Published podcast speaker

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Anthropic

“In the case of Anthropic, we're using five-minute caching, and so it doesn't stick around very long.”

The Cognitive Revolution · 15 May 2026

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What Andrew said.

9 transcript-backed records

01 / belief

I think the value of being a system of record in a world where you have agents goes down a lot because like moving data around between systems suddenly gets a lot easier.

“I think the value of being a system of record in a world where you have agents goes down a lot because like moving data around between systems suddenly gets a lot easier.”
Speaker
Andrew Lee
Publisher
The Cognitive Revolution

02 / belief

I agree with that, and I think that trend is going to continue. But I also think the effects are multiplicative, and they're orthogonal disciplines, and there's no reason not to take the best model and put in the best harness, and I think we should.

“I agree with that, and I think that trend is going to continue. But I also think the effects are multiplicative, and they're orthogonal disciplines, and there's no reason not to take the best model and put in the best harness, and I think we should.”
Speaker
Andrew Lee
Publisher
The Cognitive Revolution

03 / belief

I think the harnesses are also kind of converging in terms of capabilities, and largely that's because it turns out the best harness is just through low-level primitives.

“I think the harnesses are also kind of converging in terms of capabilities, and largely that's because it turns out the best harness is just through low-level primitives.”
Speaker
Andrew Lee
Publisher
The Cognitive Revolution

04 / belief

There are some changes that we can make to do a lot of cash optimization across agents and potentially even across organizations and users. And I don't want to get into the specifics of that because that's still upcoming, but I think there's a lot of potential actually to save money across agents as well.

“There are some changes that we can make to do a lot of cash optimization across agents and potentially even across organizations and users. And I don't want to get into the specifics of that because that's still upcoming, but I think there's a lot of potential actually to save money across agents as well.”
Speaker
Andrew Lee
Publisher
The Cognitive Revolution

05 / belief

We have lots of ideas how to improve this, but the basic approach of this decreasing fidelity as you go back and these bucketed cache-aware chunks, I think is the right approach.

“We have lots of ideas how to improve this, but the basic approach of this decreasing fidelity as you go back and these bucketed cache-aware chunks, I think is the right approach.”
Speaker
Andrew Lee
Publisher
The Cognitive Revolution

07 / belief

There's going to be the horizontal platforms, of which I think there'll be a very few winners because people don't want to have to maintain context and connection across a bunch of platforms.

“There's going to be the horizontal platforms, of which I think there'll be a very few winners because people don't want to have to maintain context and connection across a bunch of platforms.”
Speaker
Andrew Lee
Publisher
The Cognitive Revolution

08 / belief

I think ideally as little as possible because we want to support a lot of models and like it's hard to have a thing that, you know, It's hard to maintain across both balls, but we also want to have the ability for these agents to switch between models.

“I think ideally as little as possible because we want to support a lot of models and like it's hard to have a thing that, you know, It's hard to maintain across both balls, but we also want to have the ability for these agents to switch between models.”
Speaker
Andrew Lee
Publisher
The Cognitive Revolution

09 / belief

The naive way to do this is to like load that data through an API, feed it into the LLM, have the LLM then like call some tools to put it somewhere else. And basically, when you do that every time, you're putting it through language model context and trusting it to not hallucinate and reproduce that data, which I think the models get better at over time, but it's very hard to have a lot of confidence there.

“The naive way to do this is to like load that data through an API, feed it into the LLM, have the LLM then like call some tools to put it somewhere else. And basically, when you do that every time, you're putting it through language model context and trusting it to not hallucinate and reproduce that data, which I think the models get better at over time, but it's very hard to have a lot of confidence there.”
Speaker
Andrew Lee
Publisher
The Cognitive Revolution
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