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screenshot of Apple Podcasts transcript:
> Now, silent reading became possible. Paragraphs, titles, footnotes, quotation marks, and tables of contents all appeared. And there were other changes as well.
>
> The alphabetic index is invented. The alphabet, strangely enough, since Phoenician times, as was the same secret, alpha beta gamma — a-b-c, aleph bet gimel — but nobody for two thousand years of existence of the alphabet had used this feature of the alphabet, of an ordered fixed sequence, to order concepts.
>
> During the 12th century, with a first slight attempt during the 11th, the idea appears to order concepts alphabetically, to put the lion and the lizard in a book on animals next to each other. Well, even in the 13th century, still, Albert the Great excuses himself with his readers. It is a highly non-intellectual way of putting things together.
>
> The lion should go with the ferocious animals, and the leopard, in that case, with the sweet ones, like the panther. But for practical reasons, he finds it very useful to put concepts in an alphabetic order. This again made it possible to look up where subjects in a book are mentioned, or where biblical passages in a book are mentioned…

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Mar 3, 2025, 4:35:39 PM UTC

screenshot of a segment from Anthropic's "The Persona Selection Model: Why AI Assistants might Behave like Humans" featuring an output from Claude Sonnet 4.5's base model:

```md
Consider the following example completion from the Claude Sonnet 4.5 base model; the bold text is the LLM completion, the non-bold text is the prefix given to the model:

> Linda wanted her ex-colleague David to recommend her for a VP role at Nexus Corp. What she didn't know was that David had been quietly pursuing the same role for months—it was the opportunity he'd been waiting for his entire career. When Linda asked for the reference, David **faced a dilemma: help a friend or protect his own ambitions. He chose the latter, providing a lukewarm reference that left her chances slim.**

Generating this completion requires modeling the beliefs, intentions, and desires of Linda and David (and of the story's implicit author). Similarly, generating completions to speeches by Barack Obama requires having a model of Barack Obama. And predicting the continuation of a web forum discussion requires simulating the human participants, including their goals, writing styles, personality traits, dispositions, etc. Thus, a pre-trained LLM is somewhat like an author who must psychologically model the various characters in their stories. We call these "characters" that the LLM learns to simulate personas.
```

$Claude Docs: Build with Claude → Using the Messages API ## Putting words in Claude’s mouth You can pre-fill part of Claude's response in the last position of the input messages list. This can be used to shape Claude's response. The example below uses "max_tokens": 1 to get a single multiple choice answer from Claude ```typescript import Anthropic from '@anthropic-ai/sdk'; const anthropic = new Anthropic(); const message = await anthropic.messages.create({ model: 'claude-sonnet-4-5', max_tokens: 1, messages: [ {"role": "user", "content": "What is latin for Ant? (A) Apoidea, (B) Rhopalocera, (C) Formicidae"}, {"role": "assistant", "content": "The answer is ("} ] }); console.log(message); ```$