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Atmrix

About

A

Anthropic Cast

09/06/24

@ Anthropic

Treating the model as capable and giving it complex instructions can lead to better outcomes than simplifying the task.

Video

A

AI prompt engineering: A deep dive

@ Anthropic

09/06/24

Related Takeaways

AA

Amanda Askell

09/06/24

@ Anthropic

As models improve, it's often more effective to communicate the specific task directly rather than using metaphors or role-based prompts.

A

Anthropic Cast

04/24/25

@ Anthropic

There's a risk of overcomplicating prompts by trying to anticipate every possible issue the model might face, which can lead to ineffective results.

DP

Dwarkesh Patel Cast

05/23/25

@ Dwarkesh Patel

We often underutilize models, expecting them to solve tasks quickly without giving them enough time to iterate and improve.

TB

Trenton Bricken

05/23/25

@ Dwarkesh Patel

The challenge of reducing 'slop' in model outputs involves teaching models to produce more elegant and effective solutions, especially in coding.

AA

Amanda Askell

09/06/24

@ Anthropic

Using clear, prescriptive language about the task at hand is more effective than relying on vague role-based instructions.

YC

Y Combinator Cast

09/22/23

@ Y Combinator

To achieve complex tasks with AI, it's important to provide structured prompts and specific tasks, allowing the AI to perform effectively.

YC

Y Combinator Cast

05/30/25

@ Y Combinator

Using a larger model for meta prompting can yield better prompts that are then distilled into smaller models for practical use.

ZW

Zack Witten

09/06/24

@ Anthropic

Prompt engineering is about getting the model to perform tasks effectively by clear communication and understanding the model's psychology.

TB

Trenton Bricken

05/23/25

@ Dwarkesh Patel

The distinction between how models claim to perform tasks and how they actually do them can reveal significant insights into their capabilities.