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.

ZW

Zack Witten

09/06/24

@ Anthropic

The engineering aspect of prompt engineering comes from the ability to experiment and iterate on prompts without interference, allowing for systematic improvements.

A

Anthropic Cast

09/06/24

@ Anthropic

Integrating prompts within a system is complex; it's not just about writing a single prompt but considering how it fits into the overall architecture.

AA

Amanda Askell

09/06/24

@ Anthropic

A good prompt engineer must communicate clearly, iterate on prompts, and anticipate potential misinterpretations by the model.

AA

Amanda Askell

09/06/24

@ Anthropic

It's crucial to think about edge cases when designing prompts, ensuring they work not just for typical scenarios but also for unusual inputs.

A

Anthropic Cast

09/06/24

@ Anthropic

Reading model outputs closely is essential; it helps identify misunderstandings and refine prompts for better performance.

A

Anthropic Cast

09/06/24

@ Anthropic

A good prompt engineer should be able to step back from their own knowledge and communicate the necessary information clearly to the model.

A

Anthropic Cast

09/06/24

@ Anthropic

The best prompting can significantly impact the success of an experiment, sometimes making the difference between marginal and substantial model performance.

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.

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.

A

Anthropic Cast

09/06/24

@ Anthropic

When prompting, it's important to give the model an 'out' for unexpected inputs, allowing it to indicate uncertainty when necessary.

A

Anthropic Cast

09/06/24

@ Anthropic

It's important to evaluate prompts by testing them in real scenarios, as this can reveal flaws in the prompt design that need addressing.

A

Anthropic Cast

09/06/24

@ Anthropic

The outcome is better if you structure the reasoning and help iterate with the model on how it should do reasoning.

A

Anthropic Cast

09/06/24

@ Anthropic

Structuring the reasoning in prompts helps the model perform better, even if it's not strictly reasoning as we define it.

A

Anthropic Cast

09/06/24

@ Anthropic

In research prompts, I often include many examples to ensure the model can explore a wide range of possibilities, while in consumer applications, I focus on reliability and consistency.

A

Anthropic Cast

09/06/24

@ Anthropic

When prompting, I try to give examples that are not too similar to the data the model will see, to avoid overly consistent responses.

A

Anthropic Cast

09/06/24

@ Anthropic

Reading prompts and model outputs closely helps improve prompting skills; experimentation is key.

A

Anthropic Cast

09/06/24

@ Anthropic

Giving your prompt to someone without context can help you see if it's clear and effective.

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.

A

Anthropic Cast

09/06/24

@ Anthropic

The future of prompting may involve more guided interactions with the model, rather than just typing into a text box.

A

Anthropic Cast

09/06/24

@ Anthropic

The skill of prompting is about introspection, understanding what you want, and making yourself legible to the model.

A

Anthropic Cast

09/06/24

@ Anthropic

I often define new concepts when prompting to convey nuanced ideas clearly to the model.

A

Anthropic Cast

09/06/24

@ Anthropic

In the future, prompting may involve the model eliciting information from us rather than us having to specify everything.

AI prompt engineering: A deep dive

Takeaways