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YC

Y Combinator Cast

05/30/25

@ Y Combinator

In prompt engineering, it's crucial to provide examples of desired outputs, as this helps the AI reason through complex tasks and improves the overall quality of its responses.

Video

State-Of-The-Art Prompting For AI Agents

@ Y Combinator

State-Of-The-Art Prompting For AI Agents

05/30/25

Related Takeaways

Sander Schulhoff

06/19/25

@ Lenny's Podcast

Providing additional information and examples significantly improves the results in conversational prompt engineering.

Y Combinator Cast

05/30/25

@ Y Combinator

When prompts become too complex, using examples can be more effective than trying to articulate every detail in prose, similar to test-driven development in programming.

Paul Buchheit

01/25/25

@ Y Combinator

The ability to prompt AI effectively is crucial, as it determines the quality of the output, which is a reflection of agency and taste in AI development.

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.

Y Combinator Cast

05/30/25

@ Y Combinator

Effective prompts often start by defining the role of the AI, detailing its responsibilities, and providing a structured plan for tasks, which helps in guiding the AI's decision-making process.

Y Combinator Cast

02/28/25

@ Y Combinator

The prompt box in AI interfaces is crucial, and providing pre-built prompts can enhance user experience by guiding them in their input.

Y Combinator Cast

02/09/24

@ Y Combinator

Developer tools for prompt engineering are gaining traction, allowing users to chain prompts and test their effectiveness, which is appealing to college students experimenting with AI.

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.

Amanda Askell

09/06/24

@ Anthropic

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