Prompting Your AI Agents Just Got 5X Easier...

David Ondrej
10 May 202419:55

TLDRAnthropic has introduced a new feature that promises to simplify prompt engineering by automating the creation of advanced prompts based on the latest principles, including the chain of thought. The tool allows users to input their desired prompt topic and generates a detailed prompt that can be used directly within the Anthropic console. The feature is particularly useful for beginners or those who are not professional prompt engineers, as it alleviates the challenge of starting from a blank page. The video also discusses the importance of providing ample context to the model, including expected input data and output format, to ensure optimal performance. The presenter demonstrates the feature by creating a prompt for summarizing community call transcripts, emphasizing the need for detailed task description and examples for the best results. The tool utilizes CL-free Opus and offers variations of the summary, which can be further refined by providing examples. This feature is considered a time-saver and a valuable starting point for building AI agents.

Takeaways

  • 🚀 Anthropic has released a new feature that simplifies prompt engineering by generating advanced prompts based on user-selected topics.
  • 📈 The feature uses the latest principles of prompt engineering, such as the chain of thought (CoT), and is accessible directly within the Anthropic console.
  • 🛠️ The tool is not just for developers; it offers a dashboard and workbench for model selection, temperature adjustment, and other settings.
  • 📚 The prompt generation is based on the Anthropic cookbook, a comprehensive resource for prompt engineering techniques.
  • 💡 For best results, describe the task in as much detail as possible, providing context for the model to generate a high-quality prompt.
  • 💳 Using the feature will consume a small number of Opus tokens, so it's recommended to set up billing to avoid any interruptions.
  • 📝 The system can generate prompts for various tasks, such as email drafting, content moderation, code translation, and product recommendation.
  • 🔍 The tool allows for customization of the prompt, including the input data expected and the desired output format.
  • 📉 The output is formatted into short, informative, and non-emotional paragraphs, with the option to generate multiple variations.
  • ✅ The generated prompt can be tested and refined within the workbench, with the ability to adjust parameters like temperature and token output.
  • 🔄 The feature addresses the 'blank page problem' by providing a structured starting point for prompt engineering, especially useful for beginners.

Q & A

  • What new feature did Anthropic release that could potentially change prompt engineering?

    -Anthropic released a feature that allows users to choose what they want the prompt to be about, and it automatically creates an advanced prompt using the latest prompt engineering principles, such as the chain of thought.

  • What is the purpose of the Anthropic console?

    -The Anthropic console is a tool that allows users to generate prompts, choose different models, adjust the temperature, and access settings for organization details, members, billing, and API keys.

  • What is the significance of the Anthropic Cookbook in prompt engineering?

    -The Anthropic Cookbook is a comprehensive resource for prompt engineering techniques and principles, and it was one of the main resources used in the 'Prompt Engineering 101' workshop.

  • Why is it important to provide detailed task descriptions when using the prompt generator?

    -Providing detailed task descriptions helps the model understand the context and expectations, which is crucial for generating high-quality prompts. It includes specifying the input data and the desired output format.

  • What is the role of the Opus tokens in using the prompt generator?

    -Each generation of a prompt consumes a small number of Opus tokens. Users are advised to set up billing and connect their credit card to avoid running into issues with token usage.

  • How does the prompt generator handle the creation of multiple variations of a summary?

    -The prompt generator can output four different variations of a summary, each including three unique paragraph graphs, by using variables and formatting instructions provided by the user.

  • What is the recommended writing tone for the output of the prompt generator?

    -The recommended writing tone for the output should be informative, descriptive, non-emotional, easy to understand, and inspiring the reader to engage further with the content.

  • How does the prompt generator use variables to improve the efficiency of prompt creation?

    -The prompt generator uses variables to separate parts of the prompt, allowing users to easily change specific elements without having to rewrite the entire prompt. This reduces the chance of errors and saves time.

  • What is the advantage of naming your prompts in the Anthropic console?

    -Naming your prompts allows for easier searchability within the console, helping users to quickly find and reuse previously created prompts.

  • How does the prompt generator assist users in overcoming the 'blank page problem'?

    -The prompt generator helps users start the process of prompt engineering by providing a structured and detailed template based on the user's input. This eliminates the difficulty of starting from scratch.

  • What is the potential impact of Anthropic's new feature on professional prompt engineers?

    -While the feature may not be revolutionary for professional prompt engineers, it can save time and streamline the process of creating prompts, especially for beginners or those who are not experts in prompt engineering.

Outlines

00:00

🚀 Introduction to Anthropic's New Prompt Engineering Feature

Anthropic has introduced a groundbreaking feature that aims to revolutionize prompt engineering. The feature allows users to input their desired prompt topic and automatically generates an advanced prompt that incorporates the latest principles of prompt engineering, such as the chain of thought (CoT). This tool is accessible directly within the Anthropic console, and the video provides a step-by-step demonstration on how to use it effectively. The console is not only for developers but also offers a dashboard and workbench for users to select different models, adjust temperature settings, and manage organization details, billing, and API keys. The video also mentions a discussion on open AI's desire to track GPUs and an invitation to Matthew Burman for a podcast interview on the topic. The experimental prompt generator is based on the Anthropic Cookbook, a leading resource for prompt engineering, and the video encourages viewers to join a community for further training on the subject.

05:00

📝 Creating a Detailed Prompt for Transcript Summarization

The video script delves into creating a detailed prompt for summarizing transcripts from community calls into short, free-form paragraphs without omitting technical terms. The speaker emphasizes the importance of providing as much detail as possible when describing the task to the AI, including the nature of the input data and the desired output format. The input data in this case is the raw transcript from a YouTube private video, which may lack formatting and contain grammatical errors. The desired output is a summary that focuses on the main topics discussed during the call, excluding member interactions and routine topics. The speaker also discusses the use of variables within the prompt to maintain clarity and order in the message chain and demonstrates how the new feature can optimize the prompt further.

10:02

🔧 Testing the Prompt in Anthropic's Workbench

The video script describes the process of testing the created prompt in Anthropic's workbench. The speaker names the prompt 'Cod Transcript Generator' and explains the importance of naming prompts for easy searchability. The workbench allows for adjusting the temperature setting, which controls the randomness of the output, and setting the maximum number of tokens to sample, which determines the response length. The speaker chooses a low temperature for accuracy and a small token output for brevity. The system generates four variations of the summary, each with three unique paragraph graphs, and the speaker notes that providing examples can further improve the output. The video also offers a tip for obtaining transcripts from YouTube videos and emphasizes the importance of saving work in the console to avoid losing progress.

15:04

🎓 Enhancing the Prompt with Examples and Final Thoughts

The video concludes with the speaker enhancing the prompt by adding examples of good transcript summaries. The speaker discusses the importance of providing examples to guide the AI and notes that three examples are usually sufficient unless there is a high degree of randomness or variety required. The speaker then runs the improved prompt and observes that the output is more in line with the provided examples and the desired writing style. The speaker corrects a minor error in the transcript provided by YouTube and integrates the improved prompt into a module. The video ends with the speaker's first impressions of the Anthropic feature, suggesting that while it may not be revolutionary, it can save time and help beginners and non-professional prompt engineers overcome the challenge of starting with a blank page. The speaker encourages viewers to subscribe for more content.

Mindmap

Keywords

💡Anthropic

Anthropic is a company mentioned in the script that has released a new feature aimed at improving prompt engineering. It is associated with AI development and is the context in which the video's discussion about prompt generation takes place. The script refers to 'Anthropic console' and 'Anthropic cookbook', indicating that the company provides tools and resources for AI prompt engineering.

💡Prompt Engineering

Prompt engineering is the process of designing and refining the input prompts given to AI systems to elicit desired responses. In the video, it is central to the discussion as the new feature by Anthropic is designed to make this process easier and more efficient. The script mentions 'advanced prompt' and 'chain of thought' as part of the prompt engineering techniques.

💡Chain of Thought (CoT)

Chain of Thought, or CoT, is a technique in prompt engineering that involves guiding the AI through a logical sequence of steps to reach an answer. The script highlights that the new feature by Anthropic incorporates CoT principles to create better prompts, which is crucial for generating more accurate and detailed responses from AI systems.

💡Console

In the context of the video, a console refers to a user interface where commands are input and results are displayed. The 'Anthropic console' is mentioned as a platform where users can utilize the new prompt engineering feature to generate advanced prompts directly.

💡Temperature

In the context of AI models, 'temperature' is a parameter that controls the randomness of the model's output. A lower temperature results in more deterministic and predictable responses, while a higher temperature allows for more variability. The script discusses adjusting the temperature when using the Anthropic console for generating prompts.

💡API Keys

API Keys are unique identifiers used to authenticate requests to an application programming interface (API). In the video, they are mentioned in the context of setting up the Anthropic console, where users need to adjust settings including organization details and API keys to use the platform's features.

💡Content Moderation

Content moderation is the process of reviewing and filtering user-generated content to ensure it meets certain guidelines or standards. In the script, it is one of the examples given for how the new feature can be used to generate prompts, specifically for classifying chat transcripts into categories.

💡Product Recommendation

This refers to the process of suggesting products to users based on certain criteria or preferences. In the video, it is mentioned as another example of a task for which the new prompt engineering feature can generate effective prompts.

💡Summarization

Summarization is the process of condensing a longer piece of text into a shorter, more concise version while retaining the main points. The script discusses using the new feature to create prompts for summarizing documents, which is a common task in AI applications.

💡Variables

In the context of the video, variables are placeholders used in the prompt that can be customized by the user. They are mentioned as a way to make prompt engineering more efficient, as they allow for easy modification of prompts without having to rewrite the entire prompt.

💡LLMs (Large Language Models)

Large Language Models, or LLMs, are AI models designed to process and understand large volumes of natural language data. The script refers to 'Opus', which is an example of an LLM, and discusses its use in generating prompts and the associated costs.

Highlights

Anthropic has released a new feature that could revolutionize prompt engineering.

The feature allows users to choose the topic for their prompt and generates an advanced prompt using the latest prompt engineering principles.

It integrates directly with the Anthropic console, making it easy to use for developers and non-developers alike.

The tool is based on the Anthropic Cookbook, a leading resource in prompt engineering.

Users can adjust the temperature setting to control the randomness of the generated prompt.

The experimental prompt generator can turn a task description into a high-quality prompt for various applications.

Giving the model enough context is crucial for it to perform well, especially for beginners.

The feature consumes a small number of Opus tokens, so users should set up billing to avoid issues.

Examples provided in the transcript demonstrate how to use the feature for tasks like email drafting, content moderation, and product recommendation.

The system prompt is generated from a short and concise user input, utilizing prompt engineering techniques.

Users can write their own prompts or use the generated ones, with the option to include detailed instructions and examples.

The workbench allows users to test out the generated prompts and provides options to name and save them for future use.

The generated prompt can be fine-tuned by adjusting settings like temperature and token output.

The feature offers four different variations of a summary for a more comprehensive output.

Including examples in the prompt can lead to better and more accurate outputs.

The tool can be particularly useful for beginners and those who are not professional prompt engineers, saving them time and effort.

The feature helps overcome the 'blank page problem' often faced when starting to write a prompt from scratch.

The generated prompts are informative, descriptive, and non-emotional, making them suitable for a variety of professional uses.

Users can edit and refine the generated prompts to better fit their specific needs and preferences.

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