How to Create and Use Perplexity Personal AI Chatbot Agents! #95

Josh Evilsizor
12 Feb 202417:37

TLDRIn this informative video, Josh Evilsizer introduces the concept of Perplexity agents, which are reusable and refinable quick access prompts saved as collections. He demonstrates how to create, use, and edit these agents to streamline chatbot interactions and save time. Josh provides practical examples such as language learning, weather updates, video brainstorming, and data analysis, showcasing the versatility of Perplexity agents in various applications. The video emphasizes the benefits of reusing and refining prompts for improved efficiency and results.

Takeaways

  • 📚 Perplexity agents are reusable, refinable quick access prompts saved as collections, acting like pre-prompted chatbots for efficient interactions.
  • 🎯 To create a collection, click on the library, then the plus sign, and follow the steps to title, icon, describe, and set up the agent for specific tasks.
  • 👤 Give your collection a meaningful title and icon that resonates with its purpose for quick identification and use.
  • 📝 In the description, provide detailed steps for future use, ensuring that you or others can understand and follow the instructions easily.
  • 🔧 Edit or delete collections by accessing the library, selecting the collection, and using the provided options for adjustments.
  • 🌟 Share your collections with others by making them sharable, allowing for collaboration and knowledge transfer.
  • 🗣️ Use cases include language proficiency practice, weather updates, and video brainstorming, demonstrating versatility in various applications.
  • 🔄 Refine and reuse prompts over time to improve their effectiveness and achieve better results with each iteration.
  • 💡 The rewrite function in Pro mode allows for different chatbot outputs based on the same prompt, offering varied perspectives.
  • 📊 For data analysis tasks, agents can streamline the process of analyzing datasets by focusing on specific variables and providing statistics and visualizations.
  • 🏦 Perplexity collections save time by eliminating the need to rewrite prompts, allowing users to focus on more important tasks and improve productivity.

Q & A

  • What are perplexity agents according to the video?

    -Perplexity agents are reusable, refinable, quick access prompts saved as collections. They can be thought of as pre-prompted chatbots that are ready to respond to specific needs or tasks repeatedly.

  • How do you create a collection in Perplexity?

    -To create a collection, you click on the 'library', then click on the plus sign to create a new collection. You provide a meaningful title, an emoji that resonates with the purpose of the collection, and a detailed description including steps on how to use the collection.

  • What is the purpose of the 'Spanish proficiency agent' example shown in the video?

    -The 'Spanish proficiency agent' is designed to help improve or adhere to the user's current level of Spanish speaking proficiency. It prompts the user to have a conversation in beginner Spanish and provides feedback in English to aid improvement.

  • How can you edit an existing perplexity agent or collection?

    -To edit an existing agent or collection, you go to the 'library', select the collection, click on the three dots at the top, and choose 'edit collection'. All the fields filled out earlier are available for editing.

  • What is the 'Al Roker' example in the video used for?

    -The 'Al Roker' example is a simple agent that provides a weather forecast for a given location in a fun and whimsical manner, along with a related famous quote. It's used to demonstrate how agents can be personalized and used for specific, repetitive tasks.

  • How does the 'video brainstorming' agent work?

    -The 'video brainstorming' agent takes on the persona of an efficiency-focused productivity expert and generates video ideas based on a given topic and instructions. It produces an outline using a script formula and associated processes or habits to maximize efficiency and effectiveness.

  • What is the advantage of using the rewrite function in Perplexity?

    -The rewrite function allows users to get different answers from different chatbots without bumping into concerns related to tokens or context window. This feature is available in Pro mode and helps refine and improve the results over time.

  • How can you reuse a perplexity collection?

    -You can reuse a perplexity collection by clicking on the 'library', selecting the collection, and then starting a new query or selecting an old thread to continue from. This enables users to refine and perfect their prompts for consistent, superior results.

  • What is the main benefit of using perplexity collections?

    -The main benefit of using perplexity collections is saving time by streamlining chatbot interactions and reusing, refining, and perfecting prompts to achieve better results with each use.

  • How does the video emphasize the importance of refining and reusing prompts?

    -The video emphasizes that refining and reusing prompts can lead to superior results over time. By saving well-crafted prompts as collections, users can avoid rewriting them repeatedly, which ultimately saves time and improves efficiency.

  • What is the 'initial descriptive statistics on the variables' example about?

    -The 'initial descriptive statistics on the variables' example demonstrates how a data analyst can use a perplexity agent to quickly analyze data sets by uploading a CSV file and receiving mean, median, min, max, quantiles, and a visualization of the distributions of key variables.

Outlines

00:00

🤖 Introduction to Perplexity Agents

Josh Evilsizer introduces the concept of Perplexity Agents, which are reusable, refinable, and quick access prompts saved as collections. He emphasizes the efficiency and time-saving aspect of these agents, comparing them to pre-prompted chatbots ready for specific tasks. Josh guides the viewer through creating a 'Spanish Proficiency Agent', detailing the process of naming, icon selection, and description for easy future use. He also explains the importance of iterating prompts for perfection and shares his personal experience with the creation process.

05:01

📝 Editing and Using Perplexity Agents

The segment focuses on how to edit pre-existing Perplexity Agents for improved use. Josh demonstrates the process of accessing the library, selecting a collection, and making edits to the agent's title, icon, and description. He also covers the option to delete or share collections. Josh provides examples of different agents, such as the 'Al Roker' weather forecasting agent and explains how these agents can be customized and re-used for various tasks, emphasizing the adaptability and practicality of Perplexity Agents.

10:03

🎯 Advanced Prompts and Rewriting Functions

Josh explores more advanced uses of Perplexity Agents, specifically focusing on video brainstorming. He outlines the creation of an agent that generates video ideas based on a given topic, and details the structure of the AI prompt used. Josh also discusses the Pro mode's rewrite function, which allows for different chatbots to provide varied responses to the same prompt. He illustrates how this function can be used to refine and improve the output of agents over time, showcasing the potential for continuous improvement and adaptation of Perplexity Agents.

15:03

📊 Data Analysis with Perplexity Agents

In this part, Josh explains how Perplexity Agents can be utilized in data analysis. He presents an example of an agent designed to perform initial descriptive statistics on variables from a CSV file. Josh walks through the process of uploading data, specifying focus areas, and obtaining statistical insights and visualizations. He highlights the efficiency of using agents for repetitive data analysis tasks, allowing for quick and informed decisions based on refined prompts and iterative improvements.

🚀 The Value of Perplexity Collections

Josh concludes by emphasizing the value of using Perplexity Collections. He reiterates the time-saving benefits of streamlining chatbot interactions and the refinement of prompts for superior results. Josh encourages viewers to save well-crafted prompts as collections to benefit from their efficiency repeatedly. He invites viewer feedback and encourages sharing the video, rounding off the presentation with a call to action for increased productivity.

Mindmap

Keywords

💡Perplexity

Perplexity in the context of the video refers to a measure of how well a language model predicts or understands a sample of text. It is a crucial concept when working with AI chatbots and language models, as it helps in refining and improving the prompts to get better responses. In the video, the speaker discusses using perplexity agents to enhance chatbot interactions and save time by perfecting prompts through repeated use and refinement.

💡Agents

Agents in this context are AI-driven tools or chatbots that are designed to perform specific tasks or answer queries based on pre-set prompts or collections. They are reusable and can be refined for better performance over time. The video emphasizes the utility of these agents in saving time and improving the quality of interactions by streamlining the process of prompting and receiving responses.

💡Collections

Collections refer to a set of saved prompts or agents in the AI system that can be reused and edited as needed. They serve as a repository for efficient and quick access to commonly used or refined prompts, allowing users to save time and effort in their interactions with the AI. The video highlights the importance of collections in organizing and personalizing the user's experience with AI chatbots.

💡Streamlined

Streamlined in this context means to make a process more efficient and smooth by removing unnecessary steps or complexities. The video emphasizes the value of streamlined chatbot interactions through the use of perplexity agents and collections, which allows users to achieve their goals more quickly and with less effort.

💡Refine

Refine indicates the process of improving or polishing a concept, method, or product by making adjustments based on feedback or experience. In the video, the speaker discusses the iterative process of refining AI prompts to achieve better results from the chatbot interactions. This involves testing, evaluating, and adjusting the prompts until they yield satisfactory outcomes.

💡Quick Access

Quick access refers to the ability to retrieve or use something with minimal delay or effort. In the context of the video, it highlights the convenience of having pre-saved agents and collections that can be instantly accessed and utilized during AI interactions, thereby saving time and enhancing productivity.

💡Efficiency

Efficiency is the ability to perform tasks with the least waste of time and resources. It is a central theme in the video, where the speaker advocates for the use of perplexity agents and collections to increase efficiency in AI interactions. By saving and refining prompts, users can achieve better results with less effort and time spent.

💡迭代 (Iteration)

迭代, or iteration in English, refers to the process of repeating a procedure with the aim of approaching a desired goal or result. In the context of the video, the speaker uses iteration to improve the effectiveness of their AI prompts. By going through multiple versions of a prompt, they can fine-tune it to get the most accurate and useful responses from the AI.

💡Feedback

Feedback in this context is the response or critique provided by the AI or another user, which can be used to make improvements or adjustments. The video emphasizes the value of feedback in the learning process, especially when interacting with AI chatbots to refine prompts and enhance the quality of future interactions.

💡Productivity

Productivity refers to the efficiency and effectiveness with which tasks are completed or goals are achieved. The video discusses how using perplexity agents and collections can boost productivity by saving time and ensuring that interactions with AI chatbots are more purposeful and result-oriented.

Highlights

Perplexity agents are reusable, refinable, quick access prompts saved as collections.

Agents can be thought of as pre-prompted chatbots, springloaded to respond to specific needs repeatedly.

Creating a collection involves giving it a meaningful title, relevant icon, and detailed description for future reference.

An example of creating a Spanish proficiency agent is demonstrated, showcasing the process of crafting a prompt and saving it as a collection.

The Spanish proficiency agent is designed to improve Spanish conversation skills through a structured back-and-forth in Spanish and English.

The importance of iteration in refining prompts is emphasized, as seen with the Spanish proficiency agent's successful fifth iteration.

Editing a collection is straightforward, allowing for continuous improvement of the agents.

An example of the 'Al Roker' agent is given, where typing 'high' prompts a weather forecast in a fun and whimsical manner.

The 'Video Brainstorming' agent is introduced, which generates video ideas based on a given topic and past instructions.

The agent's role is to produce an outline using a script formula, demonstrating the versatility of Perplexity collections in content creation.

The rewrite function is a Pro feature that allows users to get different answers from various chatbots, enhancing the output.

Perplexity collections can be used to streamline chatbot interactions, saving time and improving results through reuse and refinement.

The practical application of agents in data analysis is discussed, showing how they can quickly parse data sets in a consistent manner.

Agents can be a valuable tool for productivity experts, helping them efficiently create content and manage tasks.

The concept of building a collection once and reaping ongoing benefits is likened to building a bridge that serves indefinitely.

The video encourages viewers to try using Perplexity collections and to share their experiences and questions in the comments.

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