Proposed Task

I want to create a HTML app which contains 16x prompts to generate 16 some type of AI prompts (which vary depending on specific niches I enter). users can enter some text in a text field at the top, then 16 prompts will be displayed that can be copied to the clipboard

Suggested Plan - GPT4

OVERVIEW: To create an HTML app that allows users to input text and receive 16 varying AI-generated prompts in specific niches, we would need to design a user-friendly interface, set up a server to host the app, create a mechanism to generate diverse prompts, and implement a copying feature to the clipboard. The core functionality would use the GPT-4 model to generate text prompts that change depending on the user input, indicating specific niches, and an HTML interface would present these prompts with a copy-to-clipboard option. The backend would involve server management to host the HTML content, processing the prompts, and ensuring seamless user experience. TASKS: TASK1 > INTERFACE DESIGN: Use human assistance through the TEMPLATE CREATOR task (52) to design an HTML interface template. It should include a text input field, a button to trigger the prompt generation, and an area to display the 16 prompts with copy-to-clipboard functionality for each. TASK2 > SETUP WEB SERVER: Utilize FILE MANAGEMENT tasks such as Move (8), Save (9), and Access (10 & 11) files around the server to set up the server hosting of the HTML app interface. TASK3 > PROMPT GENERATION API: Harness the GPT-4 (1), possibly in conjunction with Prompt Generator (2), to create a backend process that takes a user's input, identifies the niche, and generates 16 diverse prompts related to this niche. TASK4 > IMPLEMENT COPY FUNCTIONALITY: Engage a human through MACRO MAKER (53) to create a JavaScript macro that enables the copy-to-clipboard functionality for the displayed prompts in the HTML app. TASK5 > TEST AND DEBUG: Use the WEB BROWSER task (4) to test the HTML app's interface and functionality in various browsers, ensuring compatibility and responsiveness. This may involve iterative testing with GPT-4 TURBO (4) to simulate user interactions. CONFIDENCE: 18/20 - The sequence of tasks appears to align well with the given objectives. Confidence is slightly reduced due to potential variability in design preferences and unforeseen technical issues. HUMAN REQUESTS: - I would request the TEMPLATE CREATOR's assistance to design the HTML interface. - I would need the MACRO MAKER's capabilities to create the JavaScript needed for copy-to-clipboard functionality. - Additionally, a final review by a human to assess usability and user experience of the app would be beneficial.

Suggested Plan - Claude3

OVERVIEW: To create an HTML app that generates 16 AI prompts based on user-entered text and specific niches, we can leverage a combination of GPT-4, web development, and user interface design. The app will consist of a simple text input field at the top where users can enter their desired text. Upon submission, the app will generate 16 prompts tailored to the entered text and pre-defined niches. These prompts will be displayed in a user-friendly manner, allowing users to easily copy them to the clipboard for further use. TASKS: 1. GPT4 > Prompt generator: Use GPT-4 and the prompt generator to create a set of guidelines for generating the 16 AI prompts based on user input and specific niches. 2. GPT4: Develop the HTML, CSS, and JavaScript code for the app's structure, styling, and functionality. 3. Save content to server: Save the generated HTML, CSS, and JavaScript files to the server. 4. GPT4: Create a server-side script (e.g., Python or Node.js) to handle the user input, generate the prompts using the guidelines from step 1, and return the results to the app. 5. Save content to server: Save the server-side script to the server. 6. Concantena text/html files: Combine the HTML, CSS, and JavaScript files into a single HTML file. 7. EMAIL HUMAN: Request a human to review the app, test its functionality, and provide feedback for improvements. 8. GPT4: Incorporate the human feedback and make necessary adjustments to the app's code and functionality. 9. Save content to server: Save the updated files to the server. 10. Build landing page: Create a simple landing page to host the app and provide instructions for users. CONFIDENCE: 18/20. The available tasks cover the essential aspects of creating the HTML app, from generating the prompts to developing the user interface and server-side functionality. The human review step ensures the app's quality and usability. HUMAN REQUESTS: 1. Provide a list of specific niches for which the app should generate prompts. 2. Clarify any additional features or customization options desired for the app. 3. Specify the desired hosting platform or server environment for the app. With the given tasks and the requested human input, the HTML app for generating 16 AI prompts based on user input and specific niches can be successfully developed and deployed.

Skills Assessment - GPT4

1. LOOK FOR OUTPUTS/INPUTS THAT DON'T LINK UP Upon reviewing the sequential chain of skills: - TASK1 reports the creation of an HTML interface template including necessary fields and functionality. The input seems to be the directive to create the template, but the output must be the actual HTML/CSS/JavaScript code which would be created and passed on to the next skill. This task's output needs to be specified as such code. - TASK2 calls for setting up a webserver using file management tasks. The output of TASK1, which should be the code for the HTML app, can be the input here. However, additional configuration details like server specifications or hosting environment details should be explicitly mentioned as required inputs for the setup. - TASK3 involves using GPT-4 for prompt generation. The clear input for this task would be the user text input specifying a niche. It is important that the mechanism used to identify the niche is described—whether it is a simple keyword matching or more complex natural language understanding. Outputs would be the 16 prompts generated. - TASK4 is about implementing copy-to-clipboard functionality. This task could be more detailed; it needs specifications on how it will receive the prompts (presumably from TASK3) and the events that would trigger the copy functionality. - TASK5 proposes testing the app interface and functionality. This task seems appropriate, but it could be more explicit about what will be tested (outputs from all previous tasks are presumed inputs here) and what defines a successful test. 2. LOOK FOR SKILLS THAT NEED TO BE BROKEN INTO MORE PIECES - TASK3's use of GPT-4 to generate prompts could potentially need breaking down, depending on what is required to identify the niche accurately from user input. If this process is simply about generating prompts from keywords, it might be fine as-is, but if a more nuanced understanding of the user input is required, this may need to be another separate subtask. 3. LOOK FOR SKILLS INVOLVING HUMANS, BRAINSTORM AUTOMATED ALTERNATIVES - TASK1 involves human assistance for designing the HTML interface. As an alternative, one could use automated design tools or frameworks (like Bootstrap for easy UI components or Tailwind CSS for utility-first design) to create a standardized interface without human intervention. - TASK4 also enlists a human to create JavaScript for the copy-to-clipboard feature. An alternative could be to use an existing JavaScript library or framework that includes this functionality, thus removing the need for custom coding by a human. 4. FIND FLAWS OR LOOK FOR HOW A TASK COULD BE IMPROVED The overall task might benefit from a few overall improvements: - Consider employing a framework or library like React or Angular for the frontend which could standardize prompt display and make copy-to-clipboard functionality simpler to implement. - For TASK3, instead of using a large and potentially costly model like GPT-4 for generating prompts, one could look at keyword-based prompt generation methodologies that could be less resource-intensive and faster to implement. - For TASK2, automated deployment tools like Docker for containerization and Kubernetes for orchestration can facilitate app deployment without much human intervention. - For TASK5, automated testing suites such as Selenium or Cypress for end-to-end testing could streamline the testing process and ensure better coverage and consistency. Taking a first principles approach: - Consider whether the app needs to be hosted on a webserver. Could it be a static site, hosted on platforms like GitHub Pages or Netlify that facilitate CI/CD pipelines for easy deployment? - Examine whether the prompts really need to be AI-generated. Could they be templated and then tweaked according to the niche entered by the user? - Evaluate security concerns, like ensuring that the app sanitizes user input to avoid potential injection attacks or similar security issues. Each of these improvements would refine the AI agent's task plan to ensure efficiency and practicality, limit the reliance on human intervention, and optimize the performance and security of the end-product.

Skills Assessment - Claude

1. LOOK FOR OUTPUTS/INPUTS THAT DON'T LINK UP - The output of step 1 (guidelines for generating prompts) is not explicitly used as input in any of the subsequent steps. - The output of step 4 (server-side script) is not explicitly used as input in any of the subsequent steps. - The output of step 8 (incorporating human feedback) is not explicitly used as input in any of the subsequent steps. 2. LOOK FOR SKILLS THAT NEED TO BE BROKEN INTO MORE PIECES - Step 2 (develop HTML, CSS, and JavaScript code) could be broken down into separate tasks for each component (HTML structure, CSS styling, and JavaScript functionality). - Step 4 (create a server-side script) could be broken down into smaller tasks, such as setting up the server environment, handling user input, generating prompts, and returning results. - Step 8 (incorporate human feedback) could be broken down into reviewing feedback, identifying areas for improvement, and implementing changes in the code. 3. LOOK FOR SKILLS INVOLVING HUMANS, BRAINSTORM AUTOMATED ALTERNATIVES - Step 7 (request a human to review the app) could be partially automated by: - Implementing automated testing scripts to check the app's functionality and performance. - Using a tool like Google Lighthouse to audit the app's accessibility, SEO, and best practices. - Leveraging user analytics and feedback tools to gather data on user behavior and preferences. 4. FIND FLAWS OR LOOK FOR HOW A TASK COULD BE IMPROVED - The plan lacks a clear definition of the specific niches for which the app should generate prompts. This information is crucial for developing targeted and relevant prompts. - The plan does not include a step for optimizing the app's performance and loading speed, which is important for user experience. - The plan could benefit from a step dedicated to designing an intuitive and visually appealing user interface. - The plan should include a step for setting up analytics to track user engagement and identify areas for improvement. - The plan could incorporate a feature for users to save and manage their generated prompts for future reference. - The plan should consider implementing a mechanism for handling user errors and providing informative feedback. - The plan could explore integrating with external APIs or services to enhance the app's functionality or provide additional features. Overall, the plan provides a solid foundation for creating the HTML app, but it could be improved by clearly defining the links between outputs and inputs, breaking down complex tasks into smaller steps, automating parts of the human review process, and considering additional features and optimizations to enhance the app's functionality and user experience.

Critical Thinking - GPT4

Approaching the agent's plan from a first principles perspective involves stripping down the given solution to its fundamental components and reasoning up from there. It's about questioning the assumptions and necessitates reformulating the problem in a way that might reveal more effective or efficient solutions. First, let's restate the fundamental goals: 1. Allow user input of text to specify niche. 2. Generate 16 AI-driven, niche-specific prompts. 3. Display prompts to the user in a web interface. 4. Offer a mechanism to copy prompts to the clipboard. 5. Ensure the solution is hosted where users can access it. Now, we'll critique and review each task using first principles thinking: TASK1 > INTERFACE DESIGN: - Is HTML the most efficient way to create the interface? HTML is standard, but is there a need for pre-built templates or frameworks (like Bootstrap or React) for this design? Could this speed up the design process and ensure responsiveness across different devices? - You might ask whether a completely custom design is necessary, or if an existing solution could be modified to meet the requirement more efficiently. TASK2 > SETUP WEB SERVER: - As for setting up a server, is traditional web hosting the best option, or could a serverless architecture, like AWS Lambda combined with API Gateway, be more maintainable and scalable, potentially reducing cost and overhead? TASK3 > PROMPT GENERATION API: - The use of GPT-4 as a backend service is assumed. Could there be a more lightweight or specific model tailored to the task that would be more efficient or cost-effective? - Is Prompt Generator (2) adding complexity or overhead without sufficient benefit? It’s important to evaluate if this additional layer optimizes or complicates the process. TASK4 > IMPLEMENT COPY FUNCTIONALITY: - Is employing human assistance with a MACRO MAKER the most effective method, or could this functionality be quickly implemented with a library or existing code snippet (e.g., Clipboard.js)? - Consider whether the JavaScript could be simplified or made more robust against different browsers and platforms. TASK5 > TEST AND DEBUG: - Testing across various browsers is necessary, but could automated testing tools or services streamline this process? - The approach for testing should prioritize high-impact bugs and ensure the application gracefully handles edge cases, such as exceedingly large input or unexpected user behavior. Now, let's also consider some broader challenges and questions: - How will the app scale if it becomes popular? Does the architecture support rapid scaling, or will it crumple under high traffic? - Are there any privacy or data handling concerns that users might have when inputting their niche text, and if so, how are these being addressed? - Could the prompt-generation process benefit from cached results for common niches to improve performance and reduce API calls? - Is an HTML app the right choice? Might a progressive web app (PWA) or even a mobile app provide a better user experience? - How will updates and maintenance of the app be handled in the future? Is there a plan in place for the application's lifecycle management? By critically analyzing the agent's approach using a first principles methodology, you can identify assumptions, explore alternatives, and strive to construct a more efficient and robust plan to realize your HTML app for generating niche-specific AI prompts.

Critical Thinking - Claude

Certainly! Let's take a critical look at the suggested plan using first principles and see if there are any areas for improvement or optimization. OVERVIEW: The overall approach of using GPT-4, web development, and user interface design to create an HTML app that generates 16 AI prompts based on user input and specific niches is a solid foundation. However, we should consider if there are more efficient or effective ways to achieve the desired outcome. TASKS: 1. GPT4 > Prompt generator: Using GPT-4 to create guidelines for generating the prompts is a good starting point. However, we should consider if there are other AI models or techniques that could be more suitable for this specific task. Additionally, we should ask if the guidelines need to be generated dynamically for each user input or if a pre-defined set of guidelines could suffice. 2. GPT4: Developing the HTML, CSS, and JavaScript code using GPT-4 is an interesting approach, but it may not be the most efficient or reliable method. We should consider if using a human developer or leveraging existing web development frameworks and libraries would be more appropriate for ensuring code quality, maintainability, and performance. 3. Save content to server: Saving the generated files to the server is necessary, but we should consider if there are more optimal ways to store and manage the files, such as using a content management system (CMS) or a database. 4. GPT4: Creating a server-side script to handle user input and generate prompts is a good approach. However, we should consider if GPT-4 is the best choice for this task or if other AI models or techniques could be more efficient or accurate. Additionally, we should ask if the server-side script needs to be written from scratch or if existing libraries or frameworks could be utilized to simplify the process. 5. Save content to server: Similar to step 3, we should consider if there are more optimal ways to store and manage the server-side script. 6. Concantena text/html files: Combining the HTML, CSS, and JavaScript files into a single HTML file may not be the best approach. Modern web development practices often involve keeping these files separate for better organization, maintainability, and performance. We should consider if using a build tool or bundler would be more appropriate. 7. EMAIL HUMAN: Requesting human review and feedback is crucial for ensuring the app's quality and usability. However, we should consider if there are more efficient ways to collaborate and gather feedback, such as using project management tools or user testing platforms. 8. GPT4: Incorporating human feedback and making adjustments to the app's code and functionality using GPT-4 may not be the most reliable approach. We should consider if a human developer would be better suited for this task to ensure the changes are implemented correctly and efficiently. 9. Save content to server: Similar to steps 3 and 5, we should consider if there are more optimal ways to store and manage the updated files. 10. Build landing page: Creating a simple landing page to host the app and provide instructions for users is a good idea. However, we should consider if there are more engaging or interactive ways to present the app and its features to potential users. CONFIDENCE: The confidence level of 18/20 seems reasonable, but it could be improved by addressing the questions and considerations raised above. By optimizing the tasks and leveraging the most appropriate tools and techniques, the confidence in the plan's success could be increased. HUMAN REQUESTS: The human requests for specific niches, additional features or customization options, and hosting platform or server environment are important for tailoring the app to the desired use case. However, we should also consider asking for: 1. Examples of the types of prompts the user expects the app to generate. 2. Information about the target audience and their technical proficiency. 3. Any specific performance, security, or scalability requirements for the app. By addressing these questions and considerations, the plan for developing the HTML app for generating 16 AI prompts based on user input and specific niches can be further refined and optimized for success.