PH Deck

Users managing LLM conversations face difficulties with parallel prompts, maintaining branches in conversations, and collaborating via shared canvases for teams, leading to disorganized workflows and inefficient context management.

Website owners currently lack control over how AI crawlers access their site content, leading to unregulated scraping or improper use of data. Existing methods (like robots.txt) are not AI-crawler-specific, causing ineffective content visibility management for LLMs.

Users struggle to keep track of their GitHub activities and progress over time, leading to potential overlooking of important contributions or updates. Keeping track of GitHub activities and ensuring they are utilizing GitHub insights effectively are the main issues.

Users struggle with fragmented code management and collaboration tools, leading to inefficiency in team coordination and project tracking.

Users struggle with inefficient collaboration and code management without integrated version control and project tracking tools, leading to fragmented workflows and slower development cycles.

Users face inefficient code collaboration and version control with manual sharing methods like email or FTP, leading to disorganized workflows and difficulty tracking changes.

Users rely on cracked versions of software like Freemake Video Converter, exposing them to legal risks, malware, and lack of updates.

Users need to manually create and manage llms.txt files for AI models, leading to time-consuming processes, inconsistent formatting, and reduced AI discoverability.

Developers and users often find it challenging to manage and navigate through their numerous GitHub repositories, leading to inefficiency and frustration.

Developers manually search through GitHub repositories, documentation, and wikis to understand codebases or find specific information. Time-consuming navigation, difficulty locating precise details, and lack of instant answers for complex projects.