

Poolside
Overview :
Poolside is an advanced foundational AI model built for software engineering challenges. It fine-tunes on user code to learn the unique aspects of projects, allowing it to understand complexities that general models cannot. Built on the foundations of Poolside, it continually improves every day. In addition to its advanced coding model, Poolside also features an intuitive editor assistant and provides an API for developers to build upon. Founded by Jason Warner and Eiso Kant in April 2023, they have extensive experience in AI and software engineering.
Target Users :
Targeted at software developers and teams, particularly professionals looking to enhance their coding efficiency and quality through AI technology. Poolside offers customized AI models and tools to help users better understand and optimize their code, thereby increasing productivity and project success rates.
Use Cases
Developers used Poolside's AI model to optimize the project's code structure, improving readability and maintainability.
A software development team accelerated the iteration speed of new features with the Poolside editor assistant.
A company integrated a custom code analysis tool through Poolside's API, enhancing code quality.
Features
Fine-tuned learning: Fine-tunes on user code to learn the unique aspects of projects.
Complexity understanding: Capable of grasping complexities beyond the understanding of general models.
Continuous improvement: Built on Poolside's foundations, the model can self-improve daily.
Editor assistant: Developed an intuitive editor assistant to enhance development efficiency.
API support: Provides an API for developers to build and expand features.
Team collaboration: Supports team collaboration to build better software projects together.
Specific optimization: Optimizes for specific user needs, offering customized AI support.
How to Use
Visit the official Poolside website and register an account.
Upload your codebase for Poolside to learn from.
Select the appropriate editor assistant features based on project needs.
Optionally expand Poolside's features through the API.
Regularly check the model's learning and optimization progress to ensure it meets your project requirements.
Share the Poolside model with team members for collaborative use and optimization.
Adjust model parameters based on feedback to achieve better performance.
Utilize the resources and documentation provided by Poolside to deepen your understanding of maximizing its functionality.
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