Solver uses a Transformer-based task understanding engine whose output quality is positively correlated with the information density of the input description. Engineering practice has shown that optimal results are obtained with instructions that include the following elements:
- Specific technology stack statements (e.g., "Implemented in Python 3.10")
- Explicit contextual constraints (e.g., "need to be compatible with older APIs")
- Detailed exceptions (e.g., "competing conditions occur on concurrent requests")
Comparative case shows:
The fuzzy command "Add Login Function" may generate a basic authentication process;
A precise description of "implement JWT authentication and require support for refresh token rotation" would result in a specialized implementation that conforms to the OAuth 2.0 standard.
This feature allows Solver to meet the simple needs of non-technical users as well as handle the complex scenarios of professional developers.
This answer comes from the articleSolver: the smart tool for autonomously completing programming tasksThe
