Ahmad Awais

This talk introduces Command Code, a coding agent designed to learn and adapt to an individual developer's unique coding style and preferences, referred to as "taste." Unlike standard AI coding assistants that provide generic code, Command Code aims to internalize a developer's decision-making process, preferences for tools, and architectural choices. This is achieved through a meta-neuro-symbolic reinforcement learning approach, creating a more personalized and efficient coding experience.

This talk argues that building AI agents on primitives rather than frameworks leads to more production-ready and scalable solutions. Frameworks are often bloated, slow, and introduce unnecessary abstractions. Instead, developers should leverage composable, low-level primitives, similar to how cloud services like Amazon S3 function, to create flexible and efficient AI agents.