This series starter explores building AI agents from the ground up, eschewing popular frameworks for a more hands-on approach. The first part focuses on getting a basic agent running, covering the core loop of perception, reasoning, and action. This approach is gaining traction among developers who want deeper understanding and avoid dependency on specific frameworks. By building from scratch, developers can tailor agents to specific use cases, optimize performance, and maintain full control over the system. The series promises to cover advanced topics like memory, tool use, and multi-agent coordination. For indie hackers and AI engineers, this is a valuable resource for creating custom AI solutions.
Learn how to build AI agents without frameworks, focusing on core architecture and decision-making loops for full control and understanding.