TL;DR: An open-source agent architecture uses file-based repositories to manage state and memory across multiple AI runtimes.
Summary: An Apache-2.0 licensed agent architecture has been introduced to resolve agent memory degradation and context loss. The framework structures agents as local file repositories (including AGENTS.md, agents/, and .agentlas) rather than raw prompts. This allows the same agent state and memory to run interchangeably on runtimes like Claude Code, Codex, and Gemini CLI.
Why it matters: This approach enables builders to create highly portable, runtime-agnostic agents with persistent and clean memory states. Developers should explore treating agent configurations as local directories to prevent vendor lock-in and handle multi-session context.
Source: r/artificial