Research → Projects → YR-002
YR-002 Active P02 · Agentic & Agentless

Lightweight AI Runtime

Researching Modular Execution Architectures for Intelligent Systems

Investigating the architecture and engineering principles behind lightweight, modular intelligent runtimes. Can we develop a modular AI runtime that provides essential orchestration without depending on heavyweight agent frameworks?

Problem Statement

Existing AI agent frameworks carry significant runtime complexity, hidden dependencies and unpredictable execution behaviour. This research investigates minimal, modular runtime alternatives.

Research Questions

  1. 01 Can we develop a modular AI runtime with essential orchestration capabilities?
  2. 02 What are the core primitives required for a lightweight agent runtime?
  3. 03 How should execution state, tool invocation and context management be architected?
  4. 04 What observability and failure recovery mechanisms are needed?

Results & Findings

This project is currently in active research. Experimental findings will be published here as the research progresses through the YARA review lifecycle.

Publications

No publications available yet. Papers and technical reports will appear here when research is completed and passes independent review.