A Formal Hierarchical Architecture for Agentic Orchestration with Stack-Based Execution and Lazy Discovery
The rapid expansion of capabilities in Large Language Model (LLM) agents has exposed a critical architectural bottleneck: when agents are given access to a flat, monolithic registry of tools, the model must evaluate hundreds or thousands of options simultaneously. This leads to decision-space explosion, context window saturation, and degraded routing accuracy. To address these limitations, this paper presents a hierarchical, skill-based architecture for agentic orchestration. Capabilities are organized as a rooted tree where internal nodes make routing decisions and leaf nodes execute deterministic tasks. The runtime enforces a single-step execution loop governed by a Last-In-First-Out (L...
| Authors | Prashant Devadiga, Abhishek, Adithya Mishra et al. |
|---|---|
| Primary category | cs.AI |
| Published | 13 July 2026 |
| Last updated at source | 13 July 2026 |
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