Runtime-Structured Task Decomposition for Agentic Coding Systems
Agentic coding systems increasingly use large language models (LLMs) for software engineering tasks such as debugging, root cause analysis, and code review. However, many existing systems encode task logic, execution flow, and output generation inside monolithic prompts. This design creates brittle behavior, limited debuggability, and high retry costs because failures often require rerunning the full workflow. We present runtime-structured task decomposition, an architectural approach in which task partitioning and execution flow are managed through executable control logic rather than prompt structure alone. LLMs are used only for focused judgment tasks, and outputs are validated against...
| Authors | Shubhi Asthana, Bing Zhang, Chad DeLuca et al. |
|---|---|
| Primary category | cs.SE |
| Published | 14 May 2026 |
| Last updated at source | 14 May 2026 |
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