Governing Technical Debt in Agentic AI Systems 文章

ArXiv CS.AI2026-05-29NEWSen作者: Muhammad Zia Hydari, Raja Iqbal, Narayan Ramasubbu

详细信息

来源站点
ArXiv CS.AI
作者
Muhammad Zia Hydari, Raja Iqbal, Narayan Ramasubbu
文章类型
NEWS
语言
en
发布日期
2026-05-29

摘要

arXiv:2605.29129v1 Announce Type: new Abstract: Agentic AI systems are increasingly being explored as production infrastructure: they reason over multiple steps, call tools, act through workflows, and adapt through memory and feedback. These systems create governance challenges that are not fully captured by traditional software or predictive ML technical debt. We define Agentic Technical Debt as the accumulated liability created when prompts, memory, tool schemas, orchestration graphs, control policies, and observability routines are patched together faster than they can be validated, standardized, and governed. We define Stochastic Tax as the recurring operating burden of keeping probabilistic agent behavior within acceptable bounds. The distinction matters: debt is a stock of design and governance liability, while the tax is a flow of operating cost that arises because stochastic agents act through tools and workflows.

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