Governing Technical Debt in Agentic AI Systems
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
Record details
Published: 27 May 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy
Retrieved: 14 July 2026
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ethics.ai (27 May 2026), “Governing Technical Debt in Agentic AI Systems,” evidence record 3555, https://ethics.ai/record/3555 (originally published by arXiv).
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