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 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....
| Authors | Muhammad Zia Hydari, Raja Iqbal, Narayan Ramasubbu |
|---|---|
| Primary category | cs.AI |
| Published | 27 May 2026 |
| Last updated at source | 24 June 2026 |
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