Modeling Agentic Technical Debt and Stochastic Tax: A Standalone Framework for Measurement, Simulation, and Dashboarding
On the map: LLM agents and tool use → Financial trading and forecasting agents
Abstract (arXiv)
Agentic AI systems combine probabilistic reasoning with delegated action through tools, context, memory, orchestration, and external workflow integration. This note develops a formal and managerially usable model that distinguishes Agentic Technical Debt from Stochastic Tax. Agentic Technical Debt is a stock of accumulated design and governance liability. Stochastic Tax is a recurring flow of operating burden that arises when stochastic agents are used in business workflows. The two constructs are related, but they are not the same: debt can amplify the tax, while the tax can remain positive even when debt is minimized. The note starts from a compact dashboard expression, expands it into a fuller structural model, defines all variables and parameters, shows how each cost category can be estimated from operational data, and illustrates the framework with an accounts-payable simulation and companion spreadsheet.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 1 of its 13 references that are in the map. First posted on arXiv 26 May 2026.
Builds on
1 of 13 references.
References · 1
- 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
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Citing papers per year: 2026: 1.
1 paper.
- 2026Governing Technical Debt in Agentic AI Systemscited by 1
- 2026Governing Technical Debt in Agentic AI Systems27 May 2026
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