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cs.AI2026

The Token Not Taken: Sampling, State, and the Stochasticity of AI Agents

Muhammad Zia Hydari, Raja Iqbal

Agentic AI systems can behave differently across runs: the same request may produce a different plan, a different tool call, a different code edit, or a different final answer. Suc…

cs.AI2026

Governing Technical Debt in Agentic AI Systems

Muhammad Zia Hydari, Raja Iqbal, Narayan Ramasubbu

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 fe…

cs.AI2026

Modeling Agentic Technical Debt and Stochastic Tax: A Standalone Framework for Measurement, Simulation, and Dashboarding

Muhammad Zia Hydari, Raja Iqbal, Narayan Ramasubbu

Agentic AI systems combine probabilistic reasoning with delegated action through tools, context, memory, orchestration, and external workflow integration. This note develops a form…

cs.AI2026

Redrawing the AI Map: A Theory of Accountability Boundaries in Agentic Ecosystems

Muhammad Zia Hydari, Farooq Muzaffar

Agentic AI orchestrators reduce the interface and assembly costs of composing information systems capabilities across organizational boundaries, seemingly accelerating modularizati…

cs.AI2026

Going Headless? On the Boundaries of Vertical AI Firms

Muhammad Zia Hydari, Farooq Muzaffar

Vertical AI firms in accounting, law, healthcare, procurement, and similar domains historically bundled workflow, domain logic, and accountability into a single application. Genera…