From AI Technical Debt to Agentic Technical Debt: A Systematic Mapping of Root Causes and Manifestations in Agentic AI Systems
Muhammad Tukur, Hayatullahi B. Adeyemo, Tao Chen, Nour Ali, Anis Zarrad, Marco Agus, Rick Kazman, Rami Bahsoon
cs.AI, cs.CR, cs.SE
Submitted: 2026-08-02
Comments: 32 pages, 7 figures, 7 tables, submitted to IEEE Transactions on Software Engineering
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Foundations for Investigations of Agentic AI Systems from the Forensic Analysis of OpenClaw
- TRiSM for Agentic AI: A Review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems
- Looking Forward: Challenges and Opportunities in Agentic AI Reliability
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems