Self-Improvements in Modern Agentic Systems: A Survey
This survey reviews self-improving autonomous agents transitioning from prototypes to deployed systems. It introduces a system-level framework modeling an agent as a foundation model coupled with an operational scaffold (prompts, memory, tools, control logic). Self-improvement is formalized as a self-induced update operator that updates model parameters or scaffold components. The paper categorizes prior work by update target and driving signals, and discusses applications, evaluation, and open challenges.
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[Submitted on 14 Jul 2026]
Title:Self-Improvements in Modern Agentic Systems: A Survey
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Abstract:Self-improving autonomous agents are moving from research prototypes to deployed systems. The primary goal is controllable evolution, or adaptation, from experience with minimal or even no human input. This survey frames modern self-improving agents as adaptive systems that convert experience into accumulated capability gains. We offer a system-level framework that represents a modern agent as a configuration coupling a foundation model with an operational scaffold of prompts, memory, tools, and control logic. Within this framework, self-improvement is formalized as a self-induced update operator that obtains and commits updates to model parameters or scaffold components. We organize prior work by update target and by the signals that drive change, then review applications and discuss evaluation, before closing with open problems and future directions. For convenience, we track technical updates on this https URL.
Comments: 97 pages, 12 figures. Project page: this https URL Repository: this https URL
Subjects:
Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG)
Cite as: arXiv:2607.13104 [cs.AI]
(or arXiv:2607.13104v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2607.13104
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Zhe Ren [view email] [v1] Tue, 14 Jul 2026 09:12:57 UTC (4,958 KB)
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