Methods of Intelligent Automation of Software System Analysis Using AI Agents in the Development and Operation of Web Applications

AI agents built on large language models now take part in the analysis of software systems, yet evidence on their use across the life cycle of web applications remains scattered among benchmark reports and separate field studies. This article aims to systematize methods of agent-based analysis in the development and operation of web applications and to substantiate a model for assigning agent autonomy. The study combines a structured review of 25 sources published from 2020 to 2026, comparative analysis of benchmark results, content analysis of field studies, and a qualitative case study of two web products from the author's practice. The synthesis suggests that the strength of the verification oracle may be a more stable basis for assigning autonomy than benchmark capability scores; a direct comparative test of this hypothesis remains necessary. The article proposes an oracle-gated model with four layers, a matrix of four autonomy modes, and five monitoring indicators. The conclusions support staged adoption that begins with tasks backed by executable checks. The findings will interest web developers, game developers, engineering managers, and researchers in software engineering.