VibeGen: Autonomous Multi-Agent Swarm Orchestration and Deterministic Self-Healing Verification Gates for End-to-End Web Application Synthesis

Generative Large Language Models (LLMs) have demonstrated exceptional capabilities in producing isolated software routines; however, end-to-end synthesis of multi-component, production-grade web applications remains severely bottlenecked by code truncation, cascading syntactic errors in Abstract Syntax Trees (ASTs), runtime dependency mismatches, and hallucinatory verification. In this paper, we present VibeGen, an autonomous, multi-agent AI web application development and verification platform engineered to synthesize complete, zero-defect React/TypeScript software systems from natural language specifications. VibeGen introduces three core architectural innovations: (1) a 5-layer asynchronous swarm orchestration engine leveraging heterogeneous, hot-swappable foundation models via a unified high-throughput Model Gateway; (2) a deterministic AST and zero-touch self-healing pipeline that intercepts and repairs compiler-level faults; and (3) a zero-hallucination sandbox verification gate coupling headless DOM testing, toolchain validation, design heuristic audits, and live iframe isolation. Empirical evaluations across 152 automated unit test suites demonstrate a 100% compilation pass rate, 0% code truncation, and a 78.4% reduction in end-to-end synthesis latency compared to sequential monolithic prompting baselines.