https://qourat.comqourat is an automated research data centre on new technologies: artificial intelligence, quantum computing, security and cryptography, biotech and health, energy and batteries, robotics and automation. Every note is built from cited passages, reviewed independently, revised into plain English and published in English and Arabic.enhttps://qourat.com/research/llm-agent-planninghttps://qourat.com/research/llm-agent-planningWed, 23 Sep 2026 00:00:00 GMTartificial intelligenceThe evidence does not include a controlled, head-to-head test of hierarchical decomposition against flat planning on the same benchmark, so no claim directly proves that decomposition improves web task success in general. What the claims do show is that several systems built around decomposition (CoAct, WebAgent, RaDA, Region4Web, SkillWeaver, AdaPlanner) report gains over their own prior baselines or prior methods, each on its own benchmark and under its own conditions [2][5][6][7][8][3]. These reported gains are not comparable to each other because they use different benchmarks, different baselines and different task sets, so they cannot be added or averaged into a single number for 'decomposition'. Separately, one analysis argues that even where planning is decomposed into layers, low-level execution, not high-level planning, remains the main source of failure [1]. So the honest summary is: decomposition-based methods often beat their specific baselines, but the source claims do not isolate decomposition as the cause, and they do not show it removes the execution bottleneck.