When Do Tools Help LLM Agents, and When Do They Backfire?
When Do Tools Help LLM Agents, and When Do They Backfire? Recent papers on LLM agents are pushing back against a common assumption: adding tools and orchestration does not automatically make an agent better. "Are Tools All We Need? Unveiling the Tool-Use Tax" is a research paper that argues tool-augmented reasoning can fail to beat native chain-of-thought in some settings, especially when semantic distractors are present. "To Call or Not to Call" frames tool use as a decision problem: the key question is not just how to call a tool, but whether to call it at all. A separate position paper, "agentic AI orchestration should be Bayes-consistent," argues that the control layer of an agent system is where uncertainty-aware decision-making matters most. In a more applied setting, "SiriusHelper" describes an LLM agent-based operations assistant for big data platforms and highlights the practical difficulty of covering both general consultation and doma...