This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI.
Tool-use has been an important part of the development of large language models (LLMs) since the release of ChatGPT in 2022. Tools enable LLMs to interact with their environment and access information that goes beyond their internalized knowledge.
With AI agentic applications getting the spotlight in 2025, we’ve seen much impressive progress in both tooling, frameworks, and LLMs that can interact with their environment. Newer models are trained with native tool-use abilities. The release of Model Context Protocol (MCP) in late 2024 and other standards such as A2A and Claude Skills in 2025 made it easier to connect agents to tools and each other. And we’ve seen new specialized frameworks and models that can help enhance tool-use in AI applications.
Here is my brief take on the history of LLM tool-use, advances in 2025, and what to expect in the future.
The early innings of LLM tool-use
