"At the center of this transition was the rise of AI agents - AI systems that can use other software tools and act on their own. While researchers have studied AI for more than 60 years, and the term "agent" has long been part of the field's vocabulary, 2025 was the year the concept became concrete for developers and consumers alike. AI agents moved from theory to infrastructure, reshaping how people interact with large language models, the systems that power chatbots like ChatGPT."
"In 2025, the definition of AI agent shifted from the academic framing of systems that perceive, reason, and act to AI company Anthropic's description of large language models that are capable of using software tools and taking autonomous action. While large language models have long excelled at text-based responses, the recent change is their expanding capacity to act, using tools, calling APIs, coordinating with other systems, and completing tasks independently."
2025 marked a decisive shift as AI agents moved from research concepts to everyday infrastructure. Large language models gained the ability to use external software, call APIs, coordinate with other systems, and take autonomous actions. Anthropic reframed agents as models with tool-use and autonomous capability, and the Model Context Protocol released in late 2024 standardized connections between models and external tools. The momentum accelerated with releases such as the open-weight DeepSeek-R1, which disrupted assumptions about who could produce high-performing models and intensified global competition, driving rapid adoption and integration of agent-capable systems.
Read at Fast Company
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