We always thought the APIs (Application Programmable Interface) are a permanent feature of the digital world and the only way to use them was the manner in which we have been doing it. What is it exactly? It is a set of protocols that allows different software applications to talk to each other and exchange data or functionality. A clean endpoint, a crisp schema, and the world’s software snapped like a Lego. In early 2000s APIs went public; the web API boom began when companies like Salesforce (2000) eBay (2000) and Amazon (2002) released public APIs. The hold of APIs on the digital ecosystem continues to this day.
Now the simple request response universe is being rattled by autonomous AI agents. What will these do? They would just not answer a call but decide, reason and negotiate on our behalf. APIs thus are evolving for the AI Age; from being developer-facing utilities into backend tools orchestrated by AI agents. This represents a major leap in how digital work gets done. The transition is from APIs as building blocks to APIs as autonomous tools. APIs in the conventional mode called by developers or applications in predefined ways. Now the AI Agents call APIs dynamically, are able to select the right one and decide when and how to use it.
Context aware API usage in the future. AI agents use real-time context. Agent’s long-term memory, and reasoning helps it to decide which API to call. It does not end here. It decides on what parameters to pass, and how to handle errors or incomplete data. What is fascinating is that APIs are becoming actionable skills for agents. APIs are registered in API frameworks; LangChain, AutoGen, OpenAI Functions, as callable “tools” or “skills.” AI agents chain multiple APIs together, reason over responses and decide next actions. We can call it a Digital Operations Team.
The future of engineering is changing accordingly, from designing APIs to orchestrating intelligent agents. This is becoming amply clear just by following the emerging standards such as Model Context Protocol (MCP) and Agent-to-Agent communication. It is redefining how systems communicate, collaborate and scale. MCP provides a standardised way for AI models to interact with external tools. A2A enables structured collaboration between agents across platforms. Essentially then, A2A allows agents to talk to each other while MCP allows agents to talk to other software.
INTELLIGENT, SEAMLESS AND CONNECTED IS THE FUTURE OF APIs, COURTESY AI AGENTS.
Sanjay Sahay
Have a nice evening.