Systems | Development | Analytics | API | Testing

From Endpoints to Intent: Rethinking Agent API Workflows with Arazzo

Once, the rallying cry of the mobile revolution was ‘There’s an app for that.’ Today, the new reality is that AI-powered agents are substantially changing how we interact with software, coining a new catchphrase: ‘There’s an agent for that!’ From automating tasks to executing complex workflows and acting autonomously on our behalf, AI agents are becoming critical intermediaries in digital interactions.

If an AI Agent Can't Find You, You Don't Exist

In 2025, the most important customer for your API isn’t a developer scrolling through documentation at 2 AM. It’s an AI agent making split-second decisions about which services to integrate, recommend, or build upon. And here’s the uncomfortable truth: if an AI agent can’t find you, you don’t exist. This isn’t hyperbole. It’s the new reality of how software will get built, integrated, and scaled in an AI-first world.

Accelerating Model Context Protocol (MCP) Journey with SmartBear API Hub

In the evolving landscape of AI applications, the Model Context Protocol (MCP) emerges as a pivotal standard, facilitating seamless integration between large language models (LLMs) and external tools, data sources, and services. By standardizing these interactions, MCP enables AI systems to perform complex tasks with enhanced context and precision. To harness the full potential of MCP, developers require robust tools that ensure reliability, scalability, and efficiency.

Delivering scalable, serverless APIs with SmartBear and AWS

Amazon API Gateway and AWS Lambda are widely used for deploying and running scalable APIs or applications in the cloud. While they offer powerful capabilities for deploying and scaling APIs, designing the API or maintaining visibility into performance and reliability can be challenging without the right tools in place.

Amplify and Automate Your API Testing with ReadyAPI and TestEngine

In today’s fast-paced world of software development, the pressure to deliver high-quality releases quickly is stronger than ever. Teams are pushing code changes to production multiple times a day, and expectations around stability, security, and performance haven’t gone down—in fact, they’ve gone up. Manual testing simply can’t keep up with the speed and complexity of modern deployment cycles.