Systems | Development | Analytics | API | Testing

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.

From Flaky to Reliable: How QMetry Keeps Your Pipeline Clean

Not every failure is a bug and not every bug is what it seems. Sometimes, a test fails without warning. No code changes, no environment issues, just a red mark where there should be green. You rerun it, and it passes. These are flaky tests. And they do more than create noise. They drain team time, stall releases, and make it harder to trust automation at all. Left unchecked, they quietly become one of the most expensive problems in testing.

What is an API first approach?

APIs already account for 71% of all internet traffic, but here's what most companies are missing: AI is about to become the biggest API consumer ever. As generative AI transforms how we interact with software, agentic workflows will perform automated, API-heavy interactions on our behalf. Companies that embrace an API-first approach now will dominate tomorrow's AI economy. In this video Frank Kilcommins, Principal API Technical Evangelist at SmartBear, explains what it means for a software development organization to be API-first.