Systems | Development | Analytics | API | Testing

The SmartBear community is made up of curious, collaborative builders. They’re developers, testers, creators, and innovators who every day are experimenting with new technologies, customizing workflows, and solving complex problems.

SmartBear participated in and won first prize at the ALMathon, the annual hackathon for SAP Partners. The challenge: Create innovative use cases to extend SAP Cloud ALM. So, we integrated Reflect, our AI-powered test automation product, into SAP Cloud ALM to enable users to automate their manual testing process.

For years, APIs have been designed with one primary audience in mind: developers. The focus has been on making APIs discoverable, consistent, and easy for humans to consume. But in the AI era, a new audience has arrived: AI agents. As detailed in SmartBear’s newly published AI-Enabled API Lifecycle Report, this shift demands that organizations rethink how APIs are designed, tested, and managed to serve both human developers and intelligent systems effectively.

As coding has become more autonomous, so has code-based testing. AI agents can now write functions, generate code-based tests, and validate logic in the same workflow. But the other half of the testing equation, the system-level validation of non-code-based testing, hasn’t kept up. That disconnect is becoming one of the most critical constraints in modern software delivery.

‘API governance’ can sound like an intimidating concept. When I started as a solutions engineer at SmartBear in 2018, it took me a while to wrap my head around what exactly API governance entails and even longer to be able to explain it clearly and simply to our customers.

The financial services industry is experiencing a fundamental transformation. API-led banking is taking a more definite shape with more than 50% banks actively deploying APIs to support open banking frameworks and fintech collaboration. From centuries-old institutions to cutting-edge fintech challengers, financial organizations are embracing API-first architectures to deliver scalable, secure, and customer-centric experiences.

When the automotive industry introduced the concept of Levels of Autonomy, it gave us a shared language for something profound. It wasn’t just about self-driving cars, it was about how humans and intelligent systems work together as execution gradually shifts from one participant to the other. Level 0 is full human control. Level 5 means the car can handle any situation on its own. And between those two extremes are a series of stages that capture both technological progress and human adaptation.

We’re proud to share that Gartner has recognized SmartBear as a Visionary in the 2025 Gartner Magic Quadrant for API Management. We believe this recognition reflects our dedication to API development teams and to delivering practical solutions that drive excellence. APIs are essential, allowing businesses to move faster, integrate easily, and deliver the best experiences for their customers.

APIs and AI are on a collision course. For decades, APIs have been the foundation of digital reliability: deterministic systems where you send a request, get a predictable response, and trust that what’s defined is what will happen. AI doesn’t play by those rules. Large language models and AI agents operate in probabilities. They don’t just follow contracts; they interpret them. They learn, infer, and sometimes hallucinate.

The term “Behavior Driven Development”, or BDD, is an umbrella term for a wide variety of techniques. The general principles of BDD include reframing tests as descriptions of system behavior – “when I do one thing, I should see this result”. Historically, those descriptions were the output of a computer program. Over time, the uses of BDD shifted toward Gherkin, an English-like but precise language.