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Testing AI Code in CI/CD Made Simple for Developers

Generative AI can produce code faster than humans, and developers feel more productive with it integrated into their IDEs. That productivity is only real if CI/CD tests are solid and automated. When not appropriately tested, you may encounter a production issue that you haven't seen before. According to the State of Software Delivery 2025 report, 67% of developers spend more time debugging and resolving security vulnerabilities in code generated by AI. That cancels out the efficient gains that they get from faster AI code generation.

QA Debt: The Silent Risk That Can Take Down Your Business

In engineering, we talk a lot about technical debt — the shortcuts and compromises made in code that pile up over time. But there’s another kind of debt that’s just as dangerous and far more invisible: QA debt. QA debt is what happens when testing isn’t given the same attention as features, architecture, or performance. It’s the accumulation of missed edge cases, outdated test suites, incomplete automation, or skipped regression checks.

A Developer's Guide to Improving AI Code Reliability

You’ve probably been there: your AI coding assistant just generated what looks like a perfect solution to your problem. Decent code quality, reasonable structure, and even some comments. You run it, and… it works. So you ship it. Three weeks later, your production logs are full of 500 errors from edge cases the AI never considered, or worse, you discover the code has been making unvalidated database calls that could have been prevented with basic input sanitization.

The Developer's Guide to Debugging AI-Generated Code

AI coding tools like ChatGPT, GitHub Copilot, and Claude have completely changed how we write software. From humble beginnings where non-AI-enabled code assistants made intelligent code suggestions, like Intellisense, the latest agentic tools can generate entire functions, suggest optimal algorithms, and even scaffold complete applications in minutes. However, as any developer who’s worked with AI-generated code knows, the output isn’t always perfect.

API World 2025: Growth, Memories, and Next Steps

A couple of weeks ago, our team returned from API World. We’ve officially had a few weeks to decompress and get back into the swing of things after an incredible time at API World 2025. Looking back, the experience was even more rewarding than I had imagined in my Pre-API World blog. This year was especially memorable for me, as I had the opportunity to attend my first tech conference and travel across the country for work. I’m still buzzing from everything I learned and the people I met.

Accelerating Cloudnative Development & DevOps

Cloud-native development, and the resultant rise of DevOps, has transformed how software is built, deployed, and maintained. By embracing containerization, microservices, and continuous delivery, organizations have been able to deliver features faster, scale with demand, and recover from failures more gracefully than ever before. Many organizations are adopting these practices to keep up with industry demands and improve efficiency and security.
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Top 14 Postman Alternatives

Postman has long been a go-to tool for API developers and QA engineers in providing a streamlined environment for testing and documenting APIs. Its user-friendly interface and robust features made it an industry standard. However, Postman isn't suitable for everyone. Its complexity has increased over the years, leading to a UI that can be overwhelming, and a steep learning curve - especially for beginners.

Looking Back, Looking Ahead: Thoughts on My First Year at Speedscale

When I started at Speedscale, I looked like this: And after one year of learning, growing, and keeping pace with innovation well, let’s just say the journey has left its mark: Of course, I’m joking (sort of). The truth is, this past year has been intense, energizing, and filled with new challenges. If anything, it’s made me feel younger in spirit, even if the mirror might disagree some mornings.

Simulating Multi-Agent Workflows to Find Hidden API Vulnerabilities

API gateways are often viewed as the centralized entry point for client HTTP requests in a distributed system. They act as intermediaries between clients and backend services, managing API request routing, load balancing, rate limiting, access control, and traffic shaping across multiple backend services. This API management is vital for many services and products, but many organizations can put too much stock in it.