Systems | Development | Analytics | API | Testing

Build Agentic Workflows: Expose API Orchestration as MCP Tools with Kong AI Gateway

Learn how to expose an API orchestration workflow as an MCP server using Kong AI Gateway, configure semantic guardrails, and build an agent with the Volcano SDK. We onboard GPT-4 behind /llm, orchestrate with DataKit, and debug MCP tools in Insomnia—end-to-end without adding server code.

Can We Still Trust the Code? #speedscale #qualityassurance #digitaltwin #trust #devops

The "Velocity Gap" is real. AI like Claude and GitHub Copilot are pumping out code faster than ever, but there’s a catch: Engineers don't trust it yet. We’re moving away from the old days of "clicking around" in a test environment, but how do we verify code at the speed of light? Ken breaks down why the future of QA isn't just "testing," it’s simulation. Video collab with @ScottMooreConsultingLLC Learn More: speedscale.com.

A Developer's Guide to MCP Servers: Bridging AI's Knowledge Gaps

Have you ever asked an AI assistant to generate code for a framework it doesn't quite understand? Maybe it produces something that looks right, but the syntax is slightly off, or it uses deprecated patterns. The AI is working hard, but it lacks the specific context it needs to truly help you. The Model Context Protocol (MCP) was designed to bridge this knowledge gap by giving AI assistants access to domain-specific knowledge and capabilities they don't have built in.

Best 5 Tools for Monitoring AI-Generated Code in Production Environments

AI-generated code is no longer experimental. It is actively running in production environments across SaaS platforms, fintech systems, marketplaces, internal tools, and customer-facing applications. From AI copilots assisting developers to autonomous agents opening pull requests, the volume of machine-generated code entering production has increased dramatically. This shift has created a new operational challenge: how do you reliably monitor AI-generated code once it is live?

Building the Foundation for Responsible Autonomy: Preparing for the Agentic Era of AI

Over the past two years, generative AI has transformed how we create, learn, and interact. But a more profound shift is already underway—one that changes not just how we work but who (or what) does the work itself. We are entering the era of agentic AI, where systems don’t merely answer questions—they reason, decide, and act on our behalf.