Systems | Development | Analytics | API | Testing

In the rapidly evolving landscape of AI-driven development, the Model Context Protocol (MCP) has emerged as the critical standard for connecting AI applications to the data and tools they need. We are excited to announce the Technical Preview (TP) of Kong MCP Registry, a major milestone in our mission to provide the most comprehensive platform for modern API and AI management.

A mid-sized enterprise had a straightforward but powerful idea: use their locally-hosted AI model to automatically generate summaries of employee performance review data stored in their SQL Server database. The workflow seemed simple enough: The reality? This "simple" integration touches on some of the thorniest problems in enterprise software: database security, API orchestration, authentication, timeout management, and reliable data transformation.

With Valentine’s Day fast approaching, love is in the air. And apparently, so are breakup emails. This isn’t just about one pricing change. It’s about a pattern. Some tools promise “free forever” to get you invested, watch you build workflows, and then change the rules. They know you’ve onboarded your teams, documented your APIs, and integrated the tool into your daily work. By the time they spring the paid tier on you, switching feels painful.

January didn’t bring radical changes to Node.js, and that’s precisely why it was important. Instead of headline features, the first month of the year reinforced a clear direction for the ecosystem. Stability over novelty. Signal over noise. Security handled with context rather than urgency. For teams running Node.js in production, January delivered clarity. Here’s what actually mattered.

In the semiconductor world, “software" is more than just application code. It is a complex stack of firmware, bootloaders, microcode, drivers, and Board Support Packages (BSPs) that are intricately linked to the hardware being designed. To secure the supply chain, meet customer expectations, and maintain market access, semiconductor leaders need a dynamic, "living" SBOM strategy that assesses risk in real-time and provides a single source of truth for all teams to work from.

While every organization races to deploy AI agents faster, a quieter crisis is compounding in the background, and it will play a large part in determining who survives the agentic era. The numbers are stark. Too many executives see AI governance as a brake on innovation or something to figure out later, after the speed problem is solved. With agentic AI, that's backwards.

While every organization races to deploy AI agents faster, finance departments are watching something alarming unfold—and it will play a large part in determining who survives the agentic era. The numbers are stark: 84% of companies report more than 6% gross margin erosion from AI costs. Within that, 26% report erosion of 16% or more. And only 15% of companies can forecast AI costs within ±10% accuracy—the majority miss by 11-25%, and nearly one in four miss by more than 50%.

Artificial Intelligence in real estate is no longer a future concept or a conference buzzword. It’s already reshaping how properties are leased, managed, valued, and invested in — often quietly, behind the scenes, inside operational workflows. Over the past months, ORIL has been hosting conversations with founders, CEOs, operators, and technology leaders on the Innovation Blueprint podcast, discussing how AI is actually being used in PropTech today. Not hypotheticals. Not hype.

Executive Summary: As enterprises integrate AI and large language models (LLMs) into their data workflows, the need for predictable, secure, and auditable database interactions has never been greater. Deterministic queries—particularly those encapsulated in stored procedures—provide the guardrails necessary for both human analysts and AI systems to access sensitive data safely.