Systems | Development | Analytics | API | Testing

We’re excited to announce the general availability of Kong Insomnia 12.3! Kong Insomnia 12.3 TL;DR? Your New Year’s resolution is probably something along the lines of “work smarter, not harder.” Our resolution is to make that actually possible. Insomnia 12.1 and 12.2 sharpened your tools, and now Insomnia 12.3 removes the friction to allow you to focus on building great endpoints. Less maintenance, more momentum.

The agentic era is here, and it's exposing a critical gap in enterprise infrastructure. AI agents are no longer experimental. As many as 9 out of 10 enterprise organizations are actively adopting AI agents. Agents are making autonomous decisions, orchestrating complex workflows, and interacting with dozens of services in real time.

As APIs evolve into the strategic connective tissue of digital products and AI, organizations often fail to unlock their value due to a critical misalignment between business goals and technical execution. To transform APIs into genuine growth levers, enterprises must embrace full-lifecycle API product management, prioritizing upfront strategy, robust contract design, and scalable developer experiences over mere endpoint creation.

In one of our posts, Kong AI/MCP Gateway and Kong MCP Server technical breakdown, we described the new capabilities added to Kong AI Gateway to support MCP (Model Context Protocol). The post focused exclusively on consuming MCP server and MCP tools through Kong MCP Gateway. Now, it's time to check how an AI agent can leverage the AI and MCP infrastructure exposed and protected by Kong AI/MCP Gateway.

If your 2026 resolution is to finally get AI costs under control, we've got you covered. Every January, the same resolutions show up: eat better, exercise more, finally learn that language, finally figure out that production use case for AI agents (OK, this one isn’t so typical unless you operate in our universe). But if you're responsible for your organization's AI strategy, we'd like to suggest a different one for 2026: stop letting AI be a cost center.

While AI is revolutionizing the future of nearly every industry, it’s also created a unique set of challenges and liabilities that will need to be addressed as the area grows. Enter AI governance: a set of rules and best practices to ensure that AI is used effectively, securely, and responsibly. But what exactly does that mean, and why is it so crucial for businesses?

API endpoints process requests that power our digital world—from social feeds updating in real-time to enterprise systems syncing global inventories across continents. APIs comprise over 57% of Internet traffic, yet API endpoints often remain misunderstood. This leads to design inconsistencies, brittle integrations, and costly maintenance issues. Sound familiar? If you've merged microservices and untangled mismatched status codes, you know the pain.

Another year is wrapping up, and we’re taking a moment to reflect on what made 2025 a defining year for Kong. With major advances in building the AI connectivity layer and soaring enterprise adoption of agentic systems, this year sparked a hockey-stick surge in demand for the infrastructure that powers intelligent agents. Below is a rundown on the updates, the innovations, and the moments that moved the industry in one year-end recap.

Kong AI Gateway 3.13 moves enterprises from AI experimentation to shipping production-grade agents by unlocking new capabilities focused on agentic security, developer productivity, and resilience, including MCP tool-level access control, expanded provider support, and smarter load balancing.

Happy holidays from the Kong team! Consider this our gift to everyone who's been asked "what's the ROI on AI?" one too many times. The AI boom has a dirty secret: for most enterprises, it's bleeding money. Every LLM call, every agent invocation, every API request that powers your AI products — they all cost something. And right now, most organizations have no idea what they're spending, who's spending it, or how to control that spend. Finance teams are flying blind.