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Today, we're excited to announce Kong Mesh 2.13. Kong Mesh 2.13 delivers full support for Mesh Identity for Kubernetes and Universal mode. Plus, it's been designated as a Long Term Support release, with support for a total of 2 years. But first, what's Kong Mesh for the uninitiated?

KAi, the AI assistant inside Kong Konnect, just got significantly more capable. Today, we're announcing an enhanced beta version powered by the new Kong Konnect MCP Server — a shared infrastructure layer that also opens up your API platform to IDE copilots and custom agents. The result? KAi can now do things it couldn't before, and those same capabilities are available wherever you work. If you've used KAi before, you'll notice the difference immediately.

AI agents are spreading across organizations rapidly. Each agent needs secure access to different Model Context Protocol (MCP) servers. Authentication becomes complex. Scaling creates bottlenecks. The dreaded "too many endpoints" problem emerges. You face a classic AI infrastructure headache. The numbers tell the story. Organizations using AI in at least one business function jumped from 55% to 78% in just one year. Generative AI usage specifically rose from 33% in 2023 to 71% in 2024.

Gartner just published research that should be required reading for every platform and infrastructure leader building for the agentic era. The report, "How to Enable Agentic AI via API-Based Integration," makes a stark claim: incrementally reworking existing APIs and connector-based integrations for AI agents is no longer sufficient.

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.

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.