You swapped in a better model. You fine-tuned it. You threw more tokens at the problem. And still — your agents hallucinate, break under load, and deliver answers that were accurate about three hours ago. The model isn't the problem. Gartner recently flagged that up to 40% of enterprise agentic AI…
Recent research from Forrester’s David Mooter makes a few things very clear: the enterprises that win with agentic AI won't be the ones with the most agents — they'll be the ones with the best integration infrastructure behind them. If you've been following the agentic AI wave, you've probably…
The new Konnect Dev Portal Toolkit extension for Visual Studio Code gives you a live, portal-accurate preview of your content right beside the file you are editing. You watch a page take shape exactly as it will appear to your developers, as you type, without ever leaving your local editor. Konnect…
We're thrilled to announce a strategic technology partnership between Kong and ModelOp . As enterprises rapidly transition into the agentic era, they face a critical challenge: how to deploy AI fast enough to stay competitive without taking on unacceptable regulatory or security risks. Together,…
The MCP demo impressed the room. Then someone asked how 5,000 employees would connect to 40 MCP servers, and the answer was: one OAuth consent screen at a time. Per user. Per server. No central policy, no unified audit trail, and nothing stopping a personal account from getting wired into a work…
A new version of KAi, the Kong Konnect agentic platform assistant, is live. This is the release that turns KAi from a knowledgeable guide into something that can actually build inside your org — of course, within guardrails that you control. Until now, KAi could tell you how to set up a service,…
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…
Every few months, a frontier AI lab makes a move that says the quiet part out loud: agents are only as useful as the systems they can reach. The latest example is Anthropic's acquisition of Stainless, the company behind the tooling that turns API specs into SDKs and MCP servers. Anthropic's own…
Customers today face significant challenges as their Kubernetes environments scale. The proliferation of microservices, external integrations, and new AI workloads increases traffic volume and connectivity complexity, creating material risks to performance and availability. The core issue is a lack…
AI agents are only as capable as the tools they can reach. When an agent needs to query a database, file a support ticket, or pull data from a CRM, it has to find the right tool, authenticate, and invoke it — all at runtime. The Model Context Protocol (MCP) standardizes how agents communicate…
Key takeaways - An MCP server is a lightweight process that exposes tools, resources, and prompts to AI applications over a standardized protocol. - It acts as the bridge between an LLM-powered client and an external system — a database, API, file system, or SaaS product. - The protocol…
Three-quarters of enterprises are now piloting or deploying AI agents. But here’s the problem: actually integrating those agents with enterprise applications is proving to be one of the hardest parts of the whole endeavor. That’s the core finding of a recent Gartner research note, How to Integrate…
As organizations transition from experimental AI to production-grade systems, they often face a fragmented landscape of unmanaged LLM providers, complex tool integrations, and escalating security risks. Without a centralized orchestration layer, developers struggle to maintain consistent…
Scaling LLM and agentic AI adoption from pilot programs to enterprise-wide deployments is a massive logistical rollout. As AI and agentic usage grow, so does a nagging question for leadership: Are agents using the right tools to get the job done? While raw infrastructure metrics might tell you if a…
The shift from single-model AI features to multi-agent pipelines is no longer a future concern — it's running in production today. MCP has become the de facto protocol for tool-calling, agent-to-agent (A2A) communication patterns are proliferating, and enterprise teams are wiring together complex…
When enterprises started experimenting with LLMs, the governance challenge — while still difficult — was relatively contained once you had an AI Gateway for LLM traffic. You had a request going to a model, a response coming back, and a gateway in between to enforce policy. With the right solutions,…