Discover the future of intelligent API traffic management. Learn how AI-powered gateways enable smarter routing, adaptive security, and real-time decision-making to optimize and secure API ecosystems.
AI coding tool spend is projected to top $13 billion in 2026, compounding at more than 60% a year. That's an entire category showing up at once, according to the recent Palo Alto Networks' Secure AI Coding report. These agents don't just autocomplete a line of code anymore. They plan. They act.…
AI infrastructure is changing fast. Enterprises are no longer building around a small set of models exposed through relatively consistent interfaces. New model architectures are emerging (Here’s looking at you Jev!). Providers are introducing new APIs and capabilities. Enterprises are running…
New AI cost management capabilities help organizations price, attribute, plan, control, and optimize AI spend across models, applications, teams, and agents. AI is getting easier to build with. Paying for it is getting harder to manage. As organizations move from AI experiments to production…
Kong Webhook Engine turns business events into triggers for applications and AI agents — connecting what happens in the business to what happens next. Most AI agent interactions today start with an explicit request. A user sends a prompt. An application invokes an agent. A workflow calls one. The…
In April 2026, Uber burned through its entire year’s AI budget by the middle of the month, driven largely by usage of Anthropic's Claude Code and Cursor. Nothing was broken. No one misused the tool. Engineers were doing exactly what every team's been told to do: adopt AI, use it well, use it…
Enterprise AI governance requires a composed stack connecting high-level risk and compliance oversight with real-time runtime enforcement. While oversight tools manage inventories, approvals, and evidence, AI gateways apply policy controls directly to live model, API, MCP, and agent traffic.…
Kong and Straiker are partnering to help enterprises secure AI agents across the traffic, tools, and systems they already manage through Kong AI Gateway . The integration brings Straiker into the Kong ecosystem, giving customers a way to add deeper security visibility, testing, LLM runtime…
In July, we announced Kong AI Gateway 2.0 in private beta and made a promise: freed from the API gateway release train, AI Gateway would ship at the speed of the AI ecosystem itself. We said you'd see the evidence quickly. Here it is. Kong AI Gateway 2.0 is now generally available , and…
You've mapped the architecture. Your agents retrieve context from external tools, coordinate with other agents, and propagate mutations through your systems. The model logic is solid. An agent gateway is the control layer for traffic between agents, models, tools, APIs, and data sources. It applies…
Most teams building multi-agent systems hit the same wall at roughly the same point. The prototype works. Agents chain together, tasks complete, the demo impresses the room. Then someone asks: "What happens when this runs a thousand times a day? What happens when an agent calls an external API…
Every team running production LLMs has had the same idea: not every request needs the frontier model. Intelligent model routing (or LLM routing)— choosing a model per request on criteria such as task complexity, cost, latency, or quality — enables more efficient model usage. The idea is easy.…
You've probably seen the demos. An AI model kicks off a task, hands pieces of it to other AI models, and somehow the whole thing gets done. Emails drafted, code reviewed, reports summarized — all without a human in the loop. While a single agent doing one thing is impressive, the true paradigm…
A decade ago, cloud and API sprawl got ahead of governance, and enterprises spent years trying to account for costs they'd never tracked. Today, we're seeing the same pattern around AI, with hundreds of customers proxying traffic via Kong AI Gateway, which includes LLM, MCP, and agent connectivity.…
You've diagnosed the problem. Your agentic AI initiatives are stalling — not because the models are wrong, but because the integration layer underneath them wasn't built for this. Batch data, rigid schemas, fragmented governance, no real-time event delivery. The plumbing is the bottleneck . Now the…
If you've been around long enough to remember when iPaaS was the answer to everything, you know the pattern. New paradigms arrive. Someone realizes that wiring it into existing infrastructure is harder than the demos suggested. An integration layer gets built. That layer slowly becomes…
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…