Kong stands firmly at the center of AI and API convergence – News

Artificial intelligence is drawing a new blueprint as it aligns with application programming interfaces across the stack. Now, enterprises are racing to turn the AI and API convergence moment into results with platforms built for revenue from day one.

The goal is simple, but the path to success can be winding. At the Kong API Summit, conversations cut through hype and pushed toward a unified thesis for APIs, agents and governability. Kong Inc. leaned into that vision, bidding to be at the center of the agent-API conversation.

“Kong is positioning itself to be the infrastructure backbone of the agent economy,” according to Paul Nashawaty, principal analyst at theCUBE Research, during an analysis of Kong’s announcement-packed keynote. These included open-sourcing its Volcano development kit and adding native support for Model Context Protocol, or MCP, agents in Konnect.

Nashawaty and guests unpacked next-generation agentic connectivity and what that means for platform teams during Kong API Summit: The API Summit for the Agentic Era, through a series of exclusive broadcasts on theCUBE, News Media’s livestreaming studio. The through line for AI and API convergence: reduce complexity, increase control and move faster with guardrails. (* Disclosure below.) 

Here’s the complete keynote analysis from Paul Nashawaty:

Here are three key insights you may have missed from theCUBE’s coverage:

Insight #1: Agents are defining the AI and API convergence moment.

The summit’s subtext wasn’t subtle: consolidation wins and fragmentation bleeds budget. This year was a pivot from brazen hype to governed, monetizable AI-era plumbing. From there, the focus moves to who actually uses that piping — software agents that can find, decide and act across it. Kong stands firm that opting out means opting for irrelevance as agents become the new surface area for execution, according to Augusto Marietti, co-founder, chief executive officer and president of Kong.

Kong’s Augusto Marietti talks with theCUBE about AI traffic and the importance of a unified control plane.

“Every business will become agentic,” he told theCUBE while discussing whether becoming agentic is optional for enterprises. “It’s more about: ‘Do you want to be part of it or you want to be Yellow Pages?’”

But to stop going the way of the phone book, enterprises desire a playbook. To that end, standards are being established to make real-time, tool-rich interactions predictable, with the interface itself shifting from clicks to prompts, according to Marco Palladino (pictured), co-founder and chief technology officer of Kong. In practice, that means protocols like MCP stepping into the role that Representational State Transfer, or REST, played for APIs. It also means governance must become first class, so agents can act fast without going rogue. Against that backdrop, the next step is making agents easier to generate and expose directly through the prompt.

“I’m very bullish on agents. I’m very bullish on the ability to generate agents in a quicker way by abstracting away the infrastructure requirements, and I’m very bullish about exposing some of these agents to the customers that are now starting to use our products through the AI prompt,” Palladino said while speaking with theCUBE. “You could think of the AI prompt as being the smartest browser in the world.”

Here’s the complete video interview with Marco Palladino:

Insight #2: Scaling securely means unifying the control plane.

Of course, enterprises can’t govern what they can’t see — and many still can’t see much beyond the nearest team’s wiki. That missing system of record turns scale into a scavenger hunt and stops them from being able to take advantage of AI and API convergence. The majority still lack a reliable map from business capabilities to the services underneath, according to Rishi Singh, vice president and head of cloud and custom applications practice, North Americas, at Capgemini Financial Services.

Capgemini’s Rishi Singh talks with theCUBE about enterprise app modernization in terms of AI and API convergence.

“Right now, if you go to any large enterprise and you say, ‘Do you have a catalog which can define all of your business capabilities? What are the underlying services they’re running on?’ I think 90% of the answers would be no,” he told theCUBE. “I believe they should certainly invest in rationalizing all of that, because the moment you bring in agentic AI, that problem is going to compound.”

It all starts at the foundation. Teams with clean and discoverable APIs turn AI from demos into shipping features, according to Reza Shafii, senior vice president of product at Kong.

“If you have basically had your API foundation solidified, you’re suddenly in this amazing position where you can go much faster in establishing the AI initiatives,” he explained during an interview with theCUBE. “And if you have not, then you’re going to find out very quickly that you need to.”

Here’s the complete video interview with Reza Shafii:

Insight #3: Enterprises must monetize what they meter.

As the AI and API convergence moment matures, usage, value and cost need a common ledger. Kong’s acquisition of OpenMeter set the stage for Konnect Metering and Billing — a push to treat APIs, models and streams as billable products with real-time usage. If you can’t meter precisely — across APIs and every event — you can’t price, enforce or prove value, according to Peter Marton, co-founder of OpenMeter. Real monetization starts with deep, universal metering stitched into the platform.

Kong’s Ross Kukulinski and OpenMeter’s Peter Marton talk with theCUBE about real-time metering in the API modernization rush.

“The vendors want to have real-time metering because they want to have governance in place, they want to be able to control or even stop the traffic of certain features, but on the other end, the customers for the same reason want to see the consumption in real-time,” Marton told theCUBE. “They want to be able to take an action in their agent, in [their large language learning model], and they want to see that immediately reflected in both their usage and the estimated cost. That’s only possible on both sides with real-time metering.”

Of course, AI and API convergence’s promise has its caveats, chief among them being that AI’s cost profile isn’t forgiving. Seconds matter and surprises can be expensive. That is why tight, real-time metering is the only way to keep up the confidence, according to Ross Kukulinski, vice president of product management at Kong.

“[Because of] this rise of AI and the need to get the value out of the investment you’re making there, we realized that we really, really needed a deep metering and monetization,” Kukulinski said. “Billing — AI billing and AI revenue — is ultimately a metering problem.”

Here’s the complete video interview with Ross Kukulinski and Peter Marton:

To watch more of theCUBE’s coverage of the Kong API Summit, here’s our complete video playlist:

(* Disclosure: TheCUBE is a paid media partner for the Kong API Summit. Neither Kong, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or News.)

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