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For a long time, I thought the biggest breakthrough in AI would come from building a model that could think better than the one before it.
Bigger context windows. Better reasoning. More accurate answers. Every new generation seemed to move us closer to AI that could handle increasingly complex tasks.
But recently, I’ve started looking at a different question.
What happens when AI stops working alone?
Imagine a business where one agent researches a new market, another analyzes customer behavior, a third develops a marketing strategy, and a fourth executes the campaign. Each agent might be excellent at its individual task. Yet the entire system can still fail if these agents cannot coordinate their actions, exchange information reliably, or operate across different services.
This changes how I think about the next phase of AI.
The bottleneck may no longer be intelligence alone. It could be the infrastructure connecting that intelligence to the real world.
An AI model can generate a plan, but a plan is not execution. An agent can complete one task, but an economy requires many participants to interact. And when those interactions happen across different applications, platforms, and systems, compatibility and trust become essential.
That’s the part of the agent economy I find particularly interesting.
Kite is building infrastructure for this emerging environment, where AI agents can become active participants rather than simply tools waiting for human instructions. To me, the broader opportunity lies in making autonomous activity practical at scale, not just making individual agents more impressive.
Of course, there’s a difference between a compelling vision and widespread adoption. Developers need clear reasons to integrate the infrastructure, businesses need measurable benefits, and users need confidence that autonomous systems can operate as intended. Those are the challenges worth watching as the ecosystem develops.
My takeaway is that the next major AI breakthrough might not be another model that scores higher on a benchmark.
It might be the infrastructure that allows thousands of capable agents to work together as one connected system.
Technical point: The distinction is between model capability and system capability. Improving one agent can improve an individual task, while improving the infrastructure between agents can potentially unlock entirely new workflows.
Self-critique: Interconnected agents also introduce more dependencies and potential failure points. More automation does not automatically mean better outcomes. The real measure of success will be whether these systems deliver reliable results and genuine value beyond what a single agent can already achieve.
I’m watching Kite through this broader lens.
What do you think will create more value in the long run: smarter AI models, or better infrastructure connecting them?
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