There’s this thing that happens whenever a new foundational technology slips out of the lab and into the wild…everyone rushes to fit it neatly into yesterday’s boxes.
When electricity first lit up New York in the 1880s, people still talked about it like gas lighting, measuring it in candlepower, baffled that this flickering invisible fuel didn’t fit the usual mold.
And when we first got the internet, well, it was just another flavor of telecom–that is until suddenly it was everywhere, rewriting the fundamentals of everything from banking to bookselling.
AI’s moment feels a little like that.
Everyone knows it’s here; everyone agrees it’s big. But we're still mostly treating AI like some faster version of what came before, shoehorning it into existing data infrastructures as if what we're dealing with is just a bigger, smarter database.
That worked but the seams are starting to burst, because today’s AI isn’t just analytics turned up to eleven, it’s trillions of autonomous agents, tiny software minds working in parallel, making millions of real-time decisions. It should be no surprise that the old architectures can't hold, simply because no one ever expected them to.
This is precisely the fracture point Jeff Denworth, Renen Hallak and others spotted almost a decade ago at the founding of VAST Data.
As Jeff describes below, their realization was clear–the world didn’t just need faster storage, more processors, or slicker databases, they needed an operating system explicitly designed for an era where data would no longer be passive but agentic.
This world, which has come to fruition, is one where the system is always on, breathing in sensor data from the edge, enriching and annotating it mid-flight, and passing it directly to thousands of GPUs to crunch through billions of inference calculations in real time.
That’s not just an upgrade—it's a fundamental redesign.
The core innovation from VAST hinges on what Denworth cites as "Disaggregated, Shared Everything," (DASE) in which they’ve torn apart the traditional marriage between compute and storage, spreading data across flash-based clusters separate from the processing cores themselves.
Imagine CPUs and GPUs not confined to the narrow lanes of tightly coupled motherboards, but instead reach freely across racks and data halls, each core able to access any SSD, in parallel, without getting snarled in endless coordination chatter.
The insight here is revolutionary, particularly at true hyperscale where millions of agents consume exabytes of metadata. Partitioning data becomes not merely inefficient but impossible.
But VAST didn't stop at rethinking storage and compute. They took the concept deeper, embedding intelligence directly into the infrastructure’s DNA.
Enter the Agent Engine, announced today. It’s here the narrative shifts decisively from infrastructure into the future.
The Agent Engine isn’t just another "plug-in-your-model-and-run" toolkit. It’s a complete runtime environment purpose-built to deploy, manage, and orchestrate AI agents within a fully distributed operating system.
Built atop the foundational layers—the Data Store (flash-based storage handling files, objects, and block volumes) and the VAST Database (a uniquely parallel structure handling SQL, vectors, and Kafka-like event streams)—the Agent Engine represents the upper cerebral cortex of this distributed organism.
To understand the Agent Engine’s true punch, consider it less as conventional software and more as a brain orchestrating a swarm. Its role is deceptively simple– deploy agents that make sense of the torrent of contextualized data flowing up from the Insight Engine (a close cousin within the VAST ecosystem that takes unstructured streams and generates embeddings, making sense out of chaos).
Each agent can invoke tools, run searches through databases, probe file directories or S3 buckets, and even trigger external actions. They cannot do laundry. Yet.
But here’s what else they can do: they can communicate through clearly defined, standardized interfaces for flexibility, letting developers design workflows and pipelines rapidly through intuitive, low-code interfaces.
One subtle detail underscores the difference in approach us that observability and resilience are baked in from inception, not bolted on later.
VAST built a sophisticated distributed tracing and auditing capability into the Agent Engine, ensuring every action by every agent is not only logged but visible in real-time. No more black-box decisions; instead, enterprises gain immediate visibility into pipelines, with each step documented.
Fault tolerance isn’t an afterthought either—it’s integral, ensuring pipeline functions survive individual node failures, making the entire system robust at scales previously considered unthinkable.
As Denworth points out, when your system architecture fundamentally eliminates partitioning, suddenly your data can move fluidly, without the overhead of traditional east-west networks.
Here, each agent accesses data directly from a global transactional structure embedded at the flash-storage level. As he puts it, "no two CPUs or GPUs ever need to talk to each other" to read or write data, creating a radically simpler, more efficient model. It’s this radical simplicity that makes previously unimaginable scale possible—and affordable.
In this architecture, the data infrastructure itself becomes economically and technically efficient, flash storage performing at or below the cost of hard drives, thanks to global compression and erasure coding algorithms impossible on legacy spinning disks.
When you shift infrastructure costs lower, you don’t merely save money, you change what’s possible. Organizations can retain, analyze, and leverage far greater quantities of data in real time, feeding an army of agents with context and clarity.
Where does this take us?
Imagine a world where AI isn’t constrained by yesterday’s database silos and analytics systems, but liberated into genuine autonomy.
Autonomous vehicle fleets, digital twins monitoring real-time city infrastructure, predictive healthcare systems dynamically responding to each patient’s live stream of data–all powered by trillions of agents continuously learning, adapting, and improving on the fly.
This is precisely the future that Jeff Denworth’s Agent Engine—and the wider VAST AI Operating System—was designed for.
Just as electricity quietly reshaped the world in ways Edison himself couldn't foresee, this new operating system isn't merely upgrading today’s infrastructure it’s building tomorrow’s cognitive foundation.
It's not flashy marketing or hyperbolic futurism; it's simply architecture catching up with reality.