How Enterprises Are Adopting Intelligent Systems Faster Than Expected

Matt Glickman, CEO and co-founder of Genesis Computing, has spent his career at the intersection of data, engineering, and large-scale financial systems. Before Genesis, he helped shape Snowflake’s product and financial services strategy. Before that, he spent decades leading data platform engineering at Goldman Sachs.

That background gives him a clear view of how quickly the AI landscape is changing. According to Matt, the speed of progress in agentic systems is unlike anything he has seen in his career.

Agents Are Not “Virtual Employees”

A common idea in the industry is that agents are a replacement for human workers. Matt argues that this framing is too small. Agents are not just digital employees. They make it possible to build systems and workflows that were previously too complex or too expensive for human teams to maintain.

Across Genesis customers, the trend is consistent. Organizations are hiring fewer people and shifting more operational workloads to intelligent systems. Tasks that once required large teams can now be handled by a small number of powerful agents.

This shift is not about scaling up hundreds of agents. It is about unlocking enough capability in one agent to take on the work of dozens or even hundreds of people.

From Specialized Agents to More Capable Systems

A year ago, agent systems needed heavy specialization. Each agent required tightly scoped instructions in order to perform reliably. The industry treated agents the way engineers once treated microservices: small units that had to be orchestrated carefully.

Model capabilities have since evolved. Context windows have expanded. Techniques for loading and retaining knowledge have improved. As a result, a single agent can now carry far more context and handle a larger portion of a workflow, much closer to how a human reasoner would operate.

Instead of coordinating many small agents, companies can rely on fewer but significantly more capable systems.

The Most Valuable Shift: Capturing and Preserving Knowledge

Matt highlights the outcome that resonates most with customers. Enterprises are full of institutional knowledge stored in people’s heads. When those individuals leave, the knowledge leaves with them.

Agentic systems change this.

Organizations can now extract operational logic, best practices, and domain expertise into a system that learns, retains context, and becomes part of the company’s infrastructure. This knowledge becomes an asset that persists, even as teams change.

For many organizations, this is becoming a competitive advantage.

Why This Matters for Data Leaders

Enterprises are moving quickly because the value is clear:

• Reduced dependency on growing headcount
  
• Faster delivery across data and engineering workflows
  
• More consistent execution and fewer errors
  
• Knowledge that becomes part of the system instead of walking out the door
  

Agentic systems are not simply automating tasks. They are reshaping how companies build and maintain mission-critical systems.

See How Genesis Accelerates Data Engineering

If you want to see how Genesis applies these concepts inside your existing Snowflake or Databricks environment, we can walk you through a live demonstration tailored to your stack.

Request a demo and explore what agentic automation looks like in your environment.