What working with enterprises taught us about empowering the individual

When we first started Hypermode, there was a conviction that AI could unlock the most value in large, complex, companies— especially highly regulated ones. There are the siloed business units, the post-M&A integration inefficiencies, the compliance hurdles, the sheer volume of manual workflows—and we believed we could build real leverage there.

So we started on hard-mode and went straight after the most complicated problems for AI.

And you know what? We landed.

Our systems are now running in production inside global intelligence agencies, top-tier banks, and firms driving late-stage drug discovery. That journey taught us a lot—not just about what works in the enterprise, but more importantly, what doesn’t scale beyond it.

We realized that in a room full of brilliant people, each with a different lens on the same process. And somewhere in that org chart, we realized that the person who understands the business problem well enough to describe it doesn’t always have the tools to build the solution. Meanwhile, the person with the technical chops to build often doesn’t understand the business context well enough to automate it safely and effectively.

The real question became: how do you enable the people who already understand the process to shape the agent?

From enterprises to the individual

Our work in enterprise AI shifted our perspective. We started building for the middle person: the network engineer debugging connectivity issues. The sales ops manager syncing Salesforce and Marketo. The actuary who knows the business inside out but lacks the tools to express that knowledge in code.

These folks don’t want a dev platform. They want to automate what they already know, without waiting six months for an enterprise-wide deployment plan.

That meant building tools that let line-of-business experts create agents themselves in a way that still respects the needs of central IT, security, and governance. We aim to let domain experts design 90% of the automation—and hand off the last 10% for IT to secure, scale, and deploy.

The idea of agents isn’t to replace your best engineers. It’s to supercharge your most knowledgeable operators. You still need governance. You still need observability. You still need someone to say, “This is safe, this is logged, this meets our bar.” But now, the person who actually knows what the process should be? They get to build the first draft.

How organizations mature their agent strategy

We’ve seen that adopting AI agents isn't a switch you flip. It's a journey. Most move through three key stages of agentic maturity:

1. Individual impact

This is where most companies start—and it’s where the spark happens for technically savvy folks who say, “This process is broken. I know how it works. I just need a better way to make it run.”

At this stage, the key is low friction. Domain experts need tools that are intuitive, fast, and safe. They should be able to build and iterate without waiting for approval or access from IT.

2. Team transformation

Eventually, the agents built by individuals hit a ceiling. Someone wants the same toil reduction (and productivity gains) from the agent but slightly tweaked for their flow. Security wants visibility and consistency. That's when the work gets real.

This is where organizations need more than just a wysiwyg builder. They need infrastructure. They need observability. They need to understand what agents are doing, where data is flowing, and how decisions are made.

3. Scaled customer experiences

At the highest level, agents go from internal accelerators to external differentiators. They handle underwriting workflows, fraud detection, customer personalization.

They don’t just reduce toil—they reshape how businesses engage customers.

Few companies get there overnight. We see companies of all sizes move from empowering individuals, to enabling teams with governance, to scaling agents with enterprise-grade infrastructure. Skip the middle and you get chaos. Skip the start and you get shelfware.

So, where are you on the curve?

If you’re just starting: Pick one process. Let the people closest to the work build the agent.

If you’re in the middle: Add guardrails. Let teams move fast and stay secure.

If you’re scaling: Deploy boldly. We’ve built the infrastructure, observability, and on-prem capabilities so you don’t have to.

The future isn’t just about agents that complete tasks. It’s about agentic systems that scale across users, teams, and customers.

That’s what we’re building.