Ex-EQT investor Doreen Huber joins Interface Capital with eye for cyber deals amid ‘extremely scary’ AI agent boom

The New Reality of Autonomous Threats

We have spent the last decade talking about automation, but we are entering a phase that feels fundamentally different. The shift from simple algorithms to autonomous AI agents is creating a new category of risk that most founders are not yet equipped to handle. When Doreen Huber, a seasoned partner from EQT, moves over to Interface Capital with a specific mandate to find cyber startups, it is time to pay attention.

The move isn't just a personnel shift in the venture capital world. It reflects a growing anxiety among those who actually understand the infrastructure of the internet. We are moving toward a web populated by agents that can think, pivot, and execute without a human in the loop. For builders, this means the old playbooks for security are becoming obsolete overnight.

The Problem with Agents

In my experience, the tech community tends to get blinded by the shiny utility of new tools. We see an AI agent that can book travel, write code, or manage a calendar, and we think about efficiency. What we don't think about often enough is the attack surface. An autonomous agent is essentially a user with high-level permissions that doesn't sleep and can iterate on a breach attempt a thousand times a second.

Huber’s move to focus on this "extremely scary" boom in AI agents is rooted in a simple truth: our current defense systems are designed to stop humans or predictable bots. They are not designed to stop an LLM-driven entity that can social-engineer its way through a help desk or find a zero-day vulnerability by reasoning through a codebase.

Why Builders Should Be Worried

If you are building in the crypto or AI space, you are already a target. But the nature of the threat is evolving from blunt force to surgical precision. Here is why this shift matters for your roadmap:

• Identity is broken: If an agent can perfectly mimic a founder's voice or writing style, your internal authentication processes are worthless.
• Permission creep: We give AI tools access to our APIs and databases to make them useful, but we are effectively giving a skeleton key to an entity we don't fully control.
• Speed of exploitation: Traditional patches take days or weeks. An AI agent can identify a flaw and exploit it across an entire ecosystem in minutes.

The Opportunity in the Chaos

While the threat landscape is worsening, this is exactly where the next generation of resilient companies will be built. Huber isn't just looking at the risks; she is looking for the founders who are building the shields. For the builder-first crowd, this is a call to action. We need security that is as intelligent as the threats it faces.

We are seeing a move away from perimeter defense toward what I call "behavioral verification." It is no longer enough to know who is logging in; we need to know how they are behaving once they are inside. If a user’s behavior pattern shifts by even a fraction of a percent, the system needs to be able to isolate that agent immediately.

The transition from EQT to a more agile firm like Interface Capital suggests that the solutions to these problems won't come from the legacy giants. They will come from small, technical teams who are willing to break things to see how they work.

The Founder Perspective

I have seen plenty of cycles where a new technology creates a gold rush, followed by a massive wave of theft and exploitation. We saw it with DeFi, and we are seeing the early stages of it with AI. The difference here is the scale. A smart contract bug is a localized disaster; a compromised autonomous agent with access to a corporate network is a systemic failure.

Founders need to stop treating security as a checkbox for their Series A pitch and start treating it as the core value proposition. If your AI platform isn't secure, it isn't a platform—it’s a liability. The influx of smart capital into this niche, led by investors like Huber, confirms that the market is beginning to price in this risk.

What to Build Next

If I were starting a new project today, I wouldn't be building another wrapper for an LLM. I would be looking at the following areas:

• Agent Sandboxing: Creating environments where autonomous agents can operate without having the ability to export sensitive data or modify core system architecture.
• Proof of Humanity: Robust, privacy-preserving ways to ensure that the entity on the other end of a transaction is a person, not a script.
• Automated Red-Teaming: Using AI to constantly attack your own infrastructure to find holes before a malicious actor does.

A Skeptical Take on the Hype

Let’s be honest: not every startup claiming to use "AI for security" is going to make it. We are going to see a lot of noise. VCs are moving into this space because they smell fear, and fear is a great motivator for sales. But as a founder, you have to look past the marketing. The real winners won't be the ones with the best pitch decks; they will be the ones who understand the technical limitations of LLMs and build safeguards around them.

Huber’s focus on the "scary" side of AI isn't pessimism; it's pragmatism. It’s an acknowledgment that we’ve built something we don't quite know how to fence in yet. For those of us in the trenches, that shouldn't be a reason to stop building, but it is a reason to start thinking like an attacker.

The Takeaway

The arrival of heavy-hitting investors into the AI-cyber crossover marks the end of the honeymoon phase for autonomous agents. The tools are here, the threats are real, and the money is following the problem. If you’re a builder, your priority shouldn't just be making your AI smarter—it should be making it safer. The next billion-dollar companies won't just be the ones that give us new capabilities; they’ll be the ones that prevent the ones we already have from being turned against us.

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