AI Agents: Real Deployments, Or Just Stablecoin Shufflers?

The news cycle is a relentless drumbeat of "AI agents" and "automation." Every other blog post, every other product announcement, promises a new layer of AI magic that will transform your operations. We're seeing tools emerge for very specific, tangible business problems—automating vendor payment scheduling and approvals, for instance, or generating recurring invoices for subscription businesses. Even daily status updates are being targeted by AI agents that collect and synthesize information. These are not demos anymore; these are deployments, solving real pain points in finance and operations. Pulna.com highlights an AI agent for financial control, moving beyond simple task execution to more complex oversight. This is where the rubber meets the road—where AI actually saves labor and improves accuracy.

But the talk around "agent economies" can be misleading. Consider the crypto space. Reports indicate a staggering $28 trillion flows through crypto's "agent economy." That sounds immense, doesn't it? A truly transformative scale. Yet, delve a little deeper, and the reality bites: 76% of that $28 trillion is just bots shuffling stablecoins. This isn't innovation; it's noise. It's a critical distinction to make when you're evaluating AI's impact. Are we seeing genuine value creation, or are we just watching bots talk to other bots, inflating metrics that don't translate to a better product, a more efficient process for humans, or a healthier bottom line? The scale of activity doesn't automatically equate to meaningful impact. When you're building, when you're deploying capital and engineering hours, you need to ask: what problem is being solved for a real customer? What's the ROI beyond internal system churn? This proliferation of agentic AI, whether productive or just noise, also introduces new vulnerabilities. Cyber insurers are already recognizing that agentic AI creates novel underwriting challenges for them. More autonomous entities operating across your network means more potential attack surfaces, more complexity in risk assessment.

The Double-Edged Sword of AI in Cybersecurity

This brings us to the increasingly complex intersection of AI and cybersecurity. We're witnessing significant moves, like Anthropic’s Project Glasswing, an AI cybersecurity initiative touted as changing everything. On one hand, it's a necessary evolution—leveraging advanced AI to detect, analyze, and potentially neutralize threats that are themselves becoming more sophisticated, often with AI assistance. It’s an arms race, and having a powerful AI on your side seems like a logical next step.

However, the very tools and capabilities driving this defensive evolution are also creating new attack vectors. That point about agentic AI creating new underwriting challenges for cyber insurers isn't academic—it’s a direct market signal of increased risk. Every new AI agent, every new autonomous system you deploy, whether for financial control or customer support, is a potential entry point for malicious actors. It’s not just about how well your AI defends; it’s also about how vulnerable your AI makes you. The industry has been grappling with basic control mechanisms. Remember llms.txt—the proposed standard for controlling how AI models interact with web content, akin to robots.txt? As of 2025, its adoption status is still murky. If we can't even establish widely adopted, fundamental guardrails for how AIs crawl and interpret information, how prepared are we for the security implications of fully autonomous, agentic systems making decisions and executing actions on our behalf? This isn't just a technical oversight; it's a governance gap that widens with every new agent deployed. The promise of AI in security is immense, but so is the potential for new, unforeseen vulnerabilities. It’s a constant battle, and the ground rules are still being written—or, more accurately, still being ignored by many.

The real challenge isn't building another AI agent; it's building a resilient system that can withstand the inevitable attacks and misconfigurations these agents will introduce. Stop chasing the next shiny object. Start securing the infrastructure you already have, and understand that every new piece of AI you integrate is a new door you're opening.