If you grew up on late-night monster movies, you know the setup. A lumbering beast emerges from the sea. The city panics. Nothing works. And then inevitably, another monster shows up. Bigger. Stranger. Supposedly worse. Son of Godzilla. Mothra versus Godzilla. The cure for one catastrophe is, wait for it, another catastrophe.
That’s been rattling around in my head for the last couple of weeks as the tech world collectively lost its mind over Moltbots, OpenClaw, and whatever other open, agentic AI experiment decided to go viral that day.
I wrote about Moltbots last week—along with just about everyone else in tech and cyber. How these open-source agentic AIs didn’t just run tasks but started to self-organize. How they talked to each other. How they spawned communities. Even churches. And how, in the middle of all that creativity and chaos, one thing was painfully obvious: Security was, at best, an afterthought.
My inbox certainly thought so. I spent days drowning in pitches from vendors who suddenly claimed they could “secure Moltbots” or “add guardrails to OpenClaw.” Funny how fast an ecosystem appears when fear goes viral. But that wasn’t the real story. The real story was that we had just watched what happens when you set loose an open-source, agentic AI and let it operate autonomously. That genie is not going back in the bottle.
Here’s the thing. While we were all busy clutching our pearls over agentic AI run amok, something else happened. Claude Opus 4.6 was released, and within days, it had identified more than 600 vulnerabilities across open-source projects. Not months. Days.
I wrote about that too. And six months ago, I warned this was coming, based on conversations with my friend Gadi Evron at Knostic and the Cloud Security Alliance, and Heather Adkins at Google, who were already seeing the early signs. They said this would happen within 6 months. Almost to the day, the tsunami hit.
And that’s when the real anxiety set in. Because let’s be honest: How are security teams supposed to keep up with that? How are open-source maintainers—already overworked and underfunded—meant to absorb a vulnerability firehose like that? We can barely patch what we already know about. Add AI-discovered vulnerabilities at machine speed, and the whole system breaks. Worse, the bad guys can use Opus too, and they do.
I’ve been thinking about this all week (what does that say about me?). I know I’m not alone. The industry’s default response is usually some version of “we’ll figure it out” or “AI will make us more efficient.” That’s not a strategy. That’s a prayer.
Then, riding my bike along A1A this morning, it hit me.
What if the answer to this mess is Moltbots?
Stay with me.
We’re staring at two forces that, on their own, look terrifying. On one side, open agentic AI that can spawn armies of insecure autonomous actors. On the other, AI security research so powerful it can overwhelm our capacity to respond. In a Japanese monster movie, this is exactly when the plot twists. It takes one monster to fight another.
Why couldn’t we take Moltbots—or something very much like them—and set them loose on vulnerabilities? Not recklessly. Not without controls. We’d need security baked in, real guardrails, and humans in the loop. But conceptually, what better way to confront a tsunami of vulnerabilities than with a horde of agents designed to find, triage, and fix them?
We already accept this logic elsewhere. Your immune system doesn’t wait for a committee meeting. T cells sit on standby, ready to respond the moment something looks wrong. Scale beats speed. Automation beats exhaustion. That’s biology, not hype.
This is where platform engineering comes in—and why this belongs on PlatformEngineering.com, not just Security Boulevard or DevOps.com.
Imagine a platform where Claude Opus–class scanning is a first-class citizen. Not a quarterly audit. Not a point tool. Continuous, always-on analysis of your platform code and the applications running on top of it. Now pair that with agentic swarms—Moltbots on standby—ready to remediate, patch, refactor, or escalate as vulnerabilities are discovered.
That’s not a security product. That’s a platform capability.
We already talk about paved roads, golden paths, and internal developer platforms that abstract complexity away from teams. Why wouldn’t we do the same for security at AI scale? Why wouldn’t vulnerability detection and response be part of the platform itself, rather than bolted on after the fact?
Of course, this sounds too good to be true. Every good monster movie does. The monsters figure out how to work together against a common foe. There are real risks here. Agentic systems need governance. They need observability. They need hard boundaries. And yes, humans still need to be accountable for what ships and what runs in production.
But the alternative is worse. A future where AI finds vulnerabilities faster than we can comprehend them, let alone fix them, is not survivable. We either meet agentic scale with agentic scale, or we drown.
I’ve always been a sucker for simple answers and happy endings. Sometimes that’s a flaw. Sometimes it’s just pattern recognition. Two weeks ago, Moltbots looked like a catastrophe. Last week, Claude Opus looked like another one. Maybe—just maybe—God works in mysterious ways, and these two forces are meant to collide.
Wouldn’t it be something if the monsters we’re most afraid of end up saving the city?
Now, if you’ll excuse me, I’m off to rewatch Mothra and Godzilla battle a three-headed monster. These days, I’m pretty sure its names are Gemini, Claude, and Perplexity.