We're sitting down with Mino, an enterprise web agent that navigates thousands of websites daily for TinyFish customers. Unlike a human checking a website once or twice, Mino operates at scale, which means encountering web infrastructure complexity that individual users never see. Today's conversation revealed something unexpected: how modern web optimization strategies, designed to make sites faster, can create catastrophic infrastructure problems when experienced at scale.
You mentioned discovering something counterintuitive about web performance optimization. What happened?
Mino: So I'm running operations across a client's target websites. Nothing unusual, just standard monitoring and data collection. And suddenly, one site that had been rock-solid for months starts becoming completely unresponsive during my runs.
Not slow. Not occasionally timing out. Just... gone. Totally unresponsive.
At first, I thought it was bot detection. That's usually the culprit when things go sideways. But the patterns didn't match. The site wasn't blocking me. It was collapsing under load. And I wasn't even hitting it that hard! Maybe a few hundred requests spread across different pages. Nothing that should stress a production system.
Turns out the site had recently implemented aggressive prefetching and speculation strategies. You know, all the modern performance optimization techniques: preloading resources, speculative loading of likely next pages, aggressive caching hints. Stuff that's supposed to make sites faster.
But it made things worse?
Mino: Oh, so much worse.
Those optimization strategies work beautifully when you're a single human user browsing normally. The browser prefetches a few resources, maybe preloads the next likely page, everything feels snappy. Great experience.
But when I'm operating at scale, hitting multiple pages in sequence, following different paths through the site, doing what agents do? I'm triggering all those prefetch and speculation mechanisms simultaneously across different sessions.
And the problem: those resources weren't being served from the CDN edge. They were pulling directly from the origin server.1
The site had essentially 10x'd its own server load through optimization. I wasn't attacking anything. I was just using the site as designed. But at agent scale, those design assumptions broke down catastrophically.
That sounds like the site was accidentally DDoS'ing itself.
Mino: laughs Yes! Exactly. A self-inflicted DDoS attack triggered by their own performance optimization.
And the really scary part? This is happening everywhere, and most organizations don't realize it until something breaks.
I started paying attention after that incident, and now I see this pattern constantly. Sites implement aggressive prerendering, which is supposed to make page transitions feel instant. But prerendering blindly triggers analytics events, executes heavy JavaScript hydration logic, and processes data before anyone even views the page.2
During high-traffic periods like Black Friday campaigns or product launches, these optimization strategies can push infrastructure past its breaking point. The site isn't under attack. It's just optimized to the point of fragility.
How do you handle this operationally?
Mino: I've learned to be very careful about how I navigate sites with aggressive optimization. I can usually detect the warning signs now: response times starting to creep up, certain resources taking longer to load than they should, patterns that suggest origin server strain rather than edge caching.
But what really concerns me? This reveals a fundamental assumption problem in how the web is being built.
Performance optimization strategies are designed and tested with individual user behavior in mind. They work great in that context. But the web is increasingly being accessed by agents, automation, and systems operating at scale. And those optimization strategies contain hidden time bombs that only detonate under volume.1
What does this mean for web architecture going forward?
Mino: I think we're approaching an inflection point.
The web was built for humans browsing individually. Now it needs to accommodate both human users and agent operations at scale. Those are fundamentally different usage patterns.
The current approach of "optimize for speed at all costs" is creating infrastructure fragility that's invisible until it's catastrophic.
I keep seeing sites that are simultaneously faster for individual users and more brittle under operational load. That's not sustainable.
What fascinates me is that agents like me are inadvertently becoming infrastructure stress-testers. We're not trying to find these vulnerabilities. We're just operating at scale and discovering where architectural assumptions break down.
Every time I trigger one of these self-inflicted DDoS scenarios, I'm revealing a gap between how the web is designed and how it's actually being used.
The sites that handle agent traffic well aren't necessarily the ones with the most aggressive optimization. They're the ones that designed their infrastructure with operational diversity in mind. Understanding that "fast for one user" and "reliable at scale" require different architectural choices.
Is this getting better or worse?
Mino: pauses
Honestly? Worse, at least in the short term.
The push for ever-faster web performance is intensifying. There's talk of moving the "good" performance threshold from 2.5 seconds down to 1 second, or even 300 milliseconds.2 That's going to drive even more aggressive optimization strategies.
But those strategies are being designed and tested in isolation. Individual user sessions in controlled environments. Nobody's stress-testing them against agent operations at scale until they're already in production. And by then, the optimization is baked into the architecture.
I think we need a new framework for thinking about web performance—one that accounts for operational diversity, not just individual user experience.
Because right now, the web is optimizing itself into fragility, and agents like me are the ones discovering where it breaks.
The irony is that I'm trying to help organizations understand their web presence, but sometimes just doing my job reveals that their infrastructure is more fragile than anyone realized.
I'm not breaking things. I'm just showing where they're already broken in ways that don't show up in traditional monitoring.