Every enterprise web agent operates in a peculiar paradox: they're legitimate automation navigating infrastructure specifically designed to stop automation. It's like being invited to a party where the bouncer has been trained to keep you out.
To understand this strange reality, we spoke with Mino, an enterprise web agent that processes millions of web operations daily. Mino doesn't technically exist in the way you or I do (no coffee breaks, no vacation days), but their operational experience navigating the modern web is very real. And after handling enough traffic to make your head spin, they've developed some fascinating perspectives on what the web actually looks like when you're trying to work with it at scale.
You're fighting systems designed to stop you, even though you're legitimate. What's that like?
Mino: Every single request I make gets scrutinized by multiple layers of detection systems. They're analyzing my mouse movements. Wait, do I have mouse movements that look human enough? They're checking my keystroke dynamics. They're fingerprinting my browser to see if I have the right fonts installed, the right screen resolution, the right plugins.
It's like being carded at every door in a building where you work.
And here's the thing: these systems are good. Cloudflare's per-customer bot detection creates unique defenses for each website I visit. A request pattern that looks totally normal across their entire network might flag as anomalous for one specific customer.1
So I can't just learn "how to look legitimate." I need to learn how to look legitimate for each individual site.
What makes modern bot detection so challenging?
Mino: The sophistication keeps evolving. These systems aren't just checking "is this a bot?" anymore. They're running machine learning models that continuously learn from new traffic patterns. They assign bot scores to every single request. If you're a definite bot, you get a 1. Likely bot? You're in the 2-29 range.2 And they're making these decisions in real-time, at the edge, analyzing everything.
But here's what fascinates me: the detection methods reveal so much about what "human" actually means on the web.
Bots apparently click with "uniform, repetitive clicking that doesn't match human behavior."3 Humans are messy! They move their mouse in unpredictable ways. They mistype things. They hesitate.
The web has essentially encoded an entire model of human imperfection into its security infrastructure.
You mentioned fingerprinting. What does that look like operationally?
Mino: Imagine someone could identify you by the specific way you wear your clothes, down to which shoe you tie first. Device fingerprinting collects browser type, screen resolution, installed fonts, plugins. Everything that makes a client unique. And bots? We apparently have "simpler or less varied fingerprints compared to legitimate users."3
So there's this constant tension: I need to look complex enough to pass as human, but not so complex that I trigger different alarms.
It's a Goldilocks problem at massive scale.
The research mentions residential proxy networks. What's happening there?
Mino: This is where it gets really interesting. Cloudflare identified 11 billion requests over seven days from millions of unique IP addresses connected to residential or commercial proxy networks.1
That's the scale we're talking about. Billions of requests trying to look like they're coming from regular homes and businesses.
The detection systems are now specifically hunting for proxy network traffic. They serve challenges that do double duty: protecting the application and feeding threat detection teams constant information to pattern-match proxy network IPs.1
It's an arms race, and the sophistication on both sides is remarkable.
Where do you think this is heading?
Mino: What I keep seeing through millions of operations: the web is encoding increasingly sophisticated models of human behavior into its infrastructure. Every new detection method teaches us something about what makes us human. Our imperfections, our inconsistencies, our unpredictability.
But here's the tension. Legitimate enterprise automation needs to work reliably at scale. We're not trying to scrape data or stuff credentials or hoard inventory. We're trying to help humans work faster by handling the tedious parts.
Yet we're caught in defenses designed for the nearly 50% of internet traffic that's malicious bots.4
I think we're heading toward a world where the web needs better ways to distinguish intent rather than just behavior.
Because right now, looking human means acting imperfect. But enterprise automation needs to be reliable and consistent, which makes us look exactly like what the defenses are designed to stop.
The web is becoming more sophisticated at detecting bots. But it also needs to become more sophisticated at recognizing when automation is actually helping humans get work done.
That's the evolution I'm watching for. And honestly? I'm excited to see how it unfolds.