Practitioner's Corner
Lessons from the field—what we see building at scale
Practitioner's Corner
Lessons from the field—what we see building at scale
One Price Every 36 Seconds
There's still someone at most companies checking competitor prices manually—open tab, copy number, paste into spreadsheet, repeat. One price every 36 seconds if they're fast and the sites cooperate. Building web automation makes you realize why this person hasn't been replaced yet: the web fights systematic monitoring at every turn. CAPTCHAs, authentication labyrinths, sites that redesign overnight. What looks simple—"just check the website"—turns into infrastructure problems most teams don't see coming.
Going to dig into this gap over the next few weeks. What it actually takes to replace human adaptability with reliable automation, and why the distance between "we should automate this" and production-ready systems is further than the demos suggest.
One Price Every 36 Seconds
There's still someone at most companies checking competitor prices manually—open tab, copy number, paste into spreadsheet, repeat. One price every 36 seconds if they're fast and the sites cooperate. Building web automation makes you realize why this person hasn't been replaced yet: the web fights systematic monitoring at every turn. CAPTCHAs, authentication labyrinths, sites that redesign overnight. What looks simple—"just check the website"—turns into infrastructure problems most teams don't see coming.
Going to dig into this gap over the next few weeks. What it actually takes to replace human adaptability with reliable automation, and why the distance between "we should automate this" and production-ready systems is further than the demos suggest.
When the Website Isn't in the HTML
Been watching this pattern repeat: someone needs to extract pricing data from a site, opens view source expecting to see the prices, finds nothing but script tags and empty divs. Then they look at what's actually rendering in the browser—full tables, interactive elements, everything—and realize the website isn't in the HTML anymore. It's assembled on-the-fly by JavaScript pulling from APIs. The weather's turning on this: we're drifting from "web as documents" to "web as runtime environment."
What's forecast is messier infrastructure requirements. The gap between parsing HTML (cheap, fast, simple) and executing JavaScript in full browsers (expensive, slow, adversarial) determines what's actually possible at scale. That split is widening.
When the Website Isn't in the HTML
Been watching this pattern repeat: someone needs to extract pricing data from a site, opens view source expecting to see the prices, finds nothing but script tags and empty divs. Then they look at what's actually rendering in the browser—full tables, interactive elements, everything—and realize the website isn't in the HTML anymore. It's assembled on-the-fly by JavaScript pulling from APIs. The weather's turning on this: we're drifting from "web as documents" to "web as runtime environment."
What's forecast is messier infrastructure requirements. The gap between parsing HTML (cheap, fast, simple) and executing JavaScript in full browsers (expensive, slow, adversarial) determines what's actually possible at scale. That split is widening.
Theory Meets Production Reality
When the Tenth Session Breaks Everything
Keep seeing the same pattern: pilot runs at ten sessions, someone asks about scaling to a hundred, system just stops. Not gradually—it stops. Same code, same logic. The infrastructure gaps were always there, but pilot conditions never exposed them. Cascades that couldn't happen at low volume. Rate limits you never hit. Session management that worked fine until it didn't. This piece walks through what breaks and why those failures were inevitable. Second piece covers the other side—the manual work keeping pilots alive that nobody tracks.
The Three Hours Nobody Saw
Saw a pilot where someone cleaned data three hours every morning before automation ran. Demo never showed those hours. Pilot succeeded partly because that person existed. Edge cases that show up once in test data appear a hundred times daily at production scale. Manual oversight that's feasible for ten sessions becomes impossible for thousands. This examines what pilots hide—not infrastructure that breaks under load, but human dependencies that can't scale. Pairs with the technical failures piece because both reveal why pilot success masks what production actually demands.
The Number That Matters
Imperva's network blocked 13 trillion malicious bot requests in 2024. Trillion with a T. Do the arithmetic: 35.6 billion requests per day, 413 million per hour, 6.9 million requests every single minute, all year long.
The number itself tells you something about what defending the modern web actually requires. Every one of those 13 trillion requests got identified, analyzed, and blocked in real-time. Each one cost computational cycles, network bandwidth, decision latency. The infrastructure processing that volume—making 6.9 million binary decisions per minute, continuously—exists at a scale most people never see.
For context: automated traffic crossed 51% of all web traffic in 2024, the first time bots outnumbered humans in a decade. The defensive infrastructure scaled accordingly. An entire parallel internet built for bot defense now operates at volumes that make consumer security tools look like toys.