Foundations
Foundations
When Agents Can't Find What's Right in Front of Them
A web scraper pulls product prices from a retail site every morning. One day it returns empty results. The prices are still there, displayed correctly on the page—customers see them, competitors see them. But the agent can't find them. Teams spend days checking pipelines and validating formats. Something broke, something most debugging approaches miss entirely.
When Agents Can't Find What's Right in Front of Them
A web scraper pulls product prices from a retail site every morning. One day it returns empty results. The prices are still there, displayed correctly on the page—customers see them, competitors see them. But the agent can't find them. Teams spend days checking pipelines and validating formats. Something broke, something most debugging approaches miss entirely.
Tools & Techniques
Headless Browsers at Scale: Where Speed Determines Economics
The infrastructure lead switches 10,000 daily hotel price checks from headful to headless browsers. Monthly bill: $4,500 to $1,500. Tasks complete 2-15x faster. Same server handles three times the concurrent sessions. For teams running automation at volume, headless execution determines how many servers you need and what they cost. Then anti-bot systems evolve to catch the missing rendering pipeline, the absent plugins, the suspicious timing patterns. Engineering around detection becomes its own cost, one that sometimes exceeds the infrastructure savings.
When Headful Browsers Justify Their Resource Overhead
The pricing monitoring system ran cleanly for three months—15,000 hotel properties checked daily, data flowing into automated pricing decisions. Then Booking.com updated their anti-bot system. Success rate dropped from 94% to 31% within 48 hours. Missing pricing data meant stale dashboards. Stale dashboards meant the system underpriced 400 properties based on weekend rates that were four days old. The revenue team calculated the loss. The cost of being wrong exceeded the cost of running more expensive infrastructure by a factor of eight.
Pattern Recognition
Three major vendors launched agent management platforms in February 2026. OpenAI released Frontier on February 5. Salesforce expanded Agentforce throughout January and February. AWS grew Bedrock AgentCore. Gartner called these platforms "the most valuable real estate in AI."
Only 11% of organizations have agents in production, according to Deloitte. Gartner forecasts over 40% of agentic AI projects will be canceled by end of 2027. Vendors are racing to own infrastructure before production use cases prove out at scale, betting that controlling the platform matters more than solving deployment challenges first.
