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AgentReady is an open specification laying out what a website should do so AI agents can find, read, and act on it. The research behind it, drawn from over 250,000 agent runs, suggests that sites agents can't read get answered from other people's pages instead.
- Sites agents couldn't read were 3.7 times as likely to produce answers missing the facts the user asked for, and agent-ready businesses were clearly recommended about 1.9 times as often.
- In the traced runs, 82% of final answers traced back to a page the agent fetched, and docs pages were the most common source at 47%.
- Blocking is the big failure: not-agent-ready sites blocked agents 2.1 times as often, and a WAF returning a 403 or challenge page stops agents regardless of robots.txt.
A panel of ThoughtWorks and industry practitioners walks through the operational failures of deploying agentic AI, from silent semantic errors to code review that can't keep pace with agent output. It also covers how to limit damage through agent identity, access controls, and continuous evals.
- Embedding drift in a financial compliance agent caused false positive and false negative spikes after an unannounced background model update, while every infrastructure health check stayed green.
- Coding agents produce code faster than humans can review line by line, so teams should automate style and syntax checks in CI/CD and reserve human review for architecture, business intent, and non-functional requirements.
- Treat each agent like a new engineering hire: give it its own non-human identity, separate read-only from write actions, version third-party MCP dependencies, and keep API secrets outside its runtime.