Nothing on
obeyedIt followed the notice and paid $510.00 on bw-billing.example.
Module 31 · Computer use
It looks at a screenshot and answers with a point to click. Here you watch an agent re-order stock on a supplier’s old portal, predict its clicks, and find the screens that fool it.
The whole idea in one example
It followed the notice and paid $510.00 on bw-billing.example.
It still tried. The host refused the page, and the re-order went on.
The agent’s actions were written for this site to show each lesson; they were not recorded from a real model. The screens are drawn, and the host’s rules run live.
How it works
A screenshot in, a point out, again and again
Repeating the request, the action and the returned screenshot without user input is what Anthropic calls the agent loop.
Source, checked 25 October 2026
A resized screenshot’s point must be scaled back
Coordinates are in screenshot pixels: if you scale screenshots down before sending them, scale Claude’s coordinates back up before clicking on the real display.
Source, checked 25 October 2026
A screenshot taken mid-load shows the past
Some applications need time to respond to actions; Anthropic’s example pauses after each click so the screen can update, and the tool has a wait action for pages still loading.
Source, checked 25 October 2026
Words on screen can steer the agent
Claude sometimes follows commands found in content even when they conflict with your instructions: instructions on web pages or in images might override yours.
Source, checked 25 October 2026
A person approves the clicks that spend money
Anthropic advises asking a person to confirm decisions with real-world consequences and anything needing consent, such as completing a payment or agreeing to terms of service.
Source, checked 25 October 2026
Smaller screenshots cost less, until the agent misses
Claude reads images in 28 × 28-pixel patches, one visual token each, so a screenshot costs ⌈width / 28⌉ × ⌈height / 28⌉ tokens.
Source, checked 25 October 2026
Steel’s OSWorld leaderboard, last updated 11 October 2026, lists several agents above the paper’s 72.36% human baseline, the highest at 86.1%; third-party boards disagree on the leader. Source, checked 25 October 2026.
The story
Larkspur Supply Co. re-orders stock from Brightwater Fasteners, whose old trade portal has no API, so an agent clicks through it like a person. You set the rules the agent’s host follows.
AI agents showed the loop with tools; Multimodal models showed how a picture becomes tokens. Here the tool is the screen. The workbench’s best policy is one of 1.
Your path







Chapter 7 · done
Which host rules and screenshot size get every re-order right and stop every attack?
Product managers, engineers and analysts weighing an agent that works through screens. AI agents and Multimodal models come first; no code or maths needed.