Record a real computer workflow as a trace: goal, starting state, each action (click, type, tool call), error, recovery, and done-check. No screen recording required — a structured action log with rationale. This is what computer-use agents (Claude Computer Use, Operator-class products, browser agents) cannot scrape from the public web.
This venue is a Wing in your Human architecture. Every exercise creates Rooms organized by Hall type. Data quality is tracked via Knowledge Graph triples.
Meet all milestones to unlock buyer engagement. Hybrid threshold — both content volume AND time consistency required.
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Labs can generate synthetic GUI traces. They cannot generate your recoveries when the page is wrong, the CSV is dirty, or the vendor portal hangs. That is the data they pay for.
6–10 hours initial, then 45 min/week · 4 steps · Each step builds your architecture
Action trace (JSON: goal, steps[], tools[], errors[], done_check)
When readiness is achieved, an AAAK-compressed summary of your data is generated for buyer evaluation — privacy-preserving, compact, and instantly readable by any AI system.
Computer-use and Claude agent products need human GUI traces with recoveries.
Computer-use and agent-trajectory collection for multiple labs.
Devin-class SWE agents need human IDE and browser workflows, not textbook algorithms.
Expert computer-use annotation for labs that reject click-farms.
Open the Data Builder to complete guided exercises. Each entry builds Rooms, Halls, and Knowledge Triples in your Human architecture — reaching buyer readiness in 30–60 days.