Take a real job that took you hours or days. Break it into ordered steps an agent could attempt, with inputs, tools, checkpoints, and a human gate before anything irreversible. Cognition, enterprise ops agents, and computer-use stacks need this more than they need another tutorial.
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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Agents fail at long horizon because the plan is missing, not because the model cannot click. Your plan — with the checkpoints you actually used — is the product.
8–14 hours per module · 4 steps · Each step builds your architecture
Task graphs (JSON: goal, steps[], tools[], checkpoints[], human_gates[])
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.
Devin-class agents need human task graphs, not GitHub READMEs.
Long-horizon agent products need human plans with gates.
AIP workflows are long-horizon operations with human gates.
Collects long-horizon agent traces and plans for labs.
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.