Workflow Studio
Watch a pipeline halt exactly where the model's output lied.
The 'the lie stops here' checkpoint turns silent schema drift — normally a production incident discovered days later — into a visible, immediate, named-field halt the learner watches happen.
What goes in, what comes out
Learner builds a multi-step pipeline on a node canvas (extract to structured JSON, call a function/tool, transform, checkpoint, act), where every node is a literal schema contract, not just a prompt. Feeding the pipeline deliberately messy or adversarial input triggers a visible halt at the exact node and field that failed validation, and a human-checkpoint node forces manual sign-off before any mutating step fires.
A raw task (e.g., triage these support tickets), sample messy input data, and the target schema for each pipeline stage.
A running pipeline visualization, a validation-failure halt screen naming the exact field and value that broke contract, and a cross-model comparison of schema-drift rate.
Node graph composition, JSON Schema per node, model per node (to compare schema-honoring behavior across families), and which steps require human approval.
In-module lab for AIE-204/205 (COULD tier); reused across Marketing/Design/Founders specializations as the automation-with-a-human-checkpoint exercise.
Go deeper, elsewhere
Hand-picked public explainers and open tools that complement this one — always optional, never required, never graded.
Concepts click when you open the machinery.
Three labs are already live and free — the same hands-on style this playground brings to its module.