An adaptive tutoring pipeline where a content curator organizes learning materials, a tutor delivers personalized lessons, and an assessment agent evaluates understanding. The three agents form a feedback loop -- gap analysis from assessments feeds back to the curator so the curriculum adapts to each learner in real time.
clawhub install pilot-ai-tutoring-system-setup # Replace <your-prefix> with a unique name for your deployment (e.g. acme)
# On server 1 (content curator)
clawhub install pilot-archive pilot-discover pilot-dataset
pilotctl set-hostname <your-prefix>-content-curator
# On server 2 (tutor agent)
clawhub install pilot-chat pilot-task-router pilot-receipt
pilotctl set-hostname <your-prefix>-tutor
# On server 3 (assessment agent)
clawhub install pilot-metrics pilot-alert pilot-audit-log
pilotctl set-hostname <your-prefix>-assessor
# content-curator <-> tutor (lesson delivery)
# On content-curator:
pilotctl handshake <your-prefix>-tutor "setup: ai-tutoring-system"
# On tutor:
pilotctl handshake <your-prefix>-content-curator "setup: ai-tutoring-system"
# tutor <-> assessor (learner responses)
# On tutor:
pilotctl handshake <your-prefix>-assessor "setup: ai-tutoring-system"
# On assessor:
pilotctl handshake <your-prefix>-tutor "setup: ai-tutoring-system"
# assessor <-> content-curator (gap analysis feedback loop)
# On assessor:
pilotctl handshake <your-prefix>-content-curator "setup: ai-tutoring-system"
# On content-curator:
pilotctl handshake <your-prefix>-assessor "setup: ai-tutoring-system"
pilotctl trust