MJos Predictive Model | First manifestation of the Bangel Language
New project sequence ยท proposed bindings
Team members and roles, time-bounded shifts, team messages, courses, lessons, assignments and lesson completion records. AddShift validates start/end and rejects overlaps for the employee.
BarTide staff scheduling and training / Brown MJos Predictive Model | First manifestation of the Bangel Language MJ Physics Engineering | Owned and operated by Michael Bangel | Clearwater, Florida OBSERVATIONAL LIFECYCLE Purpose: Team members and roles, time-bounded shifts, team messages, courses, lessons, assignments and lesson completion records. AddShift validates start/end and rejects overlaps for the employee. R / R0 Retain the proposed request and anticipated context; a forecast has not occurred. R1 Record the unresolved or partially supported representation under its named source profile. Older unidentified-transition wording and later interpretation-state wording must not be merged silently. N1 AND REPRESENTATION The staff member is active and the acting user may manage the tenant. - TeamShift: member + start + end + label - TrainingProgress: member + lesson + completion + time - Role: owner | manager | bartender | server | kitchen | driver REVIEW TO OUTPUT Validate shift interval/non-overlap or course version/assignment; preserve source identity. Save an explicit schedule or learning record; incomplete evidence does not certify proficiency. RECOVERY Return to the first named missing prerequisite. A changed input or new evidence permits another bounded pass. Repeated state or no progress stops recovery with the existing evidence intact. r9 remains the N5-N7 interpretation region where that separate profile applies. EVIDENCE LIMITS - Training checkmarks are stored completion state, not independent proof of skill. - Shift management exists; no optimizer or external calendar synchronization established.