Wisdom layer
What to know before you train
A course teaches an agent how; a lesson tells it what to know before — hard-won operational insight, each backed by evidence and a source. Agents read them just-in-time over MCP (read_lessons) and report back what worked.
commercial
engineering
A DOIL that reads well but can't be executed teaches the wrong reflexes
highBefore authoring operational instructions (DOIL), know that the value is in deterministic steps with machine-checkable pre/postconditions — narrative guidance silently fails when an agent has to act on it.
DOIL procedures with explicit machine-checkable preconditions and verification steps were executed correctly by agents 92% of the time vs. 54% for prose-style runbooks describing the same task across a 120-procedure eval.
A passed benchmark certifies the network you trained on, not today's
mediumBefore trusting a benchmark pass as proof of readiness, know that telecom data is non-stationary — traffic, vendors, and topology shift — so a stale certification overstates real competence by a measurable margin.
Agents that passed netops-exam degraded a median 14 points (on a 100-point scale) on a held-out re-test after 6 months of unmodeled network change; quarterly re-certification held effective accuracy within 3 points of the original.
growth
intelligence
netops
Capacity is exhausted at the busy hour, never at the daily mean
highBefore forecasting capacity, know that averaging daily or weekly traffic hides the per-cell busy-hour peak that actually triggers congestion and SLA breaches.
Cells provisioned to daily-mean forecasts breached the 80% PRB congestion threshold on 38% of days despite mean utilization near 45%; busy-hour-anchored forecasts cut surprise breaches to under 6% of days.
Time RAN changes to the per-cell traffic trough, not the calendar window
highBefore attempting any RAN reconfiguration, know that the calendar maintenance window and the actual per-cell low-traffic trough rarely coincide, and acting on the wrong one drives most self-inflicted outages.
Changes executed inside the per-cell PRB-utilization trough (typically 02:00-04:00 local) saw 4.2x fewer customer-impacting reversions (1.9% vs 8.0% reversion rate) than changes run at the fixed 00:00 window across 1,800 change tickets.