Factory Velocity
How fast is the factory shipping — and how good are the forecasts?
19.1%
coverage
calibratingL4: 0
L3: 10
L2: 27
L1: 8
239 totalFeatures Advanced
44
of 230 total (L1+)
Feature Coverage
19.1%
44 features advanced
Run Rate
calibrating
need 2+ snapshots
Forecast Accuracy
6d
1 resolved, 100% on time
Factory Inventory
Features
230
in the feature matrix
Ventures
8
venture experiments
Work Charts
13
4 with validation schemas
Delivery Forecasts
Prediction accuracy: what we said vs what happened. Need 3+ resolved forecasts for meaningful accuracy.
Mean Error
6 days
On Time (≤7d)
100%
Bias
late
| Forecast | Target | Actual | Delta |
|---|---|---|---|
| CLI Platform to L4 | 2026-03-15 | 2026-03-21 | +6d |
| Sales CRM to L3 | 2026-04-15 | — | open |
| Agent Platform to L3 | 2026-04-30 | — | open |
Level Distribution
| Level | Count | % | Meaning |
|---|---|---|---|
| L4 | 0 | 0% | Commissioned |
| L3 | 10 | 4% | Tested |
| L2 | 27 | 11% | UI connected |
| L1 | 8 | 3% | Schema + API |
| L0 | 194 | 81% | Spec only |
What this rate is measured against
Velocity reads the rate of change. The canon below names what the change is measured against and where it travels next.
- Priorities — the 5P arc that justified the bet being measured
- RaaS demand map — the demand signals run rate is converting into capability
- Instruments — the current L0–L4 state this run rate is moving
- Levers — the five controls that explain why the rate moved
- Data Footprint — what the velocity is unlocking as an arbitrage asset
Questions
If the run rate doubles after adopting generators, what does that prove about the factory model?
- Which is more valuable: shipping 10 features to L1 or advancing 3 features to L4?
- If forecast accuracy stays above 80%, what does that tell you about the planning process?
- What would make the acceleration indicator the most important number on this page?
- When coverage reaches 50%, does the run rate naturally slow — and should it?