What to measure. Traditional manufacturing metrics vs protocol-era metrics.
| Category | What It Measures | Traditional | Protocol-Era |
|---|
| Task | Execution quality | Cycle time, defect rate | Proof of work, outcome verification |
| Financial | Return on investment | Robot ROI, utilization | Token yields, task revenue |
| Network | Fleet scale | Fleet size | Device count, geographic spread |
| Community | Participation | N/A | Operator count, governance |
Task Metrics
Execution
| Metric | Traditional | DePIN Protocol | Why Better |
|---|
| Task success rate | QA sampling | On-chain verification | Every task verified |
| Completion time | Stopwatch | Timestamped proof | Immutable record |
| Quality score | Periodic audit | Continuous attestation | Real-time feedback |
Learning Rate
| Metric | What It Shows | Target |
|---|
| Task accuracy improvement | Fleet learning speed | Improving quarter over quarter |
| New task categories | Capability expansion | Growing task diversity |
| Edge case resolution | Handling novel situations | Decreasing failure rate |
Financial Metrics
Traditional Robotics
| Metric | Benchmark | What It Shows |
|---|
| Robot ROI | 18-24 months payback | Investment recovery |
| Utilization rate | 60-80% | Asset efficiency |
| Cost per task | Industry-specific | Unit economics |
| Maintenance cost | 5-10% of capital/year | Ongoing expense |
DePIN Robotics
| Metric | Benchmark | What It Shows |
|---|
| Token yield | Variable | Operator return on deployment |
| Task revenue | Per-outcome | Real economic value |
| Burn/issuance | >1 = healthy | Token sustainability |
| Operator ROI | Months to payback | Hardware economics |
| Traditional | Protocol-Era | Shift |
|---|
| Fleet leasing revenue | Per-outcome pricing | Value to users |
| Corporate maintenance | Community maintenance | Distributed cost |
| Proprietary data value | Shared training data | Network compounds |
| Single-company fleet | Community fleet | Distributed ownership |
Opportunity Assessment
Scoring Dimensions
| Dimension | Weight | Robotics Score | Evidence |
|---|
| Market Attractiveness | 20% | 8.0 | Humanoid $38B by 2035, industrial $75B |
| Technology Disruption | 20% | 7.5 | Tesla Optimus, Figure, capabilities accelerating |
| VVFL Alignment | 25% | 7.0 | Loop works — DePIN + AI + task data |
| Competitive Position | 20% | 6.5 | Early stage, token models unproven |
| Timing Risk | 15% | 7.0 | 2025-2027 deployment wave |
Aggregate: 7.2/10 — Strong Conviction
Opportunity Matrix
| Opportunity | Score | Timing | Key Risk |
|---|
| Agricultural robots | 8.0 | Now | Seasonal demand |
| Delivery/logistics | 7.5 | Now | Regulatory, urban complexity |
| Humanoid labor | 7.0 | 2-3 years | Technical maturity |
| Drone services | 7.5 | Now | Airspace regulation |
| Industrial automation | 6.5 | Now | Incumbent entrenchment |
Watch Signals
| Signal | Bullish | Bearish |
|---|
| Tesla Optimus | Mass production begins | Delays continue |
| DePIN robotics | Token-incentivized fleets launch | No traction |
| Task automation | New categories automated quarterly | Plateaus |
| Cost curves | Unit cost drops 30%+ annually | Flat |
| Regulation | Autonomous operation permitted | Restricted |
Value Chain Disruption
| Stage | Traditional | DePIN | Margin Shift |
|---|
| Manufacturing | Centralized OEM ($50-250K/unit) | Distributed assembly | → Component providers |
| Deployment | Fleet leasing | Community ownership | → Operators |
| Operations | Corporate opex | Protocol automation | → Token holders |
| Data | Proprietary silos | Shared learning | → Network |
| Tasks | Per-robot billing | Per-outcome pricing | → Users |
The key shift: Value moves from robot ownership (capital-intensive) to task completion (outcome-intensive). Whoever owns the task orchestration layer captures the margin.
| Principle | What to Measure |
|---|
| Mobility adds dimensions | Geographic coverage, task diversity |
| Agency creates actors | Revenue per task, outcome success rate |
| Task data compounds | Model improvement rate, fleet learning speed |
| Coordination scales | Multi-robot throughput, swarm task completion |
| Physical presence matters | Fleet size, deployment rate, operator count |
Context