docs: Field Trial Log v1.1 — Pilot phases + filming protocol

- Added four pilot phases (product research, not marketing):
  1. Collection — what can actually be detected?
  2. Analysis — are decisions understandable?
  3. Verification — was recommendation correct?
  4. Reflection — what needs to change?

- Measurement principle:
  - Not: Did AI find a crack?
  - But: Did this become a decision a real person could act on?

- Document 'non-decisions' — equally valuable as clear decisions
- Film workflow, not just infrastructure:
  - How you find area, choose mission, document
  - What feels unclear, when you become uncertain
  - When system saves time

- Observer mindset: document first, change model later
  - Build model from real workflows, not assumptions

Rationale: First 20-50 real missions teach more than months of modeling.
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Bernt
2026-07-02 12:21:20 +00:00
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@@ -100,6 +100,67 @@ Example: 65 of 72 executed = **90%**
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## Pilot Structure
**Four phases — product research, not marketing:**
| Phase | What You Do | What You Learn |
|-------|-------------|----------------|
| **1. Collection** | Film, photograph, create observations | What can actually be detected? |
| **2. Analysis** | Let pipeline create Findings and Decisions | Are decisions understandable and relevant? |
| **3. Verification** | Compare with reality on site | Was the recommendation correct? |
| **4. Reflection** | Document what worked and what didn't | What needs to change in the model? |
**Full chain captured:**
```
Reality → Observation → Evidence → Finding → Decision → Action → Outcome → Learning
```
## What to Measure
**Not:** Did AI find a crack?
**But:** Did this become a decision a real person could act on?
**Example:**
- AI finds 23 cracks
- LandveX says: "Inspect Road A12 within 30 days"
- **The second is the product.**
## Document "Non-Decisions"
Also valuable:
- "No action needed"
- "More data required"
- "Cannot recommend anything yet"
If the system always tries to give advice even when evidence is weak, you risk building a system that feels confident when it shouldn't.
## Film the Workflow
Since you are conducting the pilots, film more than just infrastructure. Also film:
- How you find an area
- Why you choose a mission
- How you document
- How long it takes
- What feels unclear
- When you become uncertain
- When the system saves time
This material becomes invaluable for product development, onboarding, training, and sales.
## Observer Mindset
**Principle:** If data contradicts the model, the model should change.
Use the same approach during pilots. If you notice:
- A step feels unnecessary
- A decision becomes unclear
- A recommendation cannot be acted on
**Document first, change model later.** Build the model from real workflows instead of assumptions.
**The first 2050 real missions will give you more valuable product knowledge than months of additional modeling.**
## Status
**ACTIVE — Awaiting first customer case**
@@ -111,3 +172,4 @@ Example: 65 of 72 executed = **90%**
| Version | Datum | Beskrivning |
|---------|-------|-------------|
| 1.0 | 2026-07-02 | Initial field trial log template |
| 1.1 | 2026-07-02 | Added pilot phases, measurement principles, filming protocol |