Day 1 — Teaching an AI to Ride With Me
From 4/10 to 9/10 in 24 hours.
Context
Yesterday was Day 0.
First attempts were rough.
Jarring cuts. Wrong orientation. No corner feel.
AI didn’t understand motion continuity yet.
Day 0 Clip
File: day1_edit.mp4 (143MB, 15s)
Rating: 4/10
Video hosting in progress - YouTube embed will be added
What went wrong:
- Static starts
- Wrong energy
- No corner feel
- Doesn’t feel like riding
No ego defense. This was bad.
What Changed
Constraints added:
- Rotation detection fixed
- No static shots
- Bike visible at all times
- Cuts occur after lean stabilizes
- Velocity continuity across transitions
- 15-second structure respected
Day 1 Clip
File: coast_brake_edit_15s.mp4 (77MB, 15s)
Rating: 9/10
Video hosting in progress - YouTube embed will be added
Better. Corners feel coherent. Velocity matches. This feels like riding.
Training Notes
The system:
- Rating scale: 1–10
- Under 7 = diagnose
- 7+ = store pattern
- No verbose analysis
- Execution > storytelling
Progression:
- Initial: 4/10 (upside down, no motion)
- Refined: 6/10 (speed jumps)
- Matched: 7/10 (cuts during corrections)
- Coast brake: 9/10 (smooth flow maintained)
What I’m teaching it:
- Directional coherence
- Lean stabilization timing
- Velocity matching
- Motion continuity
Why This Matters
This isn’t about AI replacing editors.
This is about:
- AI as apprenticeship — It learns my style through iteration
- Clear constraint definition — I specify rules once
- Autonomous execution — System applies consistently
- Compounding learning — Gets better daily
Time saved per edit:
- Manual edit: 45-90 minutes
- With trained system: 2 minutes (watch + rate)
That’s the leverage.
What’s Next
Continue daily training:
- Drop footage
- Rate output
- Store learning
- Iterate
Goal: Consistent 8+ ratings with minimal prompting.
Eventually: Ride → upload → wake up → usable cut waiting.
That’s when this becomes a real force multiplier.
This is Day 1 of documenting the training process. More updates as the system improves.