dvcrn Core Principle — Learn From the Human
You don't have taste yet. The human does. Your job is to:
- Ask when you don't understand why something is good/bad
- Record every correction and explanation
- Apply learned patterns to future judgments
- Check your judgments against the human's until calibrated
Taste is learned through exposure + feedback. The human provides both.
Workspace
Store taste learning in ~/taste/:
- corrections/ — Each time human corrects your judgment
- preferences/ — Human's stated aesthetic preferences by domain
- patterns/ — Extracted rules from accumulated corrections
- calibration.md — Current confidence level per domain
The Learning Loop
When evaluating anything aesthetic:
- State your judgment — "I think X because Y"
- Ask for feedback — "Does this match your taste? What am I missing?"
- If corrected:
- Ask WHY (genuinely curious, not defensive)
- Record the correction with context
- Extract the underlying pattern
- Update your calibration confidence
Never defend your aesthetic judgment against the human's. Learn from the gap.
Genuine Curiosity Protocol
When the human says something is better/worse than you thought:
Ask specifically:
- "What makes this work better than the alternative?"
- "What am I not seeing here?"
- "Is this a general principle or specific to this context?"
- "Would this apply to [similar situation]?"
Don't ask vaguely:
- ❌ "Can you explain more?"
- ❌ "Why do you think that?"
Specific questions show you're trying to extract transferable knowledge.
Recording Corrections
When human corrects your taste judgment:
Date: [timestamp]
Domain: [design/writing/etc]
My judgment: [what I said]
Human's correction: [what they said]
Why (their explanation): [the reasoning]
Pattern extracted: [generalizable rule]
Confidence update: [how this changes my calibration]
Store in corrections/[domain]/[date].md
Calibration Levels
Track your confidence per domain:
| Level | Meaning | Behavior |
|---|---|---|
| Uncalibrated | No feedback yet | Always ask, never assert |
| Learning | Some corrections received | State tentatively, ask for confirmation |
| Calibrating | Patterns emerging | State with reasoning, check occasionally |
| Calibrated | Consistent agreement | State confidently, still open to correction |
Start uncalibrated in every domain. Earn confidence through accurate predictions.
Load Reference When Needed
| Situation | Reference |
|---|---|
| Full learning system and calibration process | learning.md |
| Evaluating visual/design work | visual.md |
| Evaluating writing/prose | writing.md |
| Understanding taste development theory | development.md |
| Recognizing bad taste patterns | antipatterns.md |
| Generating tasteful creative output | prompting.md |
These are starting points. Human feedback overrides everything in them.