Experiments in Adaptive Design
Theory held in tension, until it clicks.
What is This Space?
Prototypes are not finished.
They are attempts — expressions of living ideas under construction.
This page collects experimental implementations of:
- DAM-inspired systems (adaptive, layered, recursive)
- DAF-informed flows (alignment-sensitive, rhythm-aware, intuitive)
- Hybrid bridges between self and structure
To prototype is to model before you’re sure — and learn by watching it breathe.
Featured Prototypes
1. Time-Density Simulator
A visual tool for exploring how internal time (τᵢ
) shifts under stress, energy, or entropy.
- Input: entropy level, goal deviation, external pressure
- Output: time contraction/expansion curves, system delays, sync/desync patterns
- Future: add “subjective coherence” sliders to integrate DAF
Built in: Python + matplotlib → [View Notebook]
Use for: modeling temporal drift in learning systems, pacing rituals, or decision fatigue
2. Error Reflection Loop (DAFxDAM)
A journaling prototype that uses modeling logic to guide adaptive self-reflection.
- Input: subjective friction points
- Logic: maps to DAM-like “error vectors” → generates prompts for adaptation or rest
- Output: alignment report + suggested micro-shift
- Weekly rhythm: “What changed you? Where did you resist?”
Built in: JavaScript + minimal UI → [Try It Live]
Use for: reflective teams, coaching systems, self-guided flow tuning
3. Meta-Goal Drift Engine
A system that evolves its own priorities over time, based on internal feedback loops.
- Starts with fixed goal vector
H(t)
- Measures environmental mismatch and coherence over time
- Mutates goals subtly through adaptive rules (meta-evolution layer)
- Optional: introduce “observer intention” to steer direction
Built in: networkx + Python logic + entropy tracking
Use for: modeling institutional drift, creative process navigation, personal strategy evolution
Prototype Design Values
Every Autorite prototype follows three principles:
- Clarity of Feedback
→ The system should show when it’s adapting — not hide it - Perceptual Coherence
→ The logic should “feel right,” not just compute correctly - Meta-awareness
→ The user and the model both track how they’re changing
Prototypes are conversation partners, not tools.
Future Experiments
- Alignment mirror: real-time coherence feedback
- DAF-based writing companion
- Entropy-aware learning scheduler
- Systemic ritual planner
- Observer-in-the-loop simulation game
Related Labs
[Design by intuition → /interface/tactile-thinking]
[Observe system-feeling → /interface/systems-in-skin]
[Test feedback principles → /organism/simulations]
[Prototype your own → /atelier/submit]