Core Determinants

Knowing what differentiates AI skill helps prioritize where to spend time — especially when transitioning from exploratory use to building impactful systems like SCRY.

Five Core Determinants

1. Semantic Precision

Can you tell what the model understands vs. what it mimics?
Debug meaning, reverse-engineer failures, and sculpt prompts to extract genuine comprehension rather than surface-level imitation.

2. Systemic Framing

Do you treat the model as one cog in a larger system?
Surround the AI with memory layers, ranking logic, context scaffolding, and prompt guardrails. It's about the holistic system, not just the model.

3. Data-Curating Judgment

Are you teaching or just uploading?
What you feed the model shapes its behavior. Curate examples, filter noise, and selectively expose key knowledge to guide learning.

4. Latency vs. Determinism Control

Can you shape consistent output from a stochastic system?
Use reranking, routing, constraints, and semantic filters to control the unpredictability of language models and make them dependable.

5. Moral & Strategic Vision

Does your AI have purpose?
Strategic intent and vision embed long-term values, align outputs to real-world goals, and guide the system with human purpose.

Condensed on 2025-07-19