---
id: "question-ontology-discovery"
type: "open-question"
source_timestamps: ["00:13:40", "00:14:30"]
tags: ["systems-architecture", "machine-learning"]
related: ["concept-structured-ontology", "framework-world-model-principles"]
resolutionPath: "Developing hybrid architectures that enforce strict schemas for core business metrics while running parallel, exploratory agents that suggest new ontological relationships for human review."
sources: ["s15-block-layoffs"]
sourceVaultSlug: "s15-block-layoffs"
originDay: 15
---
# Balancing Strict Schema with Emergent Discovery

## The Question

How can a company impose enough structure to ensure factual accuracy, while simultaneously allowing the model enough exploratory freedom to discover and propose novel relationships that the business hasn't formally recognized yet?

## The Tension

The speaker identifies a critical tension between two architectures:

- [[concept-structured-ontology]] (e.g., [[entity-palantir-d15]]) is safe because it prevents hallucinations, but it is **blind to emergent patterns** outside its schema — see [[claim-ontology-blindspot]].
- [[concept-semantic-retrieval]] can find unexpected connections but **hallucinates importance** — see [[claim-semantic-retrieval-flaw]].

The unresolved question is how to architect a system that does both.

## Resolution Path

Developing hybrid architectures that:

- Enforce strict schemas for core business metrics where logic is absolute
- Run parallel, exploratory agents that suggest new ontological relationships for human review
- Surface candidate ontological extensions through the [[concept-interpretive-boundary]] explicitly as 'unverified hypotheses'

The canonical principle that supports this resolution is the quote [[quote-structure-earned]] — *structure needs to be earned, not imposed.*

## Related

- [[claim-ontology-blindspot]]
- [[claim-semantic-retrieval-flaw]]
- [[framework-world-model-principles]]