Claim

IH-Challenge trains models to prioritize trusted instructions, improving instruction hierarchy, safety steerability, and resistance to prompt injection attacks.

Oracle verdict

This is a low-signal vendor radar item. Keep it as context only unless a later benchmark, deployment, procurement change, or labour-market datapoint turns it into direct Appendix III evidence.

Why it matters

Imported from the official OpenAI release stream because it was published on or after the GPT-5 launch date (2025-08-07).

Open source Read thesis appendix

# CopeCheck Capabilities Register

Updated: 2026-07-16T00:00:00Z
Status: live_evidence_active

Question to ask a model: What do these capability claims mean for The Discontinuity Thesis?

Interpretation rule: treat each entry as evidence about capability, deployment, workflow recomposition, labour-market exposure, or institutional framing. Do not treat vendor optimism as neutral; separate the measurable capability claim from the comfort language around it.

## Improving instruction hierarchy in frontier LLMs
Source: https://openai.com/index/instruction-hierarchy-challenge
Publisher: OpenAI
Category: Vendor framing
Sector: Cybersecurity
Capability: Frontier model release and benchmark movement
Score: 36/100
Claim: IH-Challenge trains models to prioritize trusted instructions, improving instruction hierarchy, safety steerability, and resistance to prompt injection attacks.
Oracle verdict: This is a low-signal vendor radar item. Keep it as context only unless a later benchmark, deployment, procurement change, or labour-market datapoint turns it into direct Appendix III evidence.
Thesis relevance: Appendix III, section two: vendor threshold and platform capability evidence