Supply Chain Security, in plain English.

Griffin AI vs Cohere Command for SecOps

Fine-Tuning Security LLMs vs Grounding: Which Wins

Fine-tuning teaches a model to be a security expert. Grounding lets a general model act like one by reading the right sources. The right answer is usually both, but the proportions matter.

Context Window As A Security Limit

The context window is usually marketed as a capability parameter. In a security setting, it behaves like a budget, a forgetting function, and an attack surface all at once.

Training Data Provenance: The Regulatory Wave

Regulators across three continents are converging on a single demand: show where your training data came from. The engineering implications are larger than most labs have admitted.

Griffin AI vs xAI Grok for Security

Specialised Security LLM vs Frontier Model: The Choice

Frontier models are general polymaths. Security-specific LLMs are narrow experts. Choosing between them is rarely about raw intelligence and almost always about cost, latency, and the shape of your data.

Frontier Model Non-Determinism As A Security Limit

Non-determinism is not a rough edge frontier labs will polish away. It is an architectural property of how transformer decoding works, and it places a hard ceiling on the kinds of security contracts you can sign.

Prompt Injection At Scale: 2026 Trend Review

Prompt injection has evolved from demonstration exploits into a category of attack that runs continuously against production AI systems. Here is what changed in 2026.

Anthropic's Responsible Scaling Policy v3: What Changed

RSP v3.0 takes effect February 24, 2026. It splits the AI R&D threshold, adds a CBRN-development tier, and formalizes Risk Reports.