Supply Chain Security, in plain English.

Griffin AI vs Cohere Command for SecOps

The Disproof Step: Griffin AI vs Mythos

Most AI bug hunters skip the hardest step: trying to kill their own findings. Here is why Griffin AI's disproof pass is the single biggest lever on false-positive rate.

Model Tiering Strategy: Griffin AI vs Mythos

Opus for reasoning, Sonnet for drafting, Haiku for scale. We break down when each tier earns its keep and why single-model architectures cannot compete.

AI Safety Eval Datasets as Supply Chain

The datasets you use to evaluate model safety are themselves a supply chain, and almost nobody is treating them that way. A senior engineer's audit of how eval corpora get poisoned, contaminated, and silently drifted.

Enterprise AI Agent Deployment Lessons, 2026

Lessons learned from a year of enterprise AI agent deployments: what worked, what failed, and what we would do differently starting now.

Griffin AI vs Mistral Large for Remediation

Mistral Large is a strong reasoning model, but remediation is more than generating a diff. We look at what Griffin AI adds for production fix workflows.

SSO & SCIM: Griffin AI vs Mythos

Enterprise identity is not a paywall. It is the substrate on which every other security control depends, and it is where Mythos-class vendors quietly fall behind.

The MCP Threat Model: What Actually Matters in 2026

Most MCP threat models confuse protocol risk with deployment risk. Here is what the real attack surface looks like after a year of production incidents.

SWE-Bench With Security Extensions: Field Review

SWE-bench became the default benchmark for measuring AI coding agents, but the security extensions that were bolted on afterwards deserve their own scrutiny. A field review of what they measure, where they break, and whether you should trust the numbers.