AI Safety Research
That Ships.
Dynamic Frontier publishes AI safety and alignment research through the Open Science Framework. Every failure mode we study becomes a check that Safe runs automatically. Our customers benefit from research they never have to read.
Research Areas
Our research is grounded in real production failures, not synthetic benchmarks. Every audit generates new patterns that improve Safe's detection capabilities.
01. Behavioral Failure Taxonomy
Categorizing the ways AI systems silently fail in production — from missed escalations to hallucinated facts.
02. Misalignment Detection
Methods for identifying when AI behavior drifts from stated instructions, constraints, and business rules.
03. Prompt Safety Patterns
Studying which prompt structures prevent failures and which invite them — building a library of proven guardrails.
04. Adversarial Testing
Developing systematic approaches to stress-test AI systems before failures reach real users.
Coming Soon | David Max
A Taxonomy of Common AI Behavioral Failures in Production Systems
Categorizing the silent failure modes observed across telehealth, automotive, and customer service AI deployments.
Coming Soon | David Max
The Ralph Loop: A Methodology for AI Safety Engineering
A practical framework for reading, mapping, building, testing, and hardening AI systems in regulated environments.
Coming Soon | David Max
Prompt Safety Patterns for Production AI
A pattern library of prompt structures that prevent common failure modes in customer-facing AI systems.