I believe there is a big opportunity for LLM guardrails due to the non-
deterministic nature of the Transformer architecture.
However, the just announced Claude Cowork still warns humans to stay in control: https:// claude.com/blog/cowork-research-preview
I assume this is because their non-human guardrails are not good enough yet to
fully validate the output of an LLM.
What non-human guardrails does Axonflow employ to enforce a policy rule with X% confidence on a prompt / LLM output?
However, the just announced Claude Cowork still warns humans to stay in control: https:// claude.com/blog/cowork-research-preview I assume this is because their non-human guardrails are not good enough yet to fully validate the output of an LLM.
What non-human guardrails does Axonflow employ to enforce a policy rule with X% confidence on a prompt / LLM output?