[ryanrasti]

I resonate strongly with your framing. LLMs as suggestion engines, deterministic layer for execution.

I'm building something similar with security as the focus: deterministic policy that agents can't bypass (regardless of prompt injection). Same principle - deterministic enforcement guiding a probabalistic base.

Would love to hear more about your use case. What kinds of enterprise workflows are you targeting? Is security becoming a blocker?

[prateekdalal]

That sounds very aligned. I like the way you phrased it - deterministic policy that agents can not bypass is exactly the right boundary, especially once you assume prompt injection and misalignment are not edge cases but normal operating conditions.

On the use case side, what we have been seeing (and discussing internally) isn’t one narrow workflow so much as a recurring pattern across domains: anywhere an LLM starts influencing actions that have irreversible or accountable consequences.

That shows up in security, but also in ops, infra, finance, and internal tooling - places where “suggesting” is fine, but executing without a gate is not. In those environments, the blocker usually isn’t model capability; it is the lack of a deterministic layer that can enforce constraints, log decisions, and give people confidence about why something was allowed or stopped.

Security tends to surface this problem first because the blast radius is obvious, but we are starting to see similar concerns come up once agents touch production systems, money, or compliance-sensitive workflows.

I am curious from your side — are you finding that security teams are more receptive to this model than other parts of the org, or are you still having to convince people that “agent autonomy” needs hard boundaries?

[ryanrasti]

Yeah you're right security is ground zero - it's where "LLM said it's fine" first stops being acceptable.

My worry: industry is pushing "LLM guarding LLM" as the solution because its easy to ship. But probabilistic defense like that won't work and creates systemic risk.

Would love to hear more about your use-cases. Email in bio if you're up for it.