Denis Ermakov

Hey, thanks for the awesome feedback! You hit the nail right on the head regarding the lack of real-time grounding.

I love the idea of feeding the community blocklist back into alignment steps like RLHF or DPO. Attacking the root cause during fine-tuning is definitely the holy grail approach. The main hurdle there is just how fast registries change, meaning that training dataset would need to be incredibly dynamic.

Until model weights can be dynamically grounded, this scanner is absolutely a pragmatic guardrail for the pipeline. But combining runtime scanning with proactive model alignment is 100% where the industry needs to go.

Appreciate you diving deep into this! Do you think an RLHF penalty might make the model overly timid about suggesting legitimate, niche libraries, or could we scope it tightly enough?