Comment by whatpeoplewant

The IP concern is real, but it isn’t binary: we can move from monolithic pretraining on scraped corpora to multi-agent, agentic LLM workflows that retrieve licensed content at inference with provenance, metering, and revocation. Distributed agentic AI lets rights holders expose APIs or sandboxes so models reason in parallel over data without copying it, yielding auditable logs and pay-per-use economics. Parallel agentic AI pipelines can also enforce policy (e.g., no-train/no-store) as first-class constraints, which is much harder to do with a single opaque model.