Hey, great read as always. I completely resonate with your observation about the 'show me, don't tell me' phase. Rigorous evaluation and demonstrating real-world utility are realy paramount for the field's genuine progress and trustworthiness. It's exactly the direction we need.
Excellent curation on the evaluation frameworks shift. The timing of Linux Foundation's Agentic AI Foundation is particualrly interesting because it comes right when everyone's releasing their coding agent and nobody has a clue how to actually benchmark them properly. I've noticed the same tension in enterprise deployments where teams are dunno if they're measuring productivity gains or just task completion rates. The NeuroDiscoveryBench piece showing 35% vs 6-8% accuracy difference reveals the gap between data analysis and memorization.
Hey, great read as always. I completely resonate with your observation about the 'show me, don't tell me' phase. Rigorous evaluation and demonstrating real-world utility are realy paramount for the field's genuine progress and trustworthiness. It's exactly the direction we need.
thanks for feedback! truly means a lot! ♥️
Excellent curation on the evaluation frameworks shift. The timing of Linux Foundation's Agentic AI Foundation is particualrly interesting because it comes right when everyone's releasing their coding agent and nobody has a clue how to actually benchmark them properly. I've noticed the same tension in enterprise deployments where teams are dunno if they're measuring productivity gains or just task completion rates. The NeuroDiscoveryBench piece showing 35% vs 6-8% accuracy difference reveals the gap between data analysis and memorization.