Description
This week, agentic capabilities took a leap forward in both proprietary and open ecosystems. Claude Opus 4.5 has redefined the ceiling for coding agents, hitting a record 80.9% on SWE-Bench Verified and dominating complex reasoning tasks with a 91.5% score on agentic evals. In parallel, DeepSeekMath-V2 proved that open-source models can rival giants, using a novel generator-verifier loop to achieve IMO Gold Medal status—demonstrating that self-verification is key to reliable reasoning. The application layer is expanding too: Flux is bringing agentic workflows to hardware design, automating schematics and component sourcing in a browser-based CAD tool dubbed the 'Devin for Hardware.' Driving these breakthroughs is a shift in training philosophy, with engineers increasingly betting on Reinforcement Learning (RL) pipelines over simple fine-tuning to handle the complex, multi-step planning required for autonomous agents.