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Current VLMs show alarming performance drops in long-context scenarios, revealing that they may be overfitting to benchmark artifacts rather than demonstrating true understanding.
Forget the fancy tool-augmented agents: a simple coding agent with terminal access can often beat them at real-world enterprise automation tasks.
Current LLM agents are nowhere near ready for autonomous enterprise deployment, with even the best models failing at strategic reasoning and often attempting infeasible tasks with potentially harmful consequences.
Frontier-level multimodal reasoning is now within reach for organizations with limited infrastructure, thanks to a 15B parameter model that rivals much larger models through clever training design, not brute force scaling.
