
AI Agents
New review paper argues code is how AI agents think and act, not just what they produce
Jonathan KemperThe Decoder
AI Summary
A review paper argues that the software layer (tools, memory, testing, permissions) around language models, not the models themselves, is the key bottleneck for autonomous AI agents. DeepSeek is building a dedicated team to implement this model-plus-harness formula for creating functional AI agents.
This article was originally published on The Decoder. Read the full story at the source.
Read Full Article at The DecoderRelated Articles

Uber’s product chief on hotels, robotaxis, and why the company doesn’t want to be “everything for everyone”
TechCrunch AI

AI agents create virtual playgrounds to help robots get crucial training data
MIT News AI

Building a VideoAgent-Style Multi-Agent System: Intent Parsing, Graph Planning, and Tool Routing for Video Editing Tasks
MarkTechPost

Chinese Tech Vendors Converge on Humanoid Robotics and Embodied AI
AI Business