What our over-dependence on external consulting teaches us about delegating our minds to machines The post The Big Con of Agentic AI appeared first on Towards Data Science .
By Chinmay Kakatkar
The article discusses how agentic AI is reshaping the analytics stack by taking over more execution tasks. It raises the question of which responsibilities should remain with human analysts versus AI agents and explores the importance of this distinction. The piece highlights the evolving role of AI in analytics and the need to define clear boundaries between human and machine work.
By Rashi Desai
Map AI value, design workflows, redefine talent, upgrade the executive team, and measure the business impact. The post Redesign Work Before You Add More AI Agents appeared first on Towards Data Science .
By Weiwei Hu
The article discusses how coding agents are transforming AI research within OpenAI. It presents early data on agent usage, experiment velocity, task complexity, and the resulting acceleration of research. The piece highlights the growing role of these agents in speeding up development and experimentation.
How autonomous agents broke two decades of capacity planning — and what to build instead The post Three Generations of Autoscaling — And Why Agentic Traffic Breaks All of Them appeared first on Towards Data Science .
By Shoumik Chakravarty
The paper investigates how large‑language‑model (LLM) based AI agents mix latency, local resource usage, and container bottlenecks when processing user requests that involve remote LLM calls and local tool execution. By measuring three representative tasks—retrieval‑augmented question answering, web search, and software coding—the authors show that agents exhibit diverse resource dynamics, with concurrent requests revealing task‑specific bottlenecks in CPU, disk I/O, and memory. Leveraging these insights, they propose CPU‑aware tool admission and task‑aware CPU allocation, achieving up to a 5.4× speed‑up for CPU‑sensitive tasks and a 32% reduction in average latency across multiple tasks.
By Wonmi Choi, Minuk Park, Zhixiong Niu, Yongqiang Xiong, Chuck Yoo, Gyeongsik Yang