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 .
Summary generated by The Flow from the publisher's feed. The full article lives at Towards Data Science.
The hidden cost of asynchronous systems, how tiny CPU tasks quietly became our biggest bottleneck while scaling hundreds of LLM agents. The post Why Adding More AI Agents Made Our System Slower appeared first on Towards Data Science .
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 .
How to set the rules that keep agents effective and out of trouble The post What AI Agents Should Never Do on Their Own appeared first on Towards Data Science .
arXiv:2607. 07397v1 Announce Type: new Abstract: Autonomous agents promise substantial gains in speed, scale, and labor efficiency, but their failures can impose abrupt and often irreversible costs.
Building an ALNS heuristic in Python for vehicle routing, time windows, capacity constraints, and mandatory driver breaks. The post Los Movimientos, Part II: Solving Large Pickup-and-Delivery Problems with Adaptive Large Neighborhood Search appeared first on Towards Data Science .
Using mathematical optimization to solve a pickup-and-delivery problem with time windows. The post “Los Movimientos”: The Routing Problem That Nearly Broke My Spirit appeared first on Towards Data Science .