Why most agents are just flowcharts in disguise, and what to build instead.
Editor's Picks
Watermarks act at the model’s moments of doubt, and so do the safety checks that catch AI mistakes
How DFlash trades spare compute for saved memory bandwidth, and why its gains shrink as concurrency rises
LoRA fine-tuning solved our under-labeling problem. Whether it makes sense for you depends on three questions.
A walkthrough of and the maths behind using low-capacity networks to acquire fine-grained scoring when only categorical labelling is available for training
A production account of the throughput work behind a 16x jump — and the two guarantees it was never allowed to trade away
People can accept tradeoffs when they see value — but if they don’t, what happens?
5 principles that determine whether an agent system succeeds in production, explained through one I built for a $100M+ company.
How autonomous agents broke two decades of capacity planning — and what to build instead
Here's how to be the Data Scientist who thrives in a world where coding is a commodity.