
LLM Evals Start as Thirty Test Cases, Not a Platform
Most LLM features ship on vibes and break on the next prompt tweak. A small regression set, cheap deterministic checks, and a judge you actu...

Most LLM features ship on vibes and break on the next prompt tweak. A small regression set, cheap deterministic checks, and a judge you actu...

Prompt caching can cut repeated input costs by around 80%, but only if your prompt is ordered so the stable parts come first. Here's how it ...

The agent and its job I have a loop-agent running on my MacBook for about 6 months.

An LLM bill grows faster than traffic. Here's how prompt caching, the Batch API and smaller models cut it, with real prices, tested Python c...
Discover how Apple's MLX framework brings efficient machine learning to Apple silicon. Learn about unified memory, lazy evaluation, GPU acce...

Constrained decoding means the model can't return malformed JSON. Here's how structured outputs work with Zod in TypeScript, and the edge ca...

I use LLMs every day without knowing how they work, so I built the smallest one I could: a tiny transformer that writes Shakespeare one char...

A newer model with an unchanged price table can still raise or lower your bill per task.

Frameworks make agents look complicated, but the core is small: a model, a few tools, and a loop. This post walks through a working coding a...