AI Engineering
Distillation in Practice: Turning a Frontier Model Into a Cheap Specialist
A practical walkthrough of distilling a narrow task from a frontier LLM into a small, cheap fine-tuned specialist model, including data collection and evaluation steps.
Sachin SharmaCreator
Jul 18, 2026
6 min read

Featured Resource
Quick Overview
A practical walkthrough of distilling a narrow task from a frontier LLM into a small, cheap fine-tuned specialist model, including data collection and evaluation steps.

Previous Article
Python 3.13 Free-Threading: What It Means for AI Workloads
PEP 703 shipped an experimental GIL-free build of CPython. For AI backends specifically — not Python in general — here's what actually changes, and what doesn't yet.

Next Article
Building for Foldables and Spatial Displays: A Responsive Design Rethink
A Galaxy Fold in tabletop mode broke a layout that passed every breakpoint test I had. Foldables and glasses-free 3D displays need a different unit of responsive design than screen width.