What Building an LLM Playground Actually Taught Me
Every claim the series made, in one place, stated plainly and traced back to the experiment that supports it.
Category
tech
Notes on building software, machine learning, and the tools I use.
The GCP Deployment Runbook: Every Command, Every Fix
The exact commands, in order, including every failure and fix, for deploying a FastAPI + React app to Cloud Run.
TechJuly 12, 2026
Do AI Models Ever Go Obsolete?
What happens to old models, how labs actually build the next generation, and what's really changing under the hood when they do.
It Works on My Laptop: The Distance Between Running and Shipping
The gap between an application that runs and one that ships, written from an actual deployment rather than a plan for one.
Who Judges the Judges? Small Models Grading Small Models
Using small models as evaluators for other small models, and finding out how much you can and can't trust the judge.
The Same Model, Before and After: What Post-Training Actually Changes
A controlled comparison of a base model and its instruction-tuned sibling, testing whether assistant behavior is installed or emergent.
Watching a Model Fail on Purpose: Tokenization and the Decoding Tradeoff
How text becomes tokens, how probability distributions become text, and what happens when you push both to failure on purpose.
Building an Instrument, Not a Model: Why My First ML Project Was a Playground
Why I built an LLM playground instead of training a toy model, and what the architecture teaches before any experiment runs.