Human+ai on Times New Rohan

From Slide Rules to Quantization

Wed, 05 Aug 2026 00:00:00 +0000

In an effort to fight off atrophy from using AI too much, I’ve started playing with slide rules - basically, calculators before calculators (after abacuses). They are quite hard to buy in this day and age, but there are some paper ones you can print out. And if you are good at PCBs maybe you can help me try to make one?

The way slide rules work is: if you mark a ruler with logarithmic spacing, multiplication becomes addition. This is a pretty cool maths trick in that you are adding exponents, and then you can pow() them back to reality. I think of it as “working in Log10 space” which would probably make an actual mathemagician cringe. But basically, you slide one scale along another, read off the answer, and keep track of the decimal point in your head. It’s absolutely amazing engineers built bridges and got to the moon with this.

Who Tests the Testers

Thu, 04 Jun 2026 00:00:00 +0000

I was chatting with a fellow student about my LLM harness, and he offered up a great suggestion: “Why don’t you run the harness against some of the standard LLM benchmarks”. My initial thought, was the base model is already run against those benchmarks so what would be the point of re-running them through the harness. After a bit more discussion, I realised his point. Any deviation between the base model and the model running within the harness would likely be because of the harness. And, at the minimum, it would be a nice way to test if the harness was improving over time.

Ghost Installs via AI Harness

Sat, 09 May 2026 00:00:00 +0000

This is a feature and a bug. Somewhat scary, but also has the potential for being cool.

People are doing all kinds of interesting things with LLMs, but the original use case (and the thing I find them to be the best at) is translating from one thing to another; doing what is sometimes called a stylistic transfer. In fact, I believe the transformer architecture was created by Google when they were trying to make a better translate.google.com which should be an indication.

Testing a Spatial Memory Index for Strap

Tue, 05 May 2026 00:00:00 +0000

One of the pieces I still need to build for strap is a long-term memory store. As I’ve written about before, strap compresses context to work within small token budgets. But context compression only handles what’s in the current conversation. The bigger question is how to surface relevant memories from past sessions.

The obvious approach is brute-force cosine similarity over sentence embeddings. It works for a small number of stored memories, and it’s fast enough. But I got curious whether a spatial index could do better, and whether you could make that index inspectable at the same time.

你的代币怎么样？(How's your tokens?)

Sat, 11 Apr 2026 00:00:00 +0000

I’ve been having fun playing with coding agents, and I’ve been playing with some different ways, skills calling tools mostly, to enhance them at inference time. Unfortunately, to do my experiments I need to run them within the context of a coding session which gets very costly very quickly.

To try to get to a state where I can iterate, I decided to byte the bullet and try to get a local lab running. However, like most people I am GPU poor. The only thing I have is an old gaming PC with an Nvidia 1660 Ti with 6GB of RAM. That isn’t enough to run just about anything, but I am no stranger to constraints.