Rapid Prototyping

Warning: This article has a lot of embedded code, so the ball machine is slow unless you have a REALLY fast computer. Play at your own risk.

Seriously, though.

GPT-5, as a simple text completion model, is not a revelation.

This isn’t so surprising. It was becoming clearer with every new raw LLM release that the fundamental improvements from scaling solely the performance of the core text predictor were starting to show diminishing returns. But I’m going to make an argument today that, although the LLM itself is not nearly as much of a leap from GPT-4 as GPT-4 was from GPT-3, we have still seen at least a whole-version-number of real improvement between the release of GPT-4 and 5 as we did between 3 and 4. The reasons for that are mostly what exists around that LLM core.

I built a nice little tool to help AI write code for you.

I’m writing this post retrospectively as I never published it at the time of creation. It will live here as a “stake in the ground” of AI software capabilities as of March 2023. Note- if you’re reading on substack, this post won’t work. Go to hockenworks.com/gpt-4-solar-system.

The interactive solar system below was created with minimal help from me, by the very first version of GPT-4, before even function calling was a feature. It was the first of an ongoing series of experiments to see what frontier models could do by themselves - and I’m posting it here because it was the earliest example I saved.

Here’s a link to the chat where it was created, though it’s not possible to continue this conversation directly since the model involved has long since been deprecated: https://chatgpt.com/share/683b5680-8ac8-8006-9493-37add8749387

The Answering Machine is a proof-of-concept system that I built using pre-LLM natural language processing (NLP), specifically NLTK, to produce answers to questions asked about data in plain English.

Looking back, this project was a great insight into what LLMs immediately allowed that was incredibly difficult before. This project was several months of work that the openAI sdk would probably have allowed in a few weeks - and that few weeks would have been mostly frontend design and a bit of prompting.

Try it here: http://voicequery-dev.s3-website-us-west-2.amazonaws.com/ Github: https://github.com/hockenmaier/voicequery

The system uses natural language processing to produce answers to questions asked about data in plain English.

Editor’s note from 2025:

First Ten is no longer available after Google discontinued custom voice apps in 2023, but I’m leaving this article here as a record. Now, similar apps can be built in hours or minutes using modern AI models. First Ten used a now outdated intent routing system to fetch information from a serverless architecture about the Bill of Rights. Interestingly, my infrastructure for this app is still up and running behind the scenes because it’s truly serverless and costs nothing to host.

First Ten is an educational app containing information about the U.S. Bill of Rights, accessible on Google devices and smart speakers.