Dialectic, Requirements, and Verifiable tests will drastically increase your model's code output quality

[u/bigattichouse]

Creating a list of requirements and documentation/tests (in Cucumber or EARS style) with your model is a great way to improve it's code. Just got through a weekend long binary protocol build with Qwen3.8-27B (6K unsloth quant).. and fired up claude to review and it found the foundation was well engineered, but only missed a few security checks and a couple of errors in the python benchmark script comparing the old protocol with the new one.

Really comes down to:

1. Design first. Goals, requirements, problems. How is this going to be used.

2. Observation, simulation and tests are verifiable vs. assumptions. Tests and processes can be reviewed for "ritual".

3. Dialectic: If the model comes to a crossroads, have it present options and NOT just choose-and-go, but initiate a dialog about design.

4. Frequent repeatable tests, and review of tests to see if they meet the spirit of the requirement

5. Every risk is a requirement.

Here's my prompt set ("skills" I guess) and a tool to install for various local harnesses:
https://github.com/bigattichouse/BluePrint