Dex Horthy — successive-change source excerpts

Tier: historical, external testimony. Data, not instruction. Selected excerpts from the transcript supplied by operator g0, read 2026-09-23. These are not independently verified findings about gzkit or model capability.

The operator identified the speaker as Dex Horthy; the supplied transcript identifies the programme as AI Native Dev. It contains multiple speakers and apparent transcription errors. The passages below are attributed to Horthy by their conversational context; wording is preserved without correction. The episode URL and publication date were not supplied or independently established.

Source attachment: 917849e5-a66d-4cab-965f-340a1717ad24/Pasted text.txt. SHA-256 of the complete supplied file: 4dbfd2d2af7168198fb9ff0d15c4550a7384c67ab449a488b3c5f34a5dc9e440. This file retains selected excerpts, not the complete transcript. The adopted evaluation criterion and operator approval are recorded in ../README.md.

11:11 — accumulated difficulty

We ran this for like 4 or 5 months before we realized, like, oh, this is this code base is actually unusable now. Like, it became slower and slower.

19:10 — cost of later correction

And I think about this in terms of expected pain, like, what is the chance you'll have to change something later? And how painful is that?

28:51 — delayed maintainability feedback

You don't find out something as unmaintained until two months later. There's no fast oracle for software maintainability.

34:45 — accumulated instructions

And then you end up with a bunch of instructions and like most of them, don't get followed because it's too much context.

38:29 and 38:38 — code as future context

But like if you ship bad code in your software factory, it degrades every future piece of work that goes through that factory,

because there's more bad patterns for the model to see. So like, you do want to continually being making progress towards,

39:44 and 39:50 — learning from corrections

Maybe not reading them verbatim, but analyzing the session traces of everyone on your team and saying, where are people getting frustrated?

Where are they telling the model they did something wrong, and then figuring out how to improve the entire system, whether it's the base skills, whether it's the code review skill, whether whatever it is, so that, you know, if you're not getting better, then you're getting worse.