Do newer coding models end up training on the AI slop generated by older models?
The article discusses the potential issue of newer coding models being trained on subpar output generated by older models. It questions the assumption that human-written code used for training original models is free of errors or 'slop'. The author suggests that the averaging nature of these models and the way attention works may contribute to the problem.
- ▪Newer coding models may be trained on low-quality output from older models.
- ▪Human-written code used for training original models can contain errors or 'slop'.
- ▪The way attention works in these models may play a role in perpetuating the issue.
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Record
| Original publisher | Ycombinator |
| Canonical URL | https://news.ycombinator.com/item?id=49105219 |
| Publication time | Thu, 30 Jul 2026 01:40:01 +0000 |
| Retrieval time | 2026-07-30T01:53:23.302Z |
| Last seen | 2026-07-30T01:53:23.988Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | Z3NZuZHaHesK · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
How much do we assume human written code for training the original models is free of human made slop? We all know we all take shortcuts and have code we are not proud of. If they are I deed averaging machines, is it possible their output is the average of human output?I'd argue that the way attention works plays into the slop too
Excerpt limited to ~120 words for fair-use compliance. The full article is at Ycombinator.