Rails and AI
Methodology Each model ran every evaluation three times in August or September 2026, using the provider's default settings — 63 runs per model. Accuracy is the share of runs that passed the evaluation's hidden tests; refusals count as failures, and differences of a few points between models are within run-to-run noise. Speed is the median run duration, and tokens and cost are means per run.
- ▪Methodology Each model ran every evaluation three times in August or September 2026, using the provider's default settings — 63 runs per model.
- ▪Accuracy is the share of runs that passed the evaluation's hidden tests; refusals count as failures, and differences of a few points between models are within run-to-run noise.
- ▪Speed is the median run duration, and tokens and cost are means per run.
Hacker News (AI / LLM) files mainly under ai. We currently carry 6,380 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Ruby on Rails: Compress the complexity of modern web apps |
| Canonical URL | https://rubyonrails.org/ai |
| Publication time | Thu, 24 Sep 2026 23:38:18 +0000 |
| Retrieval time | 2026-09-24T23:40:26.867Z |
| Last seen | 2026-09-24T23:40:26.867Z |
| 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 | None |
| Cluster logic | Not yet clustered, or no peer story found in the clustering window. |
| 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
Methodology Each model ran every evaluation three times in August or September 2026, using the provider's default settings — 63 runs per model. Accuracy is the share of runs that passed the evaluation's hidden tests; refusals count as failures, and differences of a few points between models are within run-to-run noise. Speed is the median run duration, and tokens and cost are means per run. API recall is the percentage of runs in which the model reached directly for the target Rails API. Model-level medians come from run-level data, so they can differ slightly from the per-evaluation timings. GLM 5.3 ran on a coding-plan subscription, so it carries no dollar figures. Select any model or result for the underlying evaluation details. Explore the open-source Rails AI evaluation suite.
Excerpt limited to ~120 words for fair-use compliance. The full article is at Ruby on Rails: Compress the complexity of modern web apps.
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