Where's the holistic AI productivity data?
June 11, 2026 In AI, Business For most of my career I ran a very small company. When you run a tiny company your resources (both time and money) are limited, and you want to use them on the things that will have the most impact. You have to quickly stop doing things that aren’t cost-effective, to avoid “throwing good money after bad”.
- ▪June 11, 2026 In AI, Business For most of my career I ran a very small company.
- ▪When you run a tiny company your resources (both time and money) are limited, and you want to use them on the things that will have the most impact.
- ▪You have to quickly stop doing things that aren’t cost-effective, to avoid “throwing good money after bad”.
Hacker News (AI / LLM) files mainly under ai. We currently carry 3,302 of its stories.
Story provenance
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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 | Co |
| Canonical URL | https://rachelandrew.co.uk/archives/2026/06/11/wheres-the-holistic-ai-productivity-data/ |
| Publication time | Sat, 04 Jul 2026 15:03:07 +0000 |
| Retrieval time | 2026-07-04T19:00:17.953Z |
| Last seen | 2026-07-04T19:00:17.953Z |
| 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 | fhqZ25qFFhnh |
| 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
Where’s the holistic AI productivity data? June 11, 2026 In AI, Business For most of my career I ran a very small company. When you run a tiny company your resources (both time and money) are limited, and you want to use them on the things that will have the most impact. You have to quickly stop doing things that aren’t cost-effective, to avoid “throwing good money after bad”. Ideally, you do a small trial of something new and measure the results before rolling it out more widely, to avoid going all in on something untested. As tech news starts to publish stories about how companies are realising that AI costs more than the humans it was supposed to replace, I’m wondering why it took them so long to figure this out.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Co.
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