PostHog will train AI models with your data (opt-in by default)
PostHog is planning to train AI models using user data to enhance its products. The initiative aims to make existing tools smarter and develop new features like PostHog Code. Users will have the option to opt-out of data usage for this purpose by default.
- ▪PostHog has started integrating AI-powered features into its platform over the past year.
- ▪The company aims to build proactive products that can automatically provide solutions and improve over time.
- ▪One focus area for the AI models is session replay analysis to enhance user experience and product development.
Hacker News (AI / LLM) files mainly under ai. We currently carry 2,433 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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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 | Posthog |
| Canonical URL | https://posthog.com/blog/training-ai-models |
| Publication time | Wed, 27 May 2026 16:08:42 +0000 |
| Retrieval time | 2026-05-27T16:23:01.931Z |
| Last seen | 2026-05-27T16:23:01.931Z |
| 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 | _hcSlORLyVth |
| 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
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Posthog.
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