AI and Teams =?
AI + Teams = ?What happens to our teams when we introduce these exemplary new AI teammates? Research from NYU shares valuable lessons.Marcus CastenforsSep 26, 2026311ShareA new team member shows up one day.It’s the chatty, diligent type, always cheerful and eager to help. All business, but after “thought for 42s”, sometimes hallucinates and goes off on a tangent.A question I’ve been pondering: what happens to our team when we introduce these exemplary AI teammates?
- ▪AI + Teams = ?What happens to our teams when we introduce these exemplary new AI teammates?
- ▪Research from NYU shares valuable lessons.Marcus CastenforsSep 26, 2026311ShareA new team member shows up one day.It’s the chatty, diligent type, always cheerful and eager to help.
- ▪All business, but after “thought for 42s”, sometimes hallucinates and goes off on a tangent.A question I’ve been pondering: what happens to our team when we introduce these exemplary AI teammates?
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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 | Hacker News (AI / LLM) |
| Canonical URL | https://mcastenfors.substack.com/p/ai-teams |
| Publication time | Sun, 27 Sep 2026 06:56:45 +0000 |
| Retrieval time | 2026-09-27T07:05:40.931Z |
| Last seen | 2026-09-27T07:05:40.931Z |
| 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 | 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
AI + Teams = ?What happens to our teams when we introduce these exemplary new AI teammates? Research from NYU shares valuable lessons.Marcus CastenforsSep 26, 2026311ShareA new team member shows up one day.It’s the chatty, diligent type, always cheerful and eager to help. Works around the clock. Doesn’t eat lunch. All business, but after “thought for 42s”, sometimes hallucinates and goes off on a tangent.A question I’ve been pondering: what happens to our team when we introduce these exemplary AI teammates? How will the team dynamics change?Fortunately, we have scholars ruminating on the same subject such as New York University professor J.P.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Hacker News (AI / LLM).
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