1660362 comments

• Comment Link
  Rosa Mack

  Sábado, 24 Octubre 2026 13:20

  The blind-vote results seem more useful than a polished launch demo, especially when small model upgrades can change how answers feel in everyday use. I’d be curious whether the ranking holds across different task types, not just general prompts https://privatebin.net/?ed102ffad983944f#DXQ5pavxon1cCgHNp1hTGPBdAHojDmDBJgivR1ZCaHw8
• Comment Link
  Jackson Quinn

  Sábado, 24 Octubre 2026 13:18

  As a product manager, I can see multi-model orchestration helping with research summaries where one model’s blind spots can derail the whole draft. The reported 35 multi AI tool for analytics
• Comment Link
  Gerald Moran

  Sábado, 24 Octubre 2026 13:15

  I like the reminder that agreement is not proof, especially when several models are weighing in at once. A confident consensus can still repeat the same blind spot AI multiple
• Comment Link
  Charlotte Colon

  Sábado, 24 Octubre 2026 13:15

  The blind-vote format seems useful because it focuses on how answers feel before people know which model produced them. Still, a small preference gap can be hard to interpret if the prompts vary Additional hints
• Comment Link
  Lewis Hogan

  Sábado, 24 Octubre 2026 13:14

  I manage content workflows for a small nonprofit, so the Sequential vs Super Mind comparison caught my eye. Having models check one another could help with research summaries, but I wonder how much the results depend on the task and prompt quality multi agent multi model platform
• Comment Link
  Lida Padilla

  Sábado, 24 Octubre 2026 13:13

  The blind-vote angle is useful because it focuses on what people actually prefer, not just benchmark scores. Still, a 2-point edge could mean something very different with a small sample than with thousands of votes Claude vs GPT model updates
• Comment Link
  Dominic Munoz

  Sábado, 24 Octubre 2026 13:12

  I like the point that parallel and sequential chats serve different purposes: getting several independent views is useful, while a follow-up can help test an emerging idea. The Red Team step seems especially practical for catching blind spots https://future-wiki.win/index.php/How_Do_I_Get_AI_to_Find_Gaps_in_My_Plan_Instead_of_Rewriting_It_Prettier%3F
• Comment Link
  Marguerite Curtis

  Sábado, 24 Octubre 2026 13:10

  As a product manager, I’ve been experimenting with multi-model workflows for research summaries, so the Sequential vs Super Mind comparison caught my attention multiple AI in one platform
• Comment Link
  Georgie Wallace

  Sábado, 24 Octubre 2026 13:10

  I like the distinction between parallel and sequential chats, since asking several models at once seems useful for surfacing different angles before one model pulls the ideas together http://storylatticex.com/s/ZUye2I1H5GYjkwcAbuAvY
• Comment Link
  Olga Stewart

  Sábado, 24 Octubre 2026 13:08

  I could see using Suprmind for an IC memo when I need to pressure-test an investment thesis from several angles multi-model AI platform