{"id":3768,"date":"2026-02-12T07:11:57","date_gmt":"2026-02-12T12:11:57","guid":{"rendered":"https:\/\/rosenfeldmedia.com\/advancing-research\/?post_type=sessions&#038;p=3768"},"modified":"2026-03-11T08:38:47","modified_gmt":"2026-03-11T12:38:47","slug":"survicate-session-day-1","status":"publish","type":"sessions","link":"https:\/\/rosenfeldmedia.com\/advancing-research\/sessions\/survicate-session-day-1\/","title":{"rendered":"Why AI Is Bad at Research (and how to make it actually useful)"},"content":{"rendered":"<p>LLMs are everywhere, but when it comes to real research, they often fall short. Generic LLMs weren\u2019t built for continuous research workflows, and product researchers quickly see the problem: the outputs are generic, lack full context, and struggle to connect multiple data sources. Instead of surfacing meaningful insights, they can amplify noise.<\/p>\n<p>In this session, Daniel will break down why AI often fails research teams and what\u2019s missing. He\u2019ll show how to make AI actually useful for continuous product research.<\/p>\n<p>Accelerating analysis, connecting insights across sources, and keeping researchers at the center, equipped with a powerful tool rather than replaced by one.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>LLMs are everywhere, but when it comes to real research, they often fall short. Generic LLMs weren\u2019t built for continuous research workflows, and product researchers quickly see the problem: the outputs are generic, lack full context, and struggle to connect multiple data sources. Instead of surfacing meaningful insights, they can amplify noise. In this session, [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":4229,"template":"","session-theme":[],"session-type":[26],"rm-permissions":[],"event-type":[],"class_list":["post-3768","sessions","type-sessions","status-publish","has-post-thumbnail","hentry","session-type-sponsor-session"],"acf":[],"_links":{"self":[{"href":"https:\/\/rosenfeldmedia.com\/advancing-research\/wp-json\/wp\/v2\/sessions\/3768","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rosenfeldmedia.com\/advancing-research\/wp-json\/wp\/v2\/sessions"}],"about":[{"href":"https:\/\/rosenfeldmedia.com\/advancing-research\/wp-json\/wp\/v2\/types\/sessions"}],"author":[{"embeddable":true,"href":"https:\/\/rosenfeldmedia.com\/advancing-research\/wp-json\/wp\/v2\/users\/3"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rosenfeldmedia.com\/advancing-research\/wp-json\/wp\/v2\/media\/4229"}],"wp:attachment":[{"href":"https:\/\/rosenfeldmedia.com\/advancing-research\/wp-json\/wp\/v2\/media?parent=3768"}],"wp:term":[{"taxonomy":"session-theme","embeddable":true,"href":"https:\/\/rosenfeldmedia.com\/advancing-research\/wp-json\/wp\/v2\/session-theme?post=3768"},{"taxonomy":"session-type","embeddable":true,"href":"https:\/\/rosenfeldmedia.com\/advancing-research\/wp-json\/wp\/v2\/session-type?post=3768"},{"taxonomy":"rm-permissions","embeddable":true,"href":"https:\/\/rosenfeldmedia.com\/advancing-research\/wp-json\/wp\/v2\/rm-permissions?post=3768"},{"taxonomy":"event-type","embeddable":true,"href":"https:\/\/rosenfeldmedia.com\/advancing-research\/wp-json\/wp\/v2\/event-type?post=3768"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}