Share the goodness!
Most social teams brainstorm content ideas from memory or a generic AI prompt, then wonder why nothing sounds different from a competitor’s post. Christopher Penn, Chief Data Scientist at TrustInsights.ai, pulls real audience questions straight out of Reddit and turns them into a ranked list of 100 video topics.
In this episode:
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A model on par with Claude Sonnet 5 can run for about 1/40th the cost through a smart-and-cheap provider pick.
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Reddit’s questions, not its answers, make the safest source material, with a human still filtering trolls and skipping competitor mentions.
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One Gemini Notebook prompt turns a raw Reddit export into 100 ranked questions.
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Recording on an iPhone in a kitchen can beat a polished studio setup on platforms downranking synthetic-looking video.
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Turning on YouTube’s third-party training permission gets a creator’s expertise cited by AI agents.
Timestamps:
0:00 – The line that opens every failed AI pipeline
2:39 – Why Chris skipped Claude Code for OpenCode
5:05 – Mapping models by smart-and-cheap, not by brand
9:45 – Why a product requirements document comes before any code
13:31 – The one file that survives an AI’s memory getting compressed
17:50 – Turning a Reddit export into a grounded notebook
20:51 – The exact prompt that produces 100 ranked questions
22:05 – Why a human still filters trolls and skips competitors
25:00 – Recording in a kitchen on purpose
29:07 – The YouTube setting that trains AI on your expertise
31:52 – The one trap that breaks every rushed AI pipeline
Guest: Christopher Penn, Chief Data Scientist, TrustInsights.ai
trustinsights.ai · christopherspenn.com · LinkedIn
Full show notes and transcript:
https://www.agorapulse.com/blog/podcasts/ai-social-playbook/e4
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