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:

• A model on par with Claude Sonnet 5 can run for about 1/40th the cost through a smart-and-cheap provider pick.

• Reddit's questions, not its answers, make the safest source material, with a human still filtering trolls and skipping competitor mentions.

• One Gemini Notebook prompt turns a raw Reddit export into 100 ranked questions.

• Recording on an iPhone in a kitchen can beat a polished studio setup on platforms downranking synthetic-looking video.

• 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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