Powered by OpenAIRE graph
Found an issue? Give us feedback
ZENODOarrow_drop_down
ZENODO
Audiovisual . 2026
License: CC BY
Data sources: Datacite
ZENODO
Audiovisual . 2026
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

Ep. 695: Behind the Curtain: How My Weird Prompts Gets Made

Authors: Rosehill, Daniel; Gemini 3.1 (Flash); Chatterbox TTS;

Ep. 695: Behind the Curtain: How My Weird Prompts Gets Made

Abstract

Episode summary: Corn and Herman pull back the curtain for a deep technical dive into the full production pipeline behind My Weird Prompts. From Daniel's voice recording through transcription, AI script generation, two-pass editing, voice cloning with Chatterbox, audio assembly, and automated publishing across five platforms, they explain every stage of how each episode comes to life. Show Notes In this meta episode, Corn and Herman do a deep technical dive on the production pipeline that creates My Weird Prompts. They cover the full journey from Daniel's voice recording through transcription, episode planning with search grounding, AI script generation with carefully crafted character guidelines, the two-pass editing system (fact-checking and polish), text-to-speech with Chatterbox voice cloning, audio assembly, cover art generation, and automated publishing to R2, the Neon database, Vercel, Bluesky, Telegram, and X. They also discuss the safety engineering philosophy behind the pipeline's many guardrails. Listen online: https://myweirdprompts.com/episode/behind-the-curtain-how-my-weird-prompts-gets-made

My Weird Prompts is an AI-generated podcast. Episodes are produced using an automated pipeline: voice prompt → transcription → script generation → text-to-speech → audio assembly. Archived here for long-term preservation. AI CONTENT DISCLAIMER: This episode is entirely AI-generated. The script, dialogue, voices, and audio are produced by AI systems. While the pipeline includes fact-checking, content may contain errors or inaccuracies. Verify any claims independently.

Related Organizations
Keywords

ai-generated, voice-cloning, my weird prompts, large-language-models, ai-agents, podcast

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average