Turn Podcast Transcripts into Blog Posts with AI
A workflow for converting podcast transcripts into well-structured blog posts using AI, without losing the speaker's voice.
Start with a clean transcript
Run the raw transcript through the Transcript Cleaner. Removing timestamps and filler makes the content readable and cuts tokens so the whole episode fits in one prompt.
Extract, then draft
Ask first for an outline: main ideas, best quotes, and stories. Approve or edit it, then ask for a draft following that outline. Two steps beat one giant prompt.
Publish-ready formatting
Ask for Markdown output so headings and lists paste cleanly into your CMS. If you are pulling show notes from an HTML page, convert them with the Markdown Converter first.
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- Transcript Cleaner — Removes timestamps, filler words, and duplicate speaker labels.
- Context Compressor — Reduce token usage with compression strategies tuned for LLMs.
- Markdown Converter — Paste HTML, DOCX, or webpage text and get tidy Markdown.
Tools mentioned
Frequently asked
Will the post sound like AI?
Less so if you ask the model to use direct quotes and keep the host's phrasing. Always edit the draft.
How long should the post be?
Usually 1,000 to 1,500 words covering three to five main ideas from the episode.
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