Repurpose · blog post

Turn a podcast episode into a blog post

DomeScribe converts a podcast episode into a blog post by transcribing the audio first, then writing a standalone Markdown article from that transcript — a specific headline, an opening that states the core claim, three to six sections built on concrete details from the conversation, and a closing takeaway. The article is written for a reader who never heard the episode, not as an “in this episode we discussed” recap, and every fact in it comes from the recording.

Turn an episode into a post · How Transcribe Studio works

Updated 2026-08-23

Input
Upload MP3, WAV, M4A, FLAC, MP4, MOV, WebM — or paste a YouTube, Vimeo, TikTok, Facebook, X, Twitch, or Dailymotion link
Output
A Markdown article: H1, opening claim, 3–6 headed sections, closing takeaway — plus the timestamped transcript
Length
Standard is about 600–900 words; short is roughly half, long about 1.75×
Tone
Professional, casual, or punchy — each a separate draft
Cost
1 AI credit per draft; the transcript uses plan minutes (30 free minutes and 5 credits to start)
Retention
Transcript encrypted at rest, auto-deleted after 30 days; the uploaded file is deleted after transcription

How to turn a podcast episode into a blog post

  1. Transcribe the episode

    In Transcribe Studio, upload the episode file or paste its link. DomeScribe transcribes it with timestamps in any of 99 languages, detecting the language automatically. Long episodes are processed in chunks.

  2. Choose Repurpose → Blog post

    On the recording’s workspace, open Repurpose, pick Blog post, set a tone and a length, and generate. One draft costs one AI credit.

  3. Read it against the transcript

    The transcript sits beside the draft. Check names, figures, and any verbatim quote, then edit the Markdown in place or in your editor.

  4. Publish, then make the companions

    Paste the Markdown into WordPress, Ghost, Substack, or any CMS. From the same transcript you can also generate show notes, a LinkedIn post, an X thread, or a newsletter section — each a separate one-credit draft.

What a podcast-to-blog-post conversion should produce

A transcript pasted onto a web page is not a blog post; it reads like a conversation because it is one. The useful conversion is an article: it picks the episode’s central idea, states it up front, and supports it with the specific things that were said — a number, a story, a quote — arranged so a reader who skims the headings still gets the argument.

That is the brief DomeScribe’s blog-post format follows. The model is instructed to write a specific, non-clickbait H1 that names the idea rather than the episode, to put the core claim in the first two sentences, to build each section on a concrete detail from the transcript, and to close with one takeaway and a single reflective question or next step. It is told never to write “the host said” or “they discussed”; when the episode has one speaker, first person is allowed, otherwise a neutral authorial voice.

Why the article is written from the transcript, not from a summary

Repurpose drafts are generated only from the transcript of the recording. The model has no outside knowledge to fall back on and is instructed not to invent quotes, names, numbers, or links. If the episode does not contain something the format would normally want, it is left out rather than made up. That constraint is what makes the draft safe to publish after a read-through: the risk is a transcription error you can spot, not a plausible-sounding claim nobody made.

Because the transcript is machine-generated, the model is also told to read through filler, false starts, and mis-transcriptions silently and to quote verbatim only when a line is genuinely strong. The article you get reflects what the speakers meant, lightly cleaned, in the language the episode was recorded in.

Tone and length are contracts, not moods

Pick professional, casual, or punchy, and short, standard, or long. Each tone has observable markers the model must hit. Professional means longer, complete sentences, no contractions, no exclamation marks, claims stated with their evidence. Casual means shorter sentences, contractions, second person, jargon explained right after it appears. Punchy means sentences averaging six to twelve words, strong verbs, the claim first and the proof second.

Length scales the word target. A standard blog post aims for about 600–900 words; short keeps only the strongest idea and its best supporting detail at roughly half that; long uses more of the transcript — further examples, the full shape of the argument, a second quote — at about 1.75 times the standard target, without padding.

  • Professional + standard: an article for your site or a guest post.
  • Casual + long: a fuller piece for a personal blog or Substack.
  • Punchy + short: a tight companion post that links back to the episode.

Working from a link versus an uploaded file

If the episode is on YouTube, Vimeo, or another supported platform, paste the link and DomeScribe transcribes from it; for YouTube videos that already have captions, it can use those captions, which is faster because no audio is downloaded. The link is used only to produce the transcript — DomeScribe never provides the media file itself. If you have the episode file, upload it; video containers are converted to audio on the server before transcription.

Either way, the transcript is the same kind of object in Transcribe Studio: timestamped segments you can click to play, with Summary, Repurpose, Chat, and AI clip picks available from the same workspace. Drafts are cached, so reopening a blog post you already generated does not cost another credit.

Privacy

Transcription runs on DomeScribe’s servers: the audio is sent to a speech-recognition model and the uploaded original is deleted after transcription. The transcript is encrypted at rest with a per-user key and auto-deletes after 30 days, or sooner if you delete it. An audio copy is kept only for playback inside the app for the transcript’s lifetime and is never downloadable.

Questions, answered

Can AI really turn a podcast into a blog post?

Yes, if it works from the transcript. DomeScribe transcribes the episode, then writes a standalone Markdown article from that transcript — headline, opening claim, three to six sections, closing takeaway — using only facts present in the recording. You read it against the transcript and publish.

How long is the blog post?

The standard length targets about 600–900 words. Short is roughly half that and keeps only the strongest idea; long is about 1.75 times the standard target and draws more examples and quotes from the transcript. Each length is a separate one-credit draft.

Will it sound like a recap of the episode?

No. The format brief tells the model to write an article for someone who never heard the recording — never “in this episode” or “the host said”. It names the idea in the headline, states the claim first, and supports it with specifics from the conversation.

Can I make a blog post from a podcast that is on YouTube?

Yes. Paste the YouTube link; DomeScribe transcribes it (using the video’s existing captions when available) and generates the article from that transcript. The link is used only to produce the text — no media file is provided.

Does it work in languages other than English?

Yes. Transcription supports 99 languages with automatic detection, and the article is written in the transcript’s language.

What does it cost?

One AI credit per blog-post draft. Every account starts with 30 minutes of transcription and 5 credits at no charge and with no credit card. Pro is $19 per month with 1,000 transcription minutes and 300 credits; see /pricing for Business.

Can I get a Word document instead of Markdown?

The blog-post draft is Markdown, which pastes into WordPress, Ghost, Substack, and most editors. The transcript itself exports as TXT on every plan and as DOCX, PDF, or JSON on paid plans.

Related

Try it on your own recording

Free to start — 30 minutes of transcription and 5 AI credits, no card required.

Turn an episode into a post · See pricing