How to Use the WIN System for Podcast Production

February 28, 2026 · 6 min read

The Post-Production Bottleneck

Recording a podcast is the fun part. What happens after is the grind: reviewing hours of audio, writing show notes, finding the best quotes for social promotion, inserting chapter markers, and creating descriptions for each platform. For solo creators, this post-production work can take longer than the recording itself.

The WIN System automates the most time-consuming parts of podcast production by transcribing the recording in real-time and letting you analyze the entire conversation with AI prompts.

Recording Setup

Launch the WIN System before starting your recording session. It captures two audio streams simultaneously:

• System audio — Your guest's voice coming through Riverside, Zoom, SquadCast, Discord, or any recording platform.
• Microphone — Your voice.

Both streams are transcribed into a single timeline. You don't need to configure routing, virtual cables, or ASIO drivers. If the audio plays through your speakers or headphones, the WIN System captures it.

During the Recording

While recording, the WIN System produces a running transcript. This is useful for:

• Tracking time — You can glance at the transcript to see what's been covered and what you still need to ask.
• Noting highlights — If the guest says something brilliant, you'll see it in the transcript and can mentally flag it. No need to interrupt the flow to take notes.

Post-Recording AI Analysis

After the recording, click "Ask the AI" with production-specific prompts:

Show Notes

Generate podcast show notes from this transcript. Include: a 2-paragraph episode summary, a bullet-point list of every topic discussed with approximate timestamps, key quotes from the guest, and any resources/links mentioned during the conversation.

Chapter Markers

Create YouTube/podcast chapter markers from this transcript. Format as: [HH:MM:SS] Topic Name. Each chapter should represent a distinct topic shift. Include 8-15 chapters.

Social Media Clips

Identify the 5 most compelling, shareable, or controversial moments from this podcast transcript. For each, provide: the timestamp range, a direct quote (under 280 characters for Twitter), and a suggested social media caption.

Episode Description

Write a podcast episode description for Apple Podcasts, Spotify, and YouTube. Three versions: (1) A short one-liner for Spotify, (2) A 3-sentence description for Apple Podcasts, (3) A paragraph with SEO keywords for YouTube.

Blog Post from Episode

Turn this podcast transcript into a blog post. Restructure the conversation into a logical article with headers, key takeaways, and a conclusion. Remove conversational filler and organize by topic, not by chronological order.

Guest Research with RAG

Before a recording session, upload your guest's bio, published articles, or previous interview transcripts to the RAG tab. During the interview, you can ask the AI:

Based on what the guest just said about AI in healthcare and the articles I've uploaded from them, what would be a good follow-up question that goes deeper than what they've covered publicly?

Searchable Episode Archive

Save each episode's transcript as a text file in the RAG tab. Over time, you build a searchable archive of every episode. When planning future content, you can ask:

Have I covered the topic of AI hallucination on any previous episode? If so, what did we say and who was the guest?

Workflow Summary

1. Launch WIN System → Start Recording
2. Record your episode normally
3. Stop Recording → Ask the AI for show notes, chapters, social clips
4. Copy results into your hosting platform, social media, and blog
5. Save the transcript to RAG for future reference

Total post-production AI time: under 5 minutes for content that would normally take 1-2 hours.