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Rob Greenlee sits down with Neil Mody, CEO and co-founder of Headliner, at Ginni Media Studios in New York City. They ask what helps someone discover a show and what gives that person a reason to come back. The conversation covers YouTube, social clips, podcast apps, RSS, newsletters, and what AI can and can’t tell a creator about which moments are worth sharing.
Three practical takeaways
- Give a stranger a reason to press play. Choose a clip that makes the episode’s question clear before the viewer knows the show or the guest. If the clip needs a long introduction to make sense, pick another moment.
- Give people one clear next step. Send viewers from a discovery clip to the full episode, where they can watch, listen, or opt in for more. Judge the clip on the behavior you can observe. Views alone can’t tell you who came back.
- Compare AI clip suggestions with your own shortlist. Neil describes Headliner’s work comparing how different methods surface clips. Watch each candidate in context and keep the one that delivers a complete idea without changing what the speaker meant.
One practical next step
Pick one episode and spend up to 30 minutes cutting a single moment that answers a real audience question. Share it on one channel with a trackable link to the full episode. After seven days, check episode-link clicks. If you tracked a comparable clip before, compare its first seven days on the same platform. A clip that gets views but few clicks gives you a reason to revisit the clip or its invitation. If your platform can’t track clicks, keep views as a measure of reach and leave listener conversion open.
How people choose a podcast
Neil traces Headliner’s early audiograms to a distinction between choosing an episode and consuming it. Someone might make the first decision while scanning a screen, then listen with the phone in a pocket. He remembers podcasters splitting over whether to put audio shows on YouTube. Some welcomed an automated way to get their back catalog there. Others doubted that YouTube was a destination for an audio show. Later in the interview, Neil says audiences had grown accustomed to the audiogram format and that creators needed to rethink what would earn attention in a feed.
Rob brings the discussion back to what happens after discovery. A short clip can lead to the full episode. A newsletter gives people who opt in a way to hear from the show again. Those are separate decisions for the audience, and each needs a clear invitation.
What podcast platforms can learn from YouTube
Neil identifies three openings for podcast platforms: help shows reach people across social feeds, explore discovery through AI search, and build tools that are specific to podcasts. Rob points to YouTube Studio as a benchmark for creator reporting. Neil frames the practical question as attribution: after publishing several posts to promote an episode, can a creator tell which one moved someone toward listening? Rob adds that making and tracking all those posts is work in its own right.
Neil gives an example of a listening tool built for the medium. He describes a prototype called TLDL (Too Long, Didn’t Listen) and a personal setup that sends him short audio excerpts from shows he follows each morning. Hearing the excerpts helps him choose episodes he might otherwise pass over. It’s an example from his own routine and illustrates how an app could help listeners decide what to play even after they have followed a show.
Why keep separate audio and video feeds?
Rob describes how New Media Show offers separate audio and video RSS feeds and can reference the other format through an alternate enclosure. That gives compatible apps another file to offer while keeping a primary format for each feed. Neil describes a related habit: he sometimes starts with video to get familiar with a guest, then keeps listening in the background.
They weigh how that flexibility could evolve. Neil expects large platforms to favor their own integrations for functions such as monetization and control. Rob points to the value of publishing once for many listening experiences and raises the possibility that open feeds could also supply content to future AI tools. Both are describing possible directions for distribution.
What Headliner is learning about clip selection
Headliner had already written clip selection software before using large language models for that job. Neil says he was surprised by how often the two methods picked similar moments. He describes a separate blind comparison of human and model picks as work in progress. The interview gives no completed result from that test or evidence that the overlap led to more episode plays.
Rob points out that the producer still decides which clip goes out, even when a tool assigns a score for predicted reach. For an interview, that means watching the suggested cut with the surrounding exchange. A striking answer may depend on the question or on a qualification the speaker adds a few seconds later.
Episode resources
- About Headliner and Neil Mody’s work
- Neil Mody’s October 23 article on how podcast platforms could compete with YouTube
- Headliner’s September 14 announcement about its YouTube clip automation
- Ginni Media Studios, the recording location
- Support independent New Media Show conversations
For a practical follow-up, read What Happens After Someone Finds Your Podcast? on RobGreenlee.com.
