Podroll: Podcast Recommendations from Creators You Trust
Last updated: March 2026
Most podcast discovery tools push what's popular or what keeps you engaged longest. The Podcast App surfaces podroll — a Podcasting 2.0 standard where creators embed their own recommendations directly in their RSS feed. When a podcaster you follow says a show is worth your time, that is a signal worth acting on.
Why Podroll Recommendations Are Different
Recommendations You Can Trust
Podroll entries are not generated by an algorithm — they are hand-picked by the creators themselves, embedded in their RSS feed via the podcast:podroll tag from the Podcasting 2.0 namespace. When a podcaster adds a show to their podroll, it is a deliberate, personal endorsement. You are not getting a prediction about what might keep you listening longer; you are getting a recommendation from someone whose editorial judgment you have already chosen to follow.
Discover Beyond the Algorithm
Algorithmic recommendations optimize for engagement signals — plays, completion rates, social graphs — and tend to reinforce what you already listen to. Podroll breaks that loop. Because recommendations come from real human curation rather than engagement metrics, they can surface shows from different genres, smaller creators, or entirely new perspectives that an algorithm would never surface. It is the podcast equivalent of a trusted friend saying, "you should really listen to this."
How Podroll Works in The Podcast App
1. Podcaster Adds Recommendations
A podcaster uses their hosting platform or RSS editor to add a podcast:podroll block to their feed. Each entry references another show by its Podcast Index GUID, making it a stable, portable link between podcasts that works across any Podcasting 2.0-compatible app.
2. App Reads the Podroll
When The Podcast App parses a podcast's RSS feed, it reads the podcast:podroll entries and resolves each GUID to its corresponding show — fetching artwork, title, and description from the Podcast Index. No extra action required from the listener.
3. "Recommended by This Show" Appears
On the podcast's page in the app, a dedicated "Recommended by [Show]" section displays artwork cards for each podroll entry. Tap any card to open that podcast, read the description, and subscribe — all in a single flow.
Your Questions, Answered
What is a podroll?
A podroll is a list of podcast recommendations embedded directly in a show's RSS feed using the podcast:podroll tag from the Podcasting 2.0 namespace. It is how a podcaster says, in a machine-readable way, "these are the other shows I recommend." When you open a podcast in The Podcast App, any podroll entries appear in a dedicated "Recommended by this show" section so you can instantly explore the creator's personal picks.
How is this different from algorithmic recommendations?
Algorithmic recommendations are generated by engagement signals — plays, completions, and social graphs — and optimized to maximize time in app. Podroll recommendations are human decisions made by the creators themselves. The podcaster chose those shows because they believe in them, not because a model predicted you would click. That distinction matters: you are getting a personal recommendation from someone whose judgment you already trust, not a prediction from a system you cannot inspect.
Do all podcasts have podrolls?
No. Podroll is part of the Podcasting 2.0 namespace and requires the podcaster's hosting platform to support it and the podcaster to actively configure it. Adoption is growing as more hosts add support and more creators learn about the feature. If a podcast has no podroll, the section simply does not appear. The Podcast App surfaces podrolls whenever they are present in the feed, with no extra steps required from the listener.
The Discovery Problem in Podcasting — and How Podroll Solves It
Podcast discovery has a fundamental trust gap. There are more than four million active podcast feeds and no authoritative way to know which ones are worth your time. Platform charts favor shows with existing audiences. Algorithmic recommendations optimize for what will keep you listening rather than what will genuinely interest you. Word of mouth works, but it doesn't scale. For independent podcasters — particularly those outside the top one percent by download count — getting in front of new listeners has always been a function of marketing budget rather than quality. The result is a discovery ecosystem that consistently amplifies the already-popular and systematically undervalues the interesting-but-unknown.
The podcast:podroll tag, developed as part of the Podcasting 2.0 initiative, is a structural solution to this problem. It adds a machine-readable recommendation block to the standard RSS feed format. A podcaster who wants to recommend other shows adds those shows to their podroll, referencing each by its Podcast Index GUID — a stable, cross-platform identifier. Any app that reads the Podcasting 2.0 namespace can then display those recommendations in context, directly on the podcast's page. The standard is open, free, and does not require any special relationship with a platform. A creator on any host can build a podroll; any compliant app can read it.
The Podcast App displays podroll entries as artwork cards in a "Recommended by [Show]" section on each podcast's detail page. When the app parses the RSS feed, it resolves each podroll GUID against the Podcast Index, fetches the recommended show's cover art and metadata, and renders the cards inline. The result is a native, low-friction discovery surface that appears exactly where you are already engaged — on the page of a show you are currently listening to. Tapping a card opens the recommended podcast directly: you can read its description, sample recent episodes, and subscribe without leaving the flow. No separate discovery tab, no algorithmic detour.
The advantage of creator curation over algorithmic curation is not just philosophical — it is structural. Creators curate from their own taste, their knowledge of the space, and their understanding of their audience. They are not optimizing for any metric other than "this show is good and my listeners will appreciate it." That signal is fundamentally different from what engagement-maximizing algorithms produce. Over time, as more podcasters adopt podroll and more apps surface it, the standard creates a distributed web of human-curated connections across the podcast graph — a discovery layer built from editorial judgment rather than behavioral data.
Discover Through Creators, Not Algorithms
Download The Podcast App and start finding new shows the way it should work — through the recommendations of creators you already trust, powered by open standards.