
Channels with Peter Kafka
by Vox Media Podcast Network
Is this your podcast?Vox Media Podcast Network is a prominent media company known for its innovative storytelling and deep dives into culture, technology, and politics. With a portfolio that spans various platforms, they leverage expertise to deliver engaging c…
On the show
From 30 epsHost
Recent guests
Recent episodes
How to Run a Political Campaign in the TikTok Era (And How Not To)
Oct 14, 2026
48m 50s
Larry Ellison’s Media Ambitions & Kevin Roose on AI’s Biggest Gamble
Oct 7, 2026
1h 01m 06s
David Ellison's Paramount-Warner Empire & The Fight That Comes Next
Sep 30, 2026
44m 22s
Meta's New $1300 Glasses and the Fight to Control AI
Sep 23, 2026
40m 16s
AI Wants to Shop for You. What Could Go Wrong?
Sep 16, 2026
40m 52s
Insights from recent episode analysis
Audience Interest
- media industry insights
- technology trends
Podcast Focus
- intersections of media and tech
- interviews with industry leaders
Publishing Consistency
- weekly or more often
- active for 10 years
Platform Reach
- part of Vox Media Network
- available on major platforms
Insights are generated by CastFox AI using publicly available data, episode content, and proprietary models.
Most discussed topics
Brands & references
Total monthly reach
Based on 3 signals.
Built from
By chart position
- 🇺🇸United States · Business NewsHOME#4135K to 183K
- 🇧🇷Brazil · Business News#244.4K to 23K
- 🇮🇳India · Business News#501.3K to 6.9K
- 🇩🇪Germany · Business News#531.2K to 6.2K
- 🇳🇬NG · Business News#16764 to 4.0K
- Per-Episode Audience
Est. listeners per new episode within ~30 days
49K to 259K🎙 ~2x weekly·598 episodes·Last published 5d ago - Monthly Reach
Unique listeners across all episodes (30 days)
98K to 518K🇺🇸71%🇧🇷9%🇮🇳3%+9 more - Active Followers
Loyal subscribers who consistently listen
54K to 285K11K real followers tracked across platforms
Market Insights
Platform Distribution
Reach across major podcast platforms, updated hourly
Total Followers
—
Total Plays
—
Total Reviews
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* Data sourced directly from platform APIs and aggregated hourly across all major podcast directories.
Social Links & Contact
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Official Website
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| Date | Episode | Topics | Guests | Brands | Places | Keywords | Sponsor | Length | |
|---|---|---|---|---|---|---|---|---|---|
| 10/14/26 | How to Run a Political Campaign in the TikTok Era (And How Not To) | Most of us stopped watching traditional TV a long time ago. Political campaigns, meanwhile, still spend most of their ad money there.Rob Flaherty has been trying to change that from inside Democratic politics. He’s been the digital guy for Hilary Clinton, and then Joe Biden, and then Kamala Harris’ 2024 campaign. (Here’s his post-mortem of that one.) Now he runs a political shop of his own. We talk about why campaigns are still built around TV ads; why campaign consultants have financial incentives to keep buying them; and what it takes to reach voters who live on TikTok, YouTube, podcasts, group chats, and algorithmic feeds instead. We also talk about the difference between paying creators and earning their attention, why some candidates can make social media work without becoming AOC or Zohran Mamdani, and why the next real wave of political innovation may come from the 2028 primaries. Learn more about your ad choices. Visit podcastchoices.com/adchoices | 48m 50s | ||||||
| 10/7/26 | Larry Ellison’s Media Ambitions & Kevin Roose on AI’s Biggest Gamble | Larry Ellison bought his son a media empire. What does he want from it? Vanity Fair’s Tom Dotan joins me to talk about the billionaire behind Paramount and Warner Bros., his connection to TikTok, and his politics. Tom’s reporting suggests there may be less of a master plan than you’d think. We also discuss why even Ellison’s enormous fortune has limits—and how his media bets are tied to Oracle’s AI gamble.Then, Kevin Roose joins me to discuss his new book, The AGI Chronicles, and a question I keep coming back to: Why did people who think AI could destroy humanity work so hard to build it? We talk about whether those same people can be trusted to slow things down, and I push Kevin on the gap between AI’s promises and what most of us experience. Plus: Why he left The New York Times to build a media business with Casey Newton. Learn more about your ad choices. Visit podcastchoices.com/adchoices | 1h 01m 06s | ||||||
| 9/30/26 | David Ellison's Paramount-Warner Empire & The Fight That Comes Next | David Ellison has won Warner Bros. Discovery. Now he has to figure out what, exactly, to do with it. LightShed analyst Rich Greenfield joins me to talk through the next version of the Paramount-Warner empire: Why Ellison wants to be Netflix; why CBS and the NFL still matter so much; and why simply bolting Paramount+ onto HBO Max won’t magically create a winning streamer. Then we zoom out to the much bigger problem for Hollywood: AI is making it easier and cheaper to create video, which could mean an explosion of stuff to watch — and a real challenge to the value of giant movie and TV libraries. Rich thinks the winners will need to become platforms, not just studios. We also talk about Meta’s Muse, and why Rich thinks it could be a much bigger deal than people realize. Learn more about your ad choices. Visit podcastchoices.com/adchoices | 44m 22s | ||||||
| 9/23/26 | Meta's New $1300 Glasses and the Fight to Control AI | I went to Meta’s Silicon Valley headquarters to try Mark Zuckerberg’s newest face computer: a $1,300 pair of virtual-reality glasses that are much lighter and cheaper than Apple’s Vision Pro, and still make you ask a very basic question: What am I supposed to do with this thing?So I asked my pal Mike Isaac, the New York Times tech reporter and longtime Meta watcher. We talked about why Meta keeps spending billions trying to put computers on our heads, why this version might have a better shot than the last ones, and where Meta’s fast-growing Muse AI agent fits into the company’s plan.Then we turn to the much bigger—and darker—AI story Mike has been reporting on: The fight over whether the companies racing to build more powerful AI systems can actually control them. What are the real risks? Who gets to decide what counts as “safe enough”? And what happens when the people building this stuff say they can’t afford to slow down? Learn more about your ad choices. Visit podcastchoices.com/adchoices | 40m 16s | ||||||
| 9/16/26 | AI Wants to Shop for You. What Could Go Wrong? | AI companies have spent years telling us that we’ll be able to use them to go shopping for us, or book us airplane tickets, or get us awesome restaurant reservations. None of that ever materialized.But in the last few weeks, services like Instinct and Meta’s Muse have made that promise feel much less theoretical. Are they actually ready? What’s holding them back? And, crucially: Do we even want them doing this stuff for us? My pal Jason Del Rey, a longtime journalist who now writes The Aisle newsletter, spends all his time learning and thinking about this stuff. We talk about what “agentic shopping” really means, why it’s been harder to build than Silicon Valley expected, and what happens if it finally works: Who wins, who gets cut out, what happens to advertising — and why Amazon may have more to lose than almost anyone. And since you’re here: Channels listeners can start a 30-day free trial of The Aisle here. Or if Jason already sold you, subscribe today. Learn more about your ad choices. Visit podcastchoices.com/adchoices | 40m 52s | ||||||
| 9/11/26 | The Atlantic’s CEO on AI, Billionaire Owners, and Moonlighting as a Creator | Nicholas Thompson runs one of the few media companies that can say things are going pretty well: The Atlantic is profitable, growing, and boasts 1.6 million subscribers.But that's today. What comes next is the bulk of our conversation: Thompson — a big AI guy — tells me what The Atlantic's deal with OpenAI has and hasn't delivered, why he thinks publishers may need to make money from a web increasingly run by bots and agents, and what he thinks his actual human readers want.Also on the docket: What it means to work for a media company owned by billionaire Laurene Powell Jobs; why he’s making his own sponsored videos and podcasts while running a 168-year-old magazine; and what The Atlantic learned from its first attempt at "let's work with Creators strategy" a few years ago. Learn more about your ad choices. Visit podcastchoices.com/adchoices | 54m 00s | ||||||
| 9/2/26 | data centerspolitics+4 | David Weigel | SemaforVox Media Podcast Network | — | data centersElon Musk+4 | — | 53m 20s | ||
| 8/26/26 | microdramasbusiness+4 | Ali AlbazazHernan Lopez | CandyJarInkitt+1 | China | microdramasCandyJar+5 | — | 48m 45s | ||
| 8/19/26 | sports mediaTV rights+4 | John Ourand | PuckFox+7 | — | sports mediaTV rights+7 | — | 42m 41s | ||
| 8/12/26 | AItechnology+4 | Joanna Stern | Wall Street JournalNew Things+2 | — | SiriOpenAI+5 | — | 48m 30s | ||
| 8/5/26 | media businesspaid newsletters+5 | Oliver Darcy | CNNStatus+4 | — | Oliver DarcyStatus+7 | — | 52m 11s | ||
| 7/29/26 | Warner BrosNetflix+5 | Lucas Shaw | Warner Bros. DiscoveryParamount+3 | — | Warner BrosNetflix+6 | — | 44m 16s | ||
| 7/22/26 | newslettersmedia business+4 | Tyler Denk | SubstackBeehiiv+3 | — | SubstackBeehiiv+5 | — | 42m 01s | ||
| 7/15/26 | podcastingcreator economy+4 | Chris Balfe | Red Seat VenturesFox+5 | — | podcastingcreator economy+8 | — | 45m 24s | ||
| 7/8/26 | AIjournalism+4 | Joe Kahn | New York TimesOpenAI | — | New York TimesAI+5 | — | 1h 04m 31s | ||
| 7/1/26 | internet personalitybusiness podcasting+4 | Joe Weisenthal | BloombergBusiness Insider | — | Joe WeisenthalBloomberg+5 | — | 58m 16s | ||
| 6/24/26 | advertisingmedia+4 | Brian Morrissey | OpenAI | Cannes | advertisingmedia brands+5 | — | 29m 21s | ||
| 6/17/26 | entertainmentstreaming+4 | Peter Micelli | Range Media PartnersNetflix+3 | — | Hollywoodstreaming+7 | — | 53m 04s | ||
| 6/10/26 | media industryCBS News+4 | Brian StelterNilay Patel | CBS News60 Minutes+3 | — | Brian StelterNilay Patel+6 | — | 1h 06m 01s | ||
| 6/3/26 | businessvideo production+3 | Dhar Mann | SamsungFox+1 | — | Dhar Mannscripted videos+5 | — | 37m 31s | ||
| 5/27/26 | media businessdata+4 | Almar Latour | Dow JonesThe Wall Street Journal | — | Dow Jonesmedia+6 | — | 46m 45s | ||
| 5/20/26 | media acquisitionpodcast industry+3 | Jim Bankoff | Vox MediaNew York Magazine+1 | — | Vox MediaJames Murdoch+3 | — | 28m 58s | ||
| 5/20/26 | cable industrybusiness strategy+3 | Mark Lazarus | VersantComcast+6 | — | VersantMark Lazarus+6 | — | 40m 25s | ||
| 5/13/26 | AImedia+4 | Roger Lynch | Condé NastGoogle+2 | — | Condé NastRoger Lynch+7 | — | 53m 34s | ||
| 5/6/26 | internet cultureAI+3 | Charlie Warzel | The Atlantic | — | AI slopvideo podcasts+3 | — | 1h 04m 15s | ||
| 4/29/26 | AIcoding+4 | Paul Ford | Claude CodeBusinessweek+2 | — | AI codingsoftware+4 | — | 53m 20s | ||
| 4/22/26 | Hollywoodhorror movies+3 | Jason Blum | Harvard Business ReviewBusiness Insider+3 | — | Jason Blumhorror movies+4 | — | 27m 12s | ||
| 4/13/26 | AI trustOpenAI+3 | Ronan FarrowAndrew Marantz | OpenAINew Yorker | — | Sam AltmanAI+6 | — | 46m 31s | ||
| 4/8/26 | Silicon Valleytelevision+4 | Jonathan Glatzer | AMCSuccession+2 | Silicon ValleyVancouver | Silicon ValleyJonathan Glatzer+5 | — | 41m 45s | ||
| 4/1/26 | Elon MuskSpaceX IPO+4 | Max Chafkin | SpaceXTesla+2 | — | Elon MuskSpaceX+6 | — | 50m 05s | ||
| 3/25/26 | prediction marketsforecasting tools+4 | Kate Knibbs | WIREDKalshi+2 | — | prediction marketsforecasting+7 | — | 45m 54s | ||
| 3/18/26 | Google Zerotraffic decline+4 | Neil Vogel | People Inc.Google+3 | — | Google ZeroPeople Inc.+6 | — | 48m 20s | ||
| 3/11/26 | OscarsHollywood+4 | Matt Belloni | PuckParamount+2 | Hollywood | OscarsHollywood+6 | — | 41m 00s | ||
| 3/4/26 | World Cupsoccer+3 | Roger Bennett | Men in BlazersWe Are the World (Cup) | U.S.Canada+3 | World CupRoger Bennett+6 | — | 40m 28s | ||
| 2/27/26 | media mergersNetflix+5 | Alex Sherman | NetflixWarner Bros. Discovery+3 | — | NetflixParamount+7 | — | 33m 31s | ||
| 2/25/26 | media analysisTrump's influence+4 | Brian Stelter | CNNNetflix+7 | — | TrumpBrian Stelter+6 | — | 49m 39s | ||
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Distribution & Reach
About the show, platforms, and key insights.
Distribution & Reach
About the show, platforms, and key insights.
Vox Media Podcast Network is a prominent media company known for its innovative storytelling and deep dives into culture, technology, and politics. With a portfolio that spans various platforms, they leverage expertise to deliver engaging content across multiple formats. "Channels with Peter Kafka" stands out by exploring the intricate relationship between media and technology through candid, accessible conversations. Kafka, a seasoned journalist, engages industry leaders and innovators, breaking down complex concepts into straightforward insights. The podcast covers a range of topics, including business strategies, media trends, and the evolving landscape of television and film. The podcast appeals to a diverse audience of media professionals, tech enthusiasts, and curious listeners seeking to understand industry dynamics. By providing unfiltered discussions and expert perspectives, it offers valuable knowledge that empowers listeners to navigate the rapidly changing media environment effectively.
By the numbers
- Total followers: 11K
- Total plays: 119K
- Total reviews: 561
Platforms
TuneIn
- Followers: 1.0K
Castbox
- Followers: 8.8K
- Plays: 119K
- Reviews: 11
Podcast App
- Followers: 554
- Reviews: 549
Podcast Republic
- Followers: 777
- Reviews: 1
Find them online
Audience
adults, professionals, general
Key insights
What the show covers
- intersections of media and tech
- interviews with industry leaders
- plain language explanations
- current media landscape discussions
Audience interests
- media industry insights
- technology trends
- business strategies
- film and TV analysis
Platform reach
- part of Vox Media Network
- available on major platforms
- growing listener base
- focused on digital media
Publishing consistency
- weekly or more often
- active for 10 years
- 577 episodes released
- consistent content delivery
Chart history for Channels with Peter Kafka
Peaked at #16 in NG, currently #16 in NG.
| Market | Genre | Peak | Current | Trend |
|---|---|---|---|---|
| NG | — | #16 | #16 | — |
| Brazil | — | #24 | #24 | — |
| AR | — | #26 | #26 | — |
| GR | — | #29 | #29 | — |
| Sweden | — | #32 | #32 | — |
| IL | — | #35 | #35 | — |
| HU | — | #38 | #38 | — |
| AE | — | #38 | #38 | — |
| United States | — | #41 | #41 | — |
| Norway | — | #43 | #43 | — |
| Ireland | — | #44 | #44 | — |
| Denmark | — | #44 | #44 | — |
| CZ | — | #44 | #44 | — |
| South Africa | — | #48 | #48 | — |
| India | — | #50 | #50 | — |
| Germany | — | #53 | #53 | — |
| PL | — | #57 | #57 | — |
| HK | — | #57 | #57 | — |
| PH | — | #64 | #64 | — |
| Finland | — | #66 | #66 | — |
Chart Positions
48 placements across 47 markets.
Chart Positions
48 placements across 47 markets.