Urgent.News

What's breaking now, across thousands of outlets.

Tech

Count transcript tags in a podcast RSS feed

Five of eight AI podcasts in a June 11, 2026 feed audit declared zero transcripts in RSS. Across the 2,148 items those feeds served, 190 carried at least one podcast:transcript tag (8.8%). An absent tag does not establish whether a transcript exists on a website, video platform, or elsewhere. If you ship a feed, or you parse one, count the tag and keep the count inside what a declaration can…

In a June 11, 2026 audit of eight AI podcasts, five of them showed zero transcripts in their RSS feeds. Out of the 2,148 items across these feeds, 190 contained a podcast:transcript tag, representing 8.8% of the total. The absence of a tag does not confirm the existence of a transcript on other platforms. A podcast:transcript tag links to a transcript or captions file, signaling apps and crawlers where the episode's text resides.

The audit focuses on declarations, not verifying the functionality of linked files or the impact on citations and search traffic. The benchmark, conducted on June 11, 2026, reveals that Chain of Thought had the highest transcript coverage at 98.4%, with only its trailer episode lacking a tag. In contrast, AI Engineering Podcast achieved 93.7% coverage, while Practical AI had a significantly lower 15.2%.

The percentages presented in the audit are snapshots of the eight selected shows and do not represent a comprehensive survey of all AI podcasts. A 0% transcription coverage in a feed does not necessarily mean the podcast lacks transcripts; it could mean the transcripts are not declared in the RSS feed. The audit does not validate the availability or quality of the transcripts or their impact on audience reach or AI citations.

Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

Read the original at dev.to →

More in Tech

Ghost in the Machine

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine What I Built TouchGrass AI is a purpose-built micro-expedition application designed around one strict…

Rutba Vision: video surveillance for camera networks past the size one recorder copes with

First published on rutba.io . A handful of cameras is a product you buy. A hundred and fifty, writing terabytes a day, is an operations problem, and it fails the same ways each time.

  • Rutba Vision handles large camera networks without single recorder limitations
  • Software runs node agents on all machines for edge, analysis, and core roles
  • Footage recorded in self-contained fMP4 segments with SHA-256 hashing

The Measurement I Kept Skipping

For months my test notes had a gap I could not see: I always measured the device at the moment it looked most interesting.

  • Fixed mark used 12 minutes after each scene ends
  • Notes became less dramatic and more reliable
  • Battery drain explained with consistent measurements

More from Saturday 31 October →