Show notes for every episode, with timestamps

Many podcasts are on YouTube, and YouTube already has the transcript. Pull it with the timed segments and let your AI write show notes, chapter markers and guest quotes. The sample is a real transcript of a three-hour Lex Fridman episode with Andrej Karpathy.

In the sample · recorded October 21, 2026

Video length
3 h 29 min
Words in the transcript
39,509
Words per minute
189
Timed segments
1,966
Chapters
31

Counted from the 1 result of one real run below. They describe this sample, not the whole market.

Podcast show notes

Why it works.

Writing show notes by hand means listening to the whole episode again. With the transcript and timestamps, your AI can draft them for you: topics with their start time, the best quotes, and the books and people that were mentioned.

Long episodes are where this pays off most. A three-hour conversation is hard to navigate without chapters, and the timed segments let your AI place every topic exactly.

Who uses it

  • Podcast hosts and producers
  • Agencies that edit and publish shows
  • Listeners who keep notes on long episodes

Real sample

What the tool returned.

Recorded October 21, 2026SAMPLE · REAL RUN, SHORTENED

Transcript of “Andrej Karpathy: Tesla AI, Self-Driving, Optimus, Aliens, and AGI | Lex Fridman Podcast #333” by Lex Fridman.

Andrej Karpathy: Tesla AI, Self-Driving, Optimus, Aliens, and AGI | Lex Fridman Podcast #333

Lex Fridman

  • 0:00- I think it's possible that physics has exploits and we should be trying to find them.
  • 0:03Arranging some kind of a crazy quantum mechanical system that somehow gives you buffer overflow, somehow gives you a rounding error in the floating point.
  • 0:10Synthetic intelligence is kind of like the next stage of development.
  • 0:15And I dunno where it leads to, at some point I suspect the universe is some kind of a puzzle.
  • 0:23These synthetic AIs will uncover that puzzle and solve it.
  • 0:30- The following is a conversation with Andrej Karpathy, previously the director of AI at Tesla. And before that, at OpenAi and Stanford.
  • 0:39He is one of the greatest scientists, engineers, and educators in the history of artificial intelligence.
  • 0:47This is the Lex Fridman Podcast. To support it, please check out our sponsors. And now, dear friends, here's Andrej Karpathy.

Chapters

  • 0:00Chapter 1: Introduction
  • 0:58Chapter 2: Neural networks
  • 6:01Chapter 3: Biology
  • 11:32Chapter 4: Aliens
  • 21:43Chapter 5: Universe
  • 33:34Chapter 6: Transformers
  • 41:50Chapter 7: Language models
  • 52:01Chapter 8: Bots
  • 58:21Chapter 9: Google's LaMDA
  • 1:05:44Chapter 10: Software 2.0
  • 1:16:44Chapter 11: Human annotation
  • 1:18:41Chapter 12: Camera vision
Input and raw JSON

The request body we sent. Long texts and lists in the result are shortened for this page.

{
  "videos": [
    "https://www.youtube.com/watch?v=cdiD-9MMpb0"
  ]
}
{
  "videoId": "cdiD-9MMpb0",
  "url": "https://www.youtube.com/watch?v=cdiD-9MMpb0",
  "title": "Andrej Karpathy: Tesla AI, Self-Driving, Optimus, Aliens, and AGI | Lex Fridman Podcast #333",
  "channelName": "Lex Fridman",
  "channelUrl": "https://www.youtube.com/@lexfridman",
  "durationSeconds": 12518,
  "language": null,
  "languageMatched": true,
  "text": "- I think it's possible that physics has exploits and we should be trying to find them. Arranging some kind of a crazy quantum mechanical system that somehow gives you buffer overflow, somehow gives you a rounding error in the floating point. Synthetic intelligence is kind of like the next stage of development. And I dunno where it leads to, at some point I suspect the universe is some kind of a puzzle. These synthetic AIs will uncover that puzzle and solve it. - The following is a conversation with Andrej Karpathy, previously the director of AI at Tesla. And before that, at OpenAi and Stanford. He is one of the greatest scientists, engineers, and educators in the history of artificial intelligence. This is the Lex Fridman Podcast. To support it, please check out our sponsors. And now, dea…",
  "wordCount": 39509,
  "segments": [
    {
      "start": 0,
      "end": 3.6,
      "text": "- I think it's possible that physics has exploits and we should be trying to find them."
    },
    {
      "start": 3,
      "end": 10.77,
      "text": "Arranging some kind of a crazy quantum mechanical system that somehow gives you buffer overflow, somehow gives you a rounding error in the floating point."
    },
    {
      "start": 10,
      "end": 15.36,
      "text": "Synthetic intelligence is kind of like the next stage of development."
    },
    {
      "start": 15,
      "end": 23.16,
      "text": "And I dunno where it leads to, at some point I suspect the universe is some kind of a puzzle."
    },
    {
      "start": 23,
      "end": 27.663,
      "text": "These synthetic AIs will uncover that puzzle and solve it."
    },
    {
      "start": 30,
      "end": 39.87,
      "text": "- The following is a conversation with Andrej Karpathy, previously the director of AI at Tesla. And before that, at OpenAi and Stanford."
    },
    {
      "start": 39,
      "end": 47.85,
      "text": "He is one of the greatest scientists, engineers, and educators in the history of artificial intelligence."
    },
    {
      "start": 47,
      "end": 57.123,
      "text": "This is the Lex Fridman Podcast. To support it, please check out our sponsors. And now, dear friends, here's Andrej Karpathy."
    },
    {
      "start": 58,
      "end": 65.46,
      "text": "What is a neural network and why does it seem to do such a surprisingly good job of learning? - What is a neural network?"
    },
    {
      "start": 65,
      "end": 72.72,
      "text": "It's a mathematical abstraction of the brain. I would say that's how it was originally developed."
    },
    {
      "start": 72,
      "end": 77.43,
      "text": "At the end of the day, it's a mathematical expression and it's a fairly simple mathematical expression when you get down to it."
    },
    {
      "start": 77,
      "end": 85.652,
      "text": "It's basically a sequence of meter multipliers, whichever really dot products mathematically and some nonlinearity is thrown in."
    }
  ],
  "chapters": [
    {
      "title": "Chapter 1: Introduction",
      "start": 0
    },
    {
      "title": "Chapter 2: Neural networks",
      "start": 58
    },
    {
      "title": "Chapter 3: Biology",
      "start": 361
    },
    {
      "title": "Chapter 4: Aliens",
      "start": 692
    },
    {
      "title": "Chapter 5: Universe",
      "start": 1303
    },
    {
      "title": "Chapter 6: Transformers",
      "start": 2014
    },
    {
      "title": "Chapter 7: Language models",
      "start": 2510
    },
    {
      "title": "Chapter 8: Bots",
      "start": 3121
    },
    {
      "title": "Chapter 9: Google's LaMDA",
      "start": 3501
    },
    {
      "title": "Chapter 10: Software 2.0",
      "start": 3944
    },
    {
      "title": "Chapter 11: Human annotation",
      "start": 4604
    },
    {
      "title": "Chapter 12: Camera vision",
      "start": 4721
    }
  ],
  "scrapedAt": "2026-10-21T06:31:40.512Z"
}

The fields that matter

What to look at first.

FieldWhy it matters hereIn the sample
SegmentssegmentsEvery line with its time, to build chapter markers.1,966 entries
TexttextThe whole conversation for your AI.- I think it's possible that physics has exploits and we should be tr…
ChapterschaptersExisting chapters, if the uploader set them.31 entries
DurationdurationSecondsEpisode length.3 h 29 min

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