The AI conversation, week by week
18 AI-focused podcasts currently tracked18 AI podcasts

Currently tracking18 AI-focused podcasts

  • AI For Humans
  • AI Inside
  • AI Today Podcast
  • Eye on AI
  • Gradient Dissent
  • Interconnects
  • Last Week in AI
  • Latent Space
  • Machine Learning Street Talk
  • Me, Myself, and AI
  • No Priors
  • Practical AI
  • The AI Daily Brief
  • The AI Native Dev
  • The Artificial Intelligence Show
  • The Cognitive Revolution
  • The TWIML AI Podcast
  • Training Data

Trends over time

Jul 13–Oct 4, 2026 · 12 published weeks

In the latest report, the remaining 1% of attention can include unpublished topics and podcasts with no qualifying discussion.

Select a topic or a dated dot to see its history below.

Swipe to follow the full timeline →

Topic attention across published weeksEach colored line uses the same attention scale. Only topics with published measurements are shown; their shares do not necessarily total 100%. Breaks mean missing measurements, not zero. Dated dots open that topic and week below.0%11.3%22.5%33.8%45%Jul 13Jul 20Jul 27Aug 3Aug 10Aug 17Aug 24Aug 31Sep 7Sep 14Sep 21Sep 28Adoption Use Cases: About the same in the latest reportAdoption Use CasesResearch: Gaining attention in the latest reportResearchAgents: About the same in the latest reportAgentsSafety & governance: Losing attention in the latest reportSafety & governanceHardware: Gaining attention in the latest reportHardwareRegulation: About the same in the latest reportRegulationOpen Models: About the same in the latest reportOpen ModelsEconomics: Losing attention in the latest reportEconomicsInfrastructure: About the same in the latest reportInfrastructureJobs: About the same in the latest reportJobsOther: Below threshold in the latest reportOther

Direction compares the latest report with recent weeks; small changes are “About the same,” and gaps mean no measurement.

Agents · 14.5% · Sep 28–Oct 4, 2026 · About the same in the latest report

Agents

AI systems that can plan, use tools, and carry out multi-step tasks.

Sep 28–Oct 4, 2026

14.5%About the sameUp 2.1 percentage points from last week

Choose a week to read the discussion.— Below threshold

Agents, week by weekDated controls show each week's attention share. Gaps mean no qualifying measurement, not zero. Select a week to read its discussion below.0%11.3%22.5%33.8%45%
Show this week’s discussionHide this week’s discussionPodcast moments and context

Agents · Sep 28–Oct 4, 2026

A closer read

What changed
Its share rose from 12.4% to 14.5%, with evidence across 12 podcasts.
Where it showed up
It appeared in episodes including “AI put Minecraft in Skyrim (and OpenAI had a Dev Day)” and “Academia is for Ambition — Alex Zhang, MIT”.
How to read it
6 cited episodes from 6 podcasts are shown below. The topic appeared across 12 podcasts in the full analysis.

Podcast moments from the week

15 quoted moments · 6 episodes · 6 podcasts

AI For Humans

AI put Minecraft in Skyrim (and OpenAI had a Dev Day)

Play episode ↗
  1. B
    “Opus 555 does, to me, feel like a pretty significant step towards AGI, especially after my AI agent Fig made a 27-minute documentary about AI almost entirely on its own. It scripted it, it generated the host, it edited it, it added the music.”
    Play from 01:08

    ConceptAgents

    Report this moment
  2. A
    “2 other agents that I've been testing that are completely free. Completely free and outright awesome”
    Play from 15:04

    ConceptAgents

    Report this moment

Latent Space

Academia is for Ambition — Alex Zhang, MIT

Open episode ↗
  1. A
    “under the hood, whatever is running can be some really weird, complicated swarm of agents that ultimately come up with an answer.”
    Open episode and seek to 1:02:03

    ConceptAgents

    Report this moment
  2. A
    “pointing models, like, or agents at a growing kind of context of information, maybe it's just enough to solve very difficult problems. That um I can buy.”
    Open episode and seek to 1:03:49

    ConceptAgents

    Report this moment
  3. B
    “I think uh one thing I wanted to bring up also was Cursor, as far as like swarm stuff is concerned. This is slightly older, uh meaning February, which is ancient. But if you scroll down all the way to the final sort of multi-agent architecture that they arrived at, it was basically an org chart of a normal software team. One thing I'm thinking about, because basically there's this um uh gather all function that you have to do with subagents, or it's very similar to GPU programming, actually.”
    Open episode and seek to 1:04:49

    ConceptAgents

    Report this moment

Machine Learning Street Talk

How a Voice Agent Learns the Rhythm of Conversation — Shawn Wen

Open episode ↗
  1. B
    “an autonomous agent, when it sees problems, can just fix things”
    Open episode and seek to 46:08

    ConceptAgents

    Report this moment
  2. A
    “we see a lot of success in applying coding agents on top to be able to actually automatically optimize it”
    Open episode and seek to 46:40

    ConceptAgents

    Report this moment
  3. A
    “people started adopting it and started to feel, okay, well, actually agent is actually better than I thought”
    Open episode and seek to 05:31

    ConceptAgents

    Report this moment

The Cognitive Revolution

AI:AM: Was Trump-Xi Anything? What Counts as Utopia? + AWS GPUs Cost 3X & AI Diagnoses Rare Diseases

Open episode ↗
  1. F
    “our job is to take the smartest intelligences in the world and mix them together and give them access to the best tools. and then get answers for our patients”
    Open episode and seek to 1:14:37

    ConceptAgents

    Report this moment

Practical AI

Open models and the future of Physical AI with NVIDIA

Open episode ↗
  1. E
    “I think we like uh agent because agent um is uh somebody has certain autonomy to behave, uh to complete tasks on um behalf of you”
    Open episode and seek to 37:56

    ConceptAgents

    Report this moment
  2. E
    “we got to have specialized agent and there's some agent good at distributing tasks and some agent good at complete tasks and they're going to uh talk together, work together uh to complete the stuff”
    Open episode and seek to 39:19

    ConceptAgents

    Report this moment
  3. E
    “multiple agents working together to complete production uh tasks uh might be decades away, right? So we are not yet there.”
    Open episode and seek to 40:58

    ConceptAgents

    Report this moment

The Artificial Intelligence Show

#244: How Alibaba.com Is Building the Future of Agent-to-Agent Commerce

Play episode ↗
  1. A
    “AI can help a lot. So we believe that the B2B will go to A2A, so agent to agent. That will be the future.”
    Play from 00:00

    ConceptAgents

    Report this moment
  2. A
    “Axio actually uh aggregates all different agents and you can put them in a group helping you to do some kind of deep research”
    Play from 12:23

    ConceptAgents

    Report this moment
  3. A
    “can help you to save a lot of time. And also there are a lot of uh complicated decisions which requires back and forth repetitive work that can be taken care of by an agent”
    Play from 17:11

    ConceptAgents

    Report this moment
Read the full weekly report →

Get the weekly AI conversation

The week’s key ideas and podcast moments, delivered to your inbox.

No account needed. One report a week. Unsubscribe anytime. Privacy

Confirm publication