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In the latest report, the remaining 1% of attention can include unpublished topics and podcasts with no qualifying discussion.

3 topics highlighted · Sep 28–Oct 4, 2026

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

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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 Cases33.4%Research: Gaining attention in the latest reportResearch22.7%Agents: About the same in the latest reportAgents14.5%Safety & governance: Losing attention in the latest reportSafety & governance8.6%Hardware: Gaining attention in the latest reportHardware7.9%Regulation: About the same in the latest reportRegulation3.9%Open Models: About the same in the latest reportOpen Models3.1%Economics: Losing attention in the latest reportEconomics2.5%Infrastructure: About the same in the latest reportInfrastructure1.2%Jobs: About the same in the latest reportJobs1.2%Other: Below threshold in the latest reportOtherNo measurement

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

Agents · 12.4% · Sep 21–27, 2026 · About the same in the latest report

Agents

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

Sep 21–27, 2026

12.4%Losing attentionDown 2.2 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 21–27, 2026

A closer read

What changed
Its share fell from 14.6% to 12.4%, with evidence across 13 podcasts.
Where it showed up
It appeared in episodes including “AI:AM: What If It Works Too Well? Colluding Agents, $200M Safety Orgs, Virtual Cells Saturate at 2%” and “When AI Research Starts Moving Faster Than Human Research - Zhengyao Jiang”.
How to read it
6 cited episodes from 6 podcasts are shown below. The topic appeared across 13 podcasts in the full analysis.

Podcast moments from the week

9 quoted moments · 6 episodes · 6 podcasts

The Cognitive Revolution

AI:AM: What If It Works Too Well? Colluding Agents, $200M Safety Orgs, Virtual Cells Saturate at 2%

Open episode ↗
  1. H
    “Companies, right? Corporations, uh which are kind of like agentic in a sense, um often um collude through price mechanisms, not explicit communication, but by signaling price in the market, which is in its own way a form of communication. So how does one uh, um prevent that ki...”
    Open episode and seek to 17:13

    ConceptAgents

    Report this moment

Machine Learning Street Talk

When AI Research Starts Moving Faster Than Human Research - Zhengyao Jiang

Open episode ↗
  1. D
    “For example, in Aiden, where we send the agent to attend OpenAI's uh hiring challenge, We found that human is still much better at generating creative primitives.”
    Open episode and seek to 08:37

    ConceptAgents

    Report this moment
  2. D
    “The inner loop agent will only look at the public set, whereas uh the outer loop will look at uh the aggregated score from the private set. So those 2 agents are optimizing at kind of different level of objective.”
    Open episode and seek to 16:05

    ConceptAgents

    Report this moment
  3. G
    “Isn't it a bit like it's cheating that the outer agent has access to the private data?”
    Open episode and seek to 16:51

    ConceptAgents

    Report this moment

No Priors

Re-Founding Incumbents for the AI Era with Sequence Holdings Co-Founder and CEO Michael Lee

Play episode ↗
  1. A
    “helps improve um the speed to which we can deploy, improves agent performance, it improves our build rates”
    Play from 21:26

    ConceptAgents

    Report this moment

Practical AI

From AGENTS.md to Enterprise Deployment

Open episode ↗
  1. C
    “Could you talk a little bit about what that looks like? Kind of paint a picture so that somebody can really get that in their head, uh me first of all, uh about what that multi-agent world looks like when you were doing all these right things that you need to do in the enterpr...”
    Open episode and seek to 17:14

    ConceptAgents

    Report this moment
  2. B
    “When you spin that agent up, does each instance of that, each session have a unique identity? What is the, what's unique about that session and the data that, that is generated by that session versus maybe the things that are always static? Like, I'm not sure if the agent's .m...”
    Open episode and seek to 27:38

    ConceptAgents

    Report this moment
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