Top Podcasts on AI Agents & Workforce Changes

“Agendic AI is powering a $3 trillion productivity revolution, and leaders are hitting a real decision point. Do you build your own AI agents, buy off the shelf, or borrow by partnering to scale faster? KPMG's latest thought leadership paper...does a great job cutting through the noise with a practical framework to help you choose based on value, risk, and readiness.”

“One of the things that makes AI so interesting is that it breaks the trend of the last couple hundred years where new technology changes tended to hit blue collar workers first, at least the negative side. Right now what we're seeing is that the places where the most realized disruption is happening is in fact in white collar roles. The way that people think about programmers themselves, for example, is changing.”

“"It does seem clear to me from some conversations that at least in part AI has been a handy pretext for job cuts... That doesn't look like weakening demand. That looks like innovation... I'm seeing a lot of excitement across my industry... But again, you still need a senior programmer... I'm not only concerned that the kind of rapid outsourcing of some of the development work to agents, I think some of that could backfire in a kind of technical debt."”

“The entire life cycle, emergence, hype, enormous salaries, democratization, obsolescence took roughly two years. AI coding agents are already demonstrating the ability to handle orchestration tasks autonomously. Claude. Code resolves 72% of medium complexity GitHub issues in under eight minutes. Devin handles planning to deployment cycles end to end and is being piloted at Goldman Sachs alongside 12,000 human developers.”

“Entry-level roles look particularly exposed because they tend to involve narrower task bundles, those bundles we were talking about earlier, with fewer edge cases requiring human discretion. Back office and clerical work is clearly shrinking. The share of Americans in clerical and admin work has already dropped from 18% in the 1980s to 10%, and that trajectory is accelerating. New research...suggests that clerical workers have the weakest capacity to adapt with fewer transferable skills and less scope to move into higher-value work.”

“"Fortune 500 leaders are unlocking 5x engineering velocity and delivering months of engineering work in a matter of days with Blitzy. Transform the way you develop software. Discover how at blitzy.com. That's B-L-I-T-Z-Y dot com. There's a new standard that I think is going to matter a lot for the enterprise AI agent space. It's called AIUC1, and it builds itself as the world's first AI agent standard."”

“"You tweeted yesterday about a DevOps engineer that you launched that would typically cost $200,000, but you have it running autonomously 24-7. What's going on? Yeah, I don't know what's going on. that I strongly believe that no one does where we're heading. And it really feels like everything that we doing right now is something that hasn been done before."”

“CEOs and CFOs might be salivating at the idea of AI agents boosting productivity and profit margins, but there's a growing wave of anxiety about what this all means for everyday workers. In fact, we're already starting to see that AI might be impacting entry-level jobs. The unemployment rate for recent college graduates is 5.6%. And if you broaden that out and look at the unemployment rate for younger workers between the age of 22 and 27, that's at 7.8%.”

“I'm mad at Amazon for laying off 16 people and blaming AI without an AI strategy... everybody has a dial that they get to turn from zero to 100... we're going to lose about half the engineers from big companies, which is scary. But at the same time, something else is happening, which is AI is enabling non-programmers to write code... we've got this mad rush of innovation coming up, bottom up.”

“Now, as we always point out, not everyone is convinced that all of these layoffs being announced are actually about AI. Before these cuts at Atlassian were announced, Buko Capital wrote on Twitter, cash flows minus stock compensation. And the math simply doesn't math. Two, many of these companies staffed up during COVID and never actually took their medicine and got fit. They thought demand would come back, and it mostly hasn't, not in the same way.”

“Gartner projects 38% of organizations will have AI agents as formal team members by 2028. Multi-agent coordination becomes the default architecture. Instead of one big agent, systems will coordinate multiple specialized agents, a researcher, a writer, a fact checker, a designer. Google DeepMind's research shows multi-agent systems can perform 80% better than single agents on parallelizable tasks. And here's the boldest prediction. By 2028, the median knowledge worker will spend more time directing agents than performing tasks directly.”

“"AI is very good at is sifting through gargantuan datasets... those are the kinds of things that regular electricians would have to work decades to get the experience in an imperfect way. So we can significantly improve what electricians, what nurses, what educators, what journalists, what academics could do using AI... that's not the direction in which AI is being developed."”

“Six months ago, I was quite certain that AI was a bubble. And I was certain for the very simple reason that I thought history was just repeating itself. AI spending was rising faster, I thought, than revenue could possibly match it. But in the last few weeks, I've changed my mind. And I want to be very, very clear about what happened that changed it. In late 2025, the AI companies Anthropic and OpenAI released new agents.”

“The history of technology, even exceptionally powerful general-purpose technology, tells us that as long as you are trying to fit capital into labor-shaped holes, you will find yourself confronted by endless frictions. Just as with electricity, the productivity inherent in any technology is unleashed only when you figure out how to organize work around it, rather than slotting it into what already exists.”

“You don't write code. You talk to an agent, and it goes and does it for you, and you maybe at best review it. And that's even probably largely not even what you're doing. What's happening is we are changing our work to make the agents effective in that model. The agent didn't really adapt to how we work. We basically adapted to how the agent works.”

“The report measures AI exposure, which doesn't necessarily imply replacement, but rather the evolution of job roles. What your job looks like today is very much going to look very different a few years from now. If you see your job here, that's okay. We're going to walk through a bunch of categories about what is most affected, what is least affected, and I guess kind of the impact that AI is going to have.”

“So in this case, though, the problem is we're automating the specific faculty that allows humans to adapt to new jobs. And so really, I mean, we've seen AI systems go from, you know, whatever, like junior high schooler abilities and math and shit to now they're solving unsolved theorems. And that happened in like three years. So they're learning faster. They're just outpacing our ability to adapt.”

“"Daron explains that it's not as cut and dry as just robots steal jobs. Because there are really two forces at play here. Two effects that are both vying for dominance... Robots can also make jobs or complement existing jobs. Once workers are displaced from the tasks that robots can now do, they can go and do other things."”

“Agentic AI is powering a $3 trillion productivity revolution, and leaders are hitting a real decision point. Do you build your own AI agents, buy off the shelf, or borrow by partnering to scale faster? Most companies don't struggle with ideas. They struggle with turning them into real AI systems that deliver value.”

“You can think of this as kind of like a shift from like humans as the orchestrators to, or generally like it's shifting from agentic orchestration to an infrastructure place. So instead of just like initiating what you doing is you being as they put it called in at the right points in the conveyor belt right So you kind of just your attention is being drawn to specific moments in the workflow where there a human inject that really required which makes this a pretty different mental model from what software development has looked like even in the AI augmented age.”