TBPN Podcast Summary

Episode: Why My Article Just Tanked the Market
Hosts: John Coogan & Jordi Hays
Guest: Ayla (Tech founding operator and investor, author of influential market-moving article)
Date: February 23, 2026

Episode Overview

This episode dives into the fallout from Ayla's recently published article, which triggered a notable downturn in the public markets by sounding the alarm on the looming impact of AI—particularly agentic coding—on white collar jobs, corporate structures, and broader economic stability. The hosts and Ayla dissect the market's reaction, the thesis behind the article, its macroeconomic implications, tech industry analogs from the past, and possible future outcomes, including policy and societal responses.

Key Topics & Insights

1. Genesis and Motivation of the Article

• Ayla's Background: 15 years in AI, 20 years as an investor.
• Catalyst: Realizing personally and within her teams how agentic coding (AI performing complex automations) has sharply increased productivity and potentially eliminates layers of white collar work.
• Market Lag: Highlights that startups see this first, but large corporations are only a year or two behind—and waves of change are imminent.
• Quote:

  "I've been building in AI for 15 years … especially the last six months, as I've just been using agentic coding myself and my teams have adopted it, it's just been a step change function in how much we can get done." — Ayla (00:39)

2. Labor Market Impacts & Macro Risks

• White Collar Decline: Noted information sector jobs are already down 8% since 2022, even before full AI rollout.
• Systemic Risks: White collar wages drive discretionary spending and underpin loans, mortgages, and the broader economy. Rapid job losses could spark contagion affecting all asset classes.
• Acceleration: If white collar job loss is ~2% per year, the economy can absorb; at 4-5%, urgent action is needed.
• Quote:

  "White collar economy is our economy. If you all of a sudden just take a leg out of that economy, it has a contagion effect into basically every asset in the world." — Ayla (03:09)

3. Tech Industry Narratives & Historical Analogies

• Comparison to 1990s-2000s predictions around the internet (e.g., “bricks to clicks”, frictionless capitalism, media disintermediation).
• Acknowledgement that while many predictions were directionally accurate, timing and required tech capabilities (like sophisticated AI) only matured recently.
• Quote:

  "Most of the predictions...couldn't really happen until you had proper AI... We only have gotten to kind of the tech required for those predictions I think this year." — Ayla (08:43)

4. Global Effects & Outsourcing

• Question of whether employment impacts will be felt first in AI-outsourcing nations (India, Philippines).
• Insight: Early impact localized to mature economies (like the US) due to higher concentration of white collar jobs; consulting/outsourcing firms may see a short-term bump but are vulnerable longer term.
• Quote:

  "White collar work is a lot more of our economy than it is the economy of India and the Philippines...I think those businesses are likely going to be in a lot of trouble over the medium term." — Ayla (10:20)

5. Moats & Business Model Durability in an Agentic World

• Analysis of business moats in the face of AI agents:
  • Brand Value: Still strong.
  • Network Effects: More powerful for true platforms (Meta), but aggregators like DoorDash/Uber more at risk.
  • Disruption of Aggregators: Agents can shop/prefer lower-cost alternatives, eroding customer lock-in advantages.
• DoorDash/Uber Example: Customer lock-in is threatened if AI agents route orders to lowest-cost providers (potentially bypassing current dominant platforms).
• Supply Side as a Bottleneck: Hosts push back, noting logistical and driver aggregation is the harder problem—Ayla counters with growth of third-party supply networks.
• Quotes:

  "The real lock in...is the customer lock in...Agents are happy to price shop as much as possible. And so if you take that away, then it's a real problem for businesses that are ultimately built on customer lock in." — Ayla (13:54)
  "I think there are a lot more of these [driver supply] businesses. All those businesses now will also just have huge opportunities to kind of take market share." — Ayla (17:42)

6. AI Winners & Public vs. Private Markets

• Labs' Positioning: Big AI labs (Anthropic, OpenAI) are major indirect beneficiaries, not yet public.
• Market Dynamics: Selloffs in public tech companies funnel capital towards the labs, but slowly due to private market structures.
• Google’s Unique Position: Has resources and customer base to withstand pressures, but ultimately, Ayla suggests hardware and semiconductor providers may be the biggest winners.
• Quote:

  "There's no way [labs] won't be the hugest winners here... but the absolute hugest winners are going to be the underlying tech, meaning the semiconductors." — Ayla (20:03)

7. Policy, Solutions, and the "Marxist" Critique

• Discussion of critiques labeling the analysis as "Marxist"—Ayla acknowledges the dynamic but emphasizes the political layer and the need for redistribution as AI-driven productivity surges.
• Suggestion that "creative destruction" will yield new industries, but only if policy structures ensure displaced workers benefit from productivity gains.
• Taxation & Redistribution: Possible evolution towards European/French levels of government spending & tax; the real question is the size and division of a much larger economic "pie."
• Quotes:

  "Marxist can also mean just understanding how capital and labor interact. In that sense, yes, it is Marxist... Progress will slow down [otherwise] because we'll have an economic crisis." — Ayla (22:11)
  "[If] done properly, [GDP] can just increase multiples of what it is today and thus it's just a win-win." — Ayla (24:01)

8. AI Lab Leaders & Public Messaging

• Hosts note lab executives have flagged job loss risks but seldom advocate policy solutions (e.g., UBI, unemployment insurance) in public.
• Ayla: Leaders are cautious about making specific calls—public messaging about solutions may be politically or reputationally sensitive, so it falls to independent thinkers to drive the discussion.
• Quote:

  "They can't go so far as to say...this is how it's going to play out. I think it's too sort of damaging to their reputations." — Ayla (25:39)

9. Industries and Jobs of the Future

• Leisure & Services Boom: If the right economic adjustments are made, sectors related to leisure, lifestyle, and entertainment could experience explosive growth.
• High-Agency Workers: Across sectors, individuals who can wield advanced tools will be able to do the work of many—a central theme for the evolving labor landscape.
• Quote:

  "Everything related to sort of leisure is going to absolutely zoom and those are going to be the biggest growth industries of the future." — Ayla (27:43)

10. Reindustrialization and Real Economy Jobs

• Hosts ask: Will displaced tech/white collar workers move into infrastructure and hardware, thanks to national policy shifts?
• Ayla: The US is making progress, but is still lagging China in industrial growth. AI will also hit these sectors; real opportunity lies in those with high agency and tool fluency.
• Quote:

  "...the ultimate thing we're seeing with AI period is just high agency. People who really know how to use the tools can just do the work of many, many people. And I think that trend applies in every industry." — Ayla (29:12)

Notable Quotes & Memorable Moments

• On triggering a global sell-off:

  "Is this your first time triggering a global sell off?" — Jordi (00:09)
  "The first time so far. But, you know, I'm just the messenger." — Ayla (00:16)

• On the nature of modern technology disruption:

  "We only have gotten to kind of the tech required for those predictions I think this year. And that's why this is the year that I think it really begins." — Ayla (08:43)

• On AI and societal adaptation:

  "We have to structure our society such that as those things happen very, you know, hopefully very slowly...we do the right thing from a taxation perspective to say the winners should win. But, you know, if that's what's causing the displacement, let's sort of make the pie a little bit bigger for everyone." — Ayla (22:11)

Timestamps for Key Segments

• [00:39] – Ayla explains motivation behind the article and early warnings about agentic AI impact.
• [03:09] – Discussion of labor market risks from sudden white collar decline.
• [06:23] – Hosts recount past overblown predictions during the Internet era as context.
• [08:43] – Ayla outlines why this tech wave is fundamentally different.
• [11:54] – Deep dive on business moats: Why DoorDash & Uber face new threats from agentic AI.
• [20:03] – Speculation about AI labs, public vs. private markets, and which sectors are poised to benefit.
• [22:11] – Ayla explains the accusation of Marxism and clarifies the need for political/economic adaptation.
• [25:39] – On why AI lab leaders avoid detailed policy solutions in public messaging.
• [27:43] – Predictions for new growth industries in an AI-accelerated, post-work world.
• [29:12] – Can “re-industrialization” absorb displaced tech talent? Ayla's skepticism and optimism.

Final Thoughts

The episode offers a candid, critical, and forward-looking analysis of the tremors shaking both the tech sector and the wider economy as AI adoption accelerates. While much remains uncertain—including precisely what new policies or jobs may emerge—there's a clear call for proactive discussion, policy innovation, and societal adaptation in the face of technological disruption. Ayla's warnings and projections have already had consequences, but the hope is that more robust debate, and ultimately constructive solutions, will follow.