| Where do I even begin? Speed is unrealistic. It compresses a decade of enterprise adoption into 18 months. Organizations don't restructure at the speed of a demo. And if it were true, companies would also stop buying AI once their customers are broke and revenue is falling. The "rational firm" logic cuts both ways. "No new jobs" is asserted, not argued. It dismisses 200 years of counter-evidence in two sentences and treats intelligence as one thing when it's really a bundle of very different skills. Ignores the deflationary benefit. If AI makes everything cheaper, the purchasing power of remaining income rises. The article only looks at the income side and never the cost side. Consumption collapse is too fast. It ignores savings buffers, severance, spousal income, and automatic stabilizers. Even 2008 took years to fully hit spending. "Ghost GDP" is wrong. Corporate profits don't vanish. They flow out as dividends, buybacks, investment, and taxes. The distribution changes, but money doesn't disappear from the economy. Overstates the intermediation collapse. People don't optimize purchases like machines. Brand loyalty, identity, and experience aren't just "friction." Stablecoin disruption is fantasy. It ignores KYC/AML rules, consumer protection laws, chargebacks, and the reality of merchant adoption. Assumes zero regulatory response. Governments moved in weeks during COVID. White-collar professionals are politically powerful and vocal. Regulation would arrive fast. |
Assumptions that I think warrant closer inspection:
- agents will always win vs antibot firewalls: highly doubtful given my experience with openclaw. Antibot measures are everywhere, they're advanced, and the more agents threaten legacy business models the harder they'll fight to protect them. Think e.g. Uber investing more in anti-bot tech to stop agents turning them into a whitelabel API. Think CloudFlare's recent moves in this area. Think Salesforce reducing access to Slack API. Data moats will be guarded more strongly.
- total cost of inference will be cheaper than the margin destruction caused by agents: inference is currently heavily subsidized. I have serious doubts "on device" inference will ever be reliable and competitive enough to be viable for running high capability agents (will they even be online enough?). What's the real cost of inference? Does Claude Code really cost $200/month at maximum utilization?
It indeed assumes steady state responses from all incumbents and governments while AI agents move at the speed of innovation. Not sure about that.