Describes his origin story: demoralized by fraud in microcaps post-dot-com bust, went to law school, started a business in China, and stumbled into short selling by exposing Orient Paper.

His father's anecdote about the Chinese chairman not smoking or chasing women signaled an attempt to game Western investor psychology, sparking his investigation.

Posits an inverse relationship between interest rates and dishonesty in society. Low rates and easy money have anesthetized investors to risk, pushing fraudulent/gray-zone behavior from micro-caps into mid-caps.

The 'gray zone' of legal but economically misleading behavior is now perhaps the norm.

1) There are easier shorts than Nvidia. 2) Flows (passive bid) squeeze floats, creating parabolic technical value beyond fundamental value. 3) His view has '180ed' in the past month. The right question isn't about valuations, but what will happen to society and markets as a result of AI.

He now refers to LLMs as AI, a shift from a month ago when he insisted they were just information processors.

Points to private credit, citing opacity and alarming anecdotes: sloppy securitization practices, lack of loan performance tracking by CLO managers, and allocators' uniform focus on the asset class.

Compares the 'private credit' buzz to the internet bubble: 'too much money chasing too few investable companies.' Connects this to potential AI job displacement risks.

Explicitly states his AI/job loss thesis: 'I think it's not unrealistic to say 15% of knowledge work jobs in the US in 3 years are gone. And if it's not three, it's going to be five. But it might not be 15, it could be 20, 25%.'

Links this to his broader market fear: job losses lead to 401k redemptions, which reverse passive flows.

AI (Claude) helps with communication and drafting, eroding his former edge in writing. It's less clear if it helps with initial fraud detection, which still requires legwork to obtain obscure documents.

Notes AI can help connect dots across many entities, a task previously reliant on memory.

The catalyst is the reversal of passive flows, specifically from target-date 401k funds. Cites Mike Green's prophecy that when flows taper and turn to outflows, it could cause a '1929 magnitude crash.'

Explicitly connects his AI job loss thesis to this catalyst: laid-off knowledge workers will stop contributing to, then withdraw from, their 401ks, triggering the outflow. States he was 'completely sanguine' five weeks ago but has now '180ed.'

The hyperscalers that benefit from AI are in the index and will be hurt by index outflows. Instead, he is creating 'highly convex trades,' primarily by 'shorting credit' because 'credit spreads are stupidly tight and credit vol is stupidly low.'

Seeks to cap potential loss while betting on a credit dislocation.