
This podcast was created using BeFreed's AI, based on selected books, the creator's learning goals, and their preferred tone.






Conduct a structured analysis on market crashes and the potential AI bubble in three parts. Part 1: Historical analysis of major crashes (1929, 1973, 1987, 2000, 2008, 2020, 2022) focusing on peak-to-trough, recovery time, and structural warning signs. Part 2: Investor recovery playbook covering behaviors like rebalancing, DCA, and portfolio construction to limit drawdown. Part 3: A mid-2026 assessment of the AI bubble, comparing valuation metrics to the dot-com era, analyzing capex-to-revenue ratios, market concentration, and specific correction triggers like ROI disappointment or credit events.

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From Columbia University alumni built in San Francisco
