Nish killed me in the trading competition and could not stop gloating. Very poor winner.

Summary

News and macro discussion

The episode begins with a breakdown of the biggest story in tech: Mark Zuckerberg’s billion-dollar attempt to poach AI talent from his competitors: Human Machines Lab (Mira Murati), OpenAI and Anthropic. Nish and Frackers discuss how Zuckerberg’s superintelligence memo was inspired by, if not copied, from a character.ai memo from several years ago.

They reflect on how investors reward execution and momentum over originality or ethics. Other headlines include strong earnings by Apple and Microsoft and Amazon’s weak AWS numbers. In crypto, the CoinDCX hack is revealed to be an insider job involving $44 million in stolen assets, with on-chain sleuth ZachXBT helping expose it. The SEC’s “Project Crypto” is also discussed as a potential shift toward lighter regulation, although the lack of clarity left markets unmoved.

Market commentary and token picks

The middle segment covers how traditional markets and crypto reacted to this mix of strong earnings and regulatory uncertainty. Michiel points out that Ethereum still hasn’t broken its previous all-time high, which he sees as a signal of weakness despite increased buying from large entities like Ether Machine. Nish notes Tether’s reported $4.9 billion profit in Q2, noting that the figure is unaudited.

Trading challenge and portfolio results

In the final part of the episode, Nish and Michiel reveal the results of their increasingly competitive trading competition. Nish went full degen, flipping $30 into $240 on the AIR token before swapping into another meme coin called A$$ and ending at $135. He describes the emotional rollercoaster of near-instant profits followed by losses, calling it a full round-trip. Michiel took a more conservative approach, sticking with a mix of Nvidia, Broadcom and Bitcoin, and ended the week with a 17 percent gain since the start of the competition in early June. They compare strategies, risk tolerance and the psychology of trading in volatile markets. The segment ends with reflections on why most traders underperform even during bull markets, and a reminder by Nish that the challenge is about learning, not outperforming each other. Michiel is not buying it.

Chapter list

00:00 – Intro and episode preview

Overview of topics including Meta, CoinDCX hack, SEC regulation and the trading competition

01:30 – Zuckerberg’s $1B AI poaching strategy

Discussion on Meta offering $5 to $10 million per engineer and the ethics behind it

04:00 – Meta’s plagiarized superintelligence memo

Breakdown of Zuck memo’s similarities to character.ai and what it reveals about Meta culture

06:20 – Big Tech earnings and market reactions

Apple, Amazon and Microsoft results and how the market is responding

08:10 – Circle and Figma IPO chatter

Comments on IPO valuations and investor psychology

09:30 – CoinDCX hack and insider involvement

How $44 million was drained from an Indian exchange by insiders, and how ZachXBT helped trace it

12:00 – SEC’s “Project Crypto” grace period

Discussion on a possible regulatory shift and its unclear impact on token markets

14:30 – Ethereum’s weak price action despite good news

Why ETH still hasn’t hit a new ATH and what that means for investor confidence

17:00 – Tether’s $4.9B quarterly profit

Questions around how Tether generates its profit and whether it’s sustainable or lega

20:00 – Trading competition recap begins

Nish explains how he turned $30 into $240 and then back to $135 using AIR and A$$

23:00 – Michiel’s conservative portfolio performance

Breakdown of a 17 percent gain using Bitcoin and equities

25:00 – Risk and psychology in crypto investing

Reflections on emotional discipline and portfolio math

27:30 – Outro and next episode preview

Wrap-up, lessons learned and what’s coming next week

Key learnings

Meta’s AI strategy relies on money over innovation

Insider risk remains a major vulnerability for crypto exchanges

SEC guidance is ambiguous and may shift investor behavior

Ethereum underperformance raises questions about narrative strength

Degenerate trading can outperform but carries emotional cost

Portfolio math needs constant double-checking

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