
Accumulate Bitcoin (BTC) as a foundational long-term store of value, prioritizing self-custody to maintain sovereignty as institutional adoption through ETFs increases liquidity. Consider exposure to the Venice.ai ecosystem via the VVV token, which utilizes a "buy and burn" deflationary mechanism, or the DIEM token, which provides a perpetual $1 daily credit for private AI services. Investors should pivot toward energy infrastructure and power production companies, as energy availability is now the primary bottleneck for scaling AI data centers. Focus on companies leveraging open-source AI models over proprietary ones to benefit from a 90% reduction in operational costs and faster innovation cycles. To hedge against labor displacement, invest in "agentic" AI tools and personal AI literacy to join the high-productivity class of "AI-augmented" professionals.
• Bitcoin is described as the best form of money ever created, fundamentally separating money from the state. • Institutional Adoption: The entry of TradFi (Traditional Finance) and institutions is viewed as an inevitable "Trojan Horse." If TradFi didn't adopt it, the asset would have failed in its march to global ascendancy. • Privacy vs. Traceability: While originally thought to be anonymous, BTC is highly traceable. This is actually seen as a benefit for survival, as it allowed the state to "tolerate" it while it grew, whereas a perfectly private coin might have been snuffed out early. • Machine Economy: BTC is viewed as "alien technology" or natively digital money designed for the coming age of AI agents. Machines handle keys and cryptography natively, solving the user experience hurdles that humans struggle with.
• Long-term Bullishness: The asset is seen as a foundational "anchoring system of value" in a future world that may be massively deflationary due to AI productivity. • Self-Custody is Essential: While custodians (ETFs/Exchanges) bring liquidity, investors must understand and maintain the ability to self-custody to preserve the asset's core value of sovereignty. • Liquidity over Privacy: Increased liquidity from financial institutions makes the asset more useful, even if it sacrifices the "dark money" reputation of its early years.
• Venice.ai is a private, uncensored competitor to ChatGPT that uses blockchain principles to ensure user sovereignty. • Privacy Model: Unlike centralized AI, Venice does not store prompts. It uses a local "vector database" (stored in the user's browser) so the company, and by extension the government, cannot access user thoughts or data. • Model Agnostic: It acts as a "port city," allowing users to access various models (OpenAI, Anthropic, or Open Source) through a privacy-preserving wrapper.
• Tokenomics (VVV): The VVV token is designed with a "buy and burn" mechanism. The company uses its revenue to buy the token from the market and destroy it, theoretically reducing supply as the platform grows. • Tokenomics (DIEM): DIEM acts as a "perpetuity" token, where holding it grants the user $1 per day in credit for Venice AI services. • Investment Theme: This represents a shift from "meme coins" back to "utility tokens" where the token is integrated into a functional consumer product.
• Open source models are rapidly closing the gap with "frontier" models (like those from OpenAI or Google). The lag has shrunk from a year to roughly three months. • Cost Efficiency: Open source models are often 90% cheaper to run than proprietary models for similar levels of intelligence. • Censorship Resistance: Open source is the only way to bypass the "moral filters" and organizational biases imposed by large corporations and governments.
• Commoditization of Intelligence: As open source improves, the "moat" for big AI companies may shrink, leading to a "race to the bottom" in the price of intelligence tokens. • Strategic Advantage: Companies that can leverage open source models efficiently will have a significant cost advantage over those locked into expensive proprietary APIs.
• The "winner" of the AI race may be determined by energy production rather than software. • China vs. USA: China is currently outpacing the US in energy infrastructure (solar and grid build-out), which is a critical "hardware" requirement for scaling AI. • Insight: Look for investment opportunities in energy production and infrastructure that can support massive data center expansion.
• A "stratification of society" is predicted based on AI adoption. • The "Demigod" Class: Individuals and small groups who master AI agents will become "vastly more potent," leading to extreme wealth and capability disparities compared to those who do not use the technology. • Insight: Investment in personal AI literacy and "agentic" tools is viewed as the highest-return activity for individuals.
• The next major frontier is placing AGI (Artificial General Intelligence) brains into robotic bodies. • This creates "Apex" members of society that are faster, stronger, and cheaper than human labor. • Risk Factor: This transition may lead to significant political unrest, shifting the debate from "Capital vs. Labor" to "Accelerationists vs. Decelerationists."
• State Intervention: As AI and Crypto enable more individual sovereignty, expect "mass ignorance" to be amplified through politics, potentially leading to laws that attempt to "steal from those who produce." • Privacy Erosion: The default trend is for data to be warehoused by large corporations. If "privacy by default" is not maintained, the merger of human thought with machine intelligence could lead to a dystopian level of surveillance. • Democracy at Machine Speed: Traditional democratic systems may be too slow to regulate or keep up with intelligence that doubles every few months, leading to a potential breakdown of current political structures.

By @raoulpaltjm
Join me on my journey through macro, crypto and the Exponential Age of technology. The world is changing faster than ever ...