Creating liquidity in private markets is not about better tech like blockchain. The core challenge is one of market structure: finding a buyer when everyone wants to sell. Without a mechanism to provide a capital backstop during liquidity shocks, technology alone cannot create a functional secondary market.

Today's market structure, dominated by High-Frequency Trading (HFT) firms, is inherently fragile. HFTs provide liquidity during calm periods but are incentivized to withdraw it during stress, creating "liquidity voids." This amplifies price dislocations and increases systemic risk, making large-cap concentration more dangerous than it appears.

When major infrastructure like AWS or Cloudflare goes down, it affects many companies simultaneously. This creates a collective "mulligan," meaning individual startups aren't heavily penalized by users for the downtime, as the issue is widespread. The exception is for mission-critical services like finance or live events.

Blockchain's disruption will not impact all of finance equally. Trading firms are safe because market making is a fundamental need. However, intermediaries like banks, exchanges, and custodians face an existential threat as their core function—managing ledgers and access—is directly replaced by blockchain's "private key and a ledger" infrastructure.

Building features like custom commands and sub-agents can look like reliable, deterministic workflows. However, because they are built on non-deterministic LLMs, they fail unpredictably. This misleads users into trusting a fragile abstraction and ultimately results in a poor experience.

High-frequency trading (HFT) firms use proprietary exchange data feeds to legally front-run retail and institutional orders. This systemic disadvantage erodes investor confidence, pushing them toward high-risk YOLO call options and sports betting to seek returns.

The primary reason multi-million dollar AI initiatives stall or fail is not the sophistication of the models, but the underlying data layer. Traditional data infrastructure creates delays in moving and duplicating information, preventing the real-time, comprehensive data access required for AI to deliver business value. The focus on algorithms misses this foundational roadblock.

Unlike the cloud market with high switching costs, LLM workloads can be moved between providers with a single line of code. This creates insane market dynamics where millions in spend can shift overnight based on model performance or cost, posing a huge risk to the LLM providers themselves.

While Exchange-Traded Products (ETPs) make crypto accessible, they present a liquidity paradox. The underlying spot crypto markets are actually more liquid and trade 24/7 globally, whereas ETFs are confined to standard market hours—a crucial difference for active traders.