The narrative of venture capital cycles has shifted from simple exit strategies to complex structural harmonics, particularly for Solo General Partners. In 2021, A16Z returned $12.5 billion in profits to Limited Partners, achieving a Distribution to Paid-In capital ratio exceeding the sum of the previous decade. Yet this peak marked the onset of a prolonged downturn for the U.S. venture industry, where tangible returns gave way to paper gains. The volatility of the crypto market synchronized with this divergence, as the Metaverse narrative in 2022 artificially extended the bull market until early 2025, when the Binance 'BFF Coin' farce effectively terminated the VC coin era. Today, many funds remain silent, trapped in heavy capital models involving computing power and data that prevent break-even, while others retreat to institutionalization relying on SaaS channel fees. Woofun AI notes that historical interest rate cycles invariably nurture distinct VC models, suggesting that the relative freedom of the crypto market allows savvy players to identify profitable signaling mechanisms that traditional giants miss.

In March and April 2021, Roblox and Coinbase utilized Direct Listings, bypassing traditional IPO underwriters and lock-up periods, a strategy championed by A16Z. Amidst these dazzling returns, A16Z raised $22 billion for its third crypto fund in June 2021, followed by a staggering $90 billion for a new fund in January 2022. The cost of this scale became evident as Coinbase's stock price plummeted 90% from its peak in 2023. Despite this, A16Z continued to raise capital, securing $7.2 billion in 2024 and $15.1 billion in 2026, with its fifth crypto fund exceeding $22 billion by May 2026, bringing its total crypto fund history near $100 billion. This trajectory highlights a critical paradox: while A16Z acts as a market indicator, its massive scale hinders the discovery of super early-stage paradigms, creating a curse of scale that prevents the identification of revolutionary rather than incremental mechanisms.

The evolution of venture capital reveals a pattern where old titans bask in past glory while new players leverage innovative mechanisms. Arthur Rock pioneered the model with Fairchild and Intel, followed by Sequoia's institutionalization, which was later overtaken during the PC-to-mobile transition. Y Combinator transformed VC into a probabilistic system under Big Data, while Masayoshi Son's SoftBank turned it into a massive-scale game. As these giants struggle, new ambitious players like Paradigm, led by Matt Huang, pivot from failed public listings in sectors like ByteDance to crypto, AI, and robotics. Woofun AI analysis suggests that reputation can be converted back into capital, but the gap lies in discovering unscaled new signals to challenge the old guard, as seen when A16Z was excluded from Anthropic's funding round in favor of individual investors like Jaan Tallinn and Eric Schmidt.

Solo General Partners operate on a fundamentally different logic than institutional giants, relying entirely on research ability rather than wide-net approaches. In the age of Agents, this human-centric model proves crucial, as each deal is vital to DPI. Unlike Y Combinator's broad strategy, Solo GPs deeply invest in specific projects, positioning themselves to act slightly ahead of A16Z as new trends emerge. The focus has shifted beyond large models to Agents, yet a dangerous leap exists: economies of scale do not apply to AI large models where server costs rise with every user, preventing the cost spreading seen in software. The network effect in Agents remains an ideal state, with interaction between Agents still theoretical. Woofun AI observes that AI remains a black box, where the math for Transformers is accessible, yet the underlying reasons for their superiority remain unknown, making it a domain for cutting-edge researchers rather than broad scaling.

The economic reality of AI large models dictates that they must become traffic centers like AWS or CloudFlare, as production-side costs cannot be reduced without unlimited consumer-side growth. Agents represent the opportunity for money, requiring them to become the consumer subject with infinite consumption potential. This drives the mainstream topic of Agents calling each other, though the distinction between Agents and Bots remains blurred. The 'evaluative agent' in reinforcement learning serves as the origin of this trend, enabling autonomous evaluation of training success. From a programming perspective, an Agent acts as a role mapping for human programmers, iterating the human outsourcing mechanism from high-value scenarios like accountants and analysts to fewer full-time employees and multiple agent invocation fees.

However, Agents lack human social relationships, and real business interactions do not smooth out simply by applying them. Humans still prefer interacting with other humans, a fact highlighted by U.S. job growth in May 2026, where non-farm employment increased by 172,000 in blue-collar sectors while the financial sector shed 22,000 jobs. The economics of Agents hold true only in theory, as consumption-side infinite growth has not materialized. The critical question remains how to invoke Agents with each other to create network effects. Venture capital cannot effectively explore technological signals, and Agents have been mass-produced without establishing natural invocation relationships. Merely issuing Agent assets or making DeFi protocols Agent-centric is meaningless in a blockchain already crowded with bots, as adding smart contract calls increases technical risk.

Human agency cannot be replaced by Agents because role mapping relies on business relationships and trust, which cannot be achieved in a vacuum. Projects like Exa aim to meet demand for one-time cleansing and multiple calls, representing true economies of scale, yet triggering calls between systems like Claude and Codex remains challenging. Catena caters to compliance financial needs among B2B Agents, requiring an OCC license, but reducing the cost of scale usage is difficult. Payment protocols represented by stablecoins seek to tap into C2C entry points, aiming to let people use Agents for transactions, learn from human participation, or lead on-chain transactions. While TrueNorth uses Hyperliquid for live trading, making humans willingly accept Agent guidance remains a distant goal compared to VC expectations.

In the Agent+Finance landscape, the 'Pay First, Trade Second' approach dominates, with payments being certain as PayPal and Stripe market shares tokenize into stablecoins. Trading outlooks are promising, from Simmons to Jane Street, yet this differs from the envisioned scenario where Agents take over transactions. A gap exists where VCs want to facilitate active replacement by Agents, but money cannot ensure the success of new social platforms. Drawing from DeFi, allowing Agents to touch funds at low frequency and small amounts can pave the way for high-frequency, large-scale daily use. Establishing a mechanism for Agents to touch money will be easier to convert users than making Agents earn money, requiring humans to act as guinea pigs to establish technological parity and compensation mechanisms.

Only when Agents actively participate in the market can efficiency and security be enhanced, understood as a process of self-bootstrapping where Agents optimize Agents. Trading is the end goal, but it requires a long elliptical runway. In this high-value financial scenario, blockchain serves as an open financial experimentation ground, with stablecoins proving the Agent-optimized market process. This is not about scale but establishing mechanisms and expansion. VC is becoming smaller and more personalized, with Solo GPs and OPCs navigating uncertain technological trends. Following the dot-com bubble, a new era of 'Agents eating software' is emerging, where foundational large-scale models conclude after the IPOs of SpaceX, OpenAI, and Anthropic. New crypto VCs like Dragonfly, ParaFi, Haun, Paradigm, and a16z will continue to scale, potentially launching market-specific funds like 5cc. The DeFi industry faces a paradigm shift where Agents and stablecoins mark the beginning of a dual-core revolution, proving that while crypto is small, the world is vast.