In the past, enterprise software startups often followed a clear path: first, find a small but expandable entry point to achieve tens of millions of dollars in ARR with a single-product; then expand the product suite around the same buyer to reach hundreds of millions; finally, once enough users and data have accumulated, become a new platform. However, in the AI era, this “three-act playbook” is becoming obsolete.
As software development costs rapidly decrease and the cycle from concept to implementation is significantly shortened, startups no longer need three to five years to prove a niche market and slowly expand boundaries. Companies like Cursor, Clay, and Harvey have approached or even surpassed $100 million in ARR in a short period, signaling a rewritten competitive pace. The core argument is that in a rapidly changing market, relying on a “safe entry point” may be conservative; new software companies need the ambition to rearchitect entire workflows from the start.
Historically, Act One involved entering a niche area to reach tens of millions in ARR, followed by Act Two, where companies launched adjacent products to break through $100 million, and finally Act Three, where they rebundled to replace existing platforms. This process typically required 6 to 10 years of calendar time.
Today, this approach is dead because the world is evolving too fast. With software engineering costs plummeting, the time required to complete these stages is approaching zero. Founders should no longer wait to refine a step-by-step strategy but should plan to build everything quickly from the start.
This shift has changed the nature of early-stage investing. Rather than looking for a protective moat or a safe entry point, investors now value unreasonable and relentless ambition. If you want to build a transformative company, you should go for the “whole enchilada” from the start, as the three-act play is no longer a viable strategy in a fast-changing era.
[BlockBeats]
The AI-Driven “Fast-Pass Era” and Its Implications for Crypto Investment
The enterprise software landscape is undergoing a fundamental transformation, with AI rendering the traditional “three-act play” entrepreneurship model obsolete. This shift from gradual expansion to immediate comprehensive solutions carries profound implications for the crypto market, particularly at the intersection of AI and blockchain technologies.
Disruption of Traditional Growth Trajectories
Historically, successful software companies followed a measured progression: establishing a niche position (Act One), expanding their product suite (Act Two), and finally evolving into platforms (Act Three). This 6-10 year timeline provided predictable investment trajectories and risk assessment frameworks. In crypto, we’ve seen similar patterns with projects focusing on solving specific problems before expanding their ecosystems.
However, companies like Cursor, Clay, and Harvey are achieving $100M+ ARR at unprecedented speeds, demonstrating that AI-powered development can compress years of work into months. This directly impacts crypto projects that leverage AI for development, testing, or optimization. Projects like Fetch.ai (FET) and SingularityNET (AGIX) are no longer just “AI blockchains” but comprehensive ecosystems that aim to redefine entire industries from inception.
Tokenomics in the Fast-Pass Era
The traditional crypto investment thesis often emphasized gradual token utility expansion, similar to the three-act model. In the new paradigm, token economics must account for accelerated value capture:
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Front-loaded utility: Tokens must demonstrate immediate value beyond simple speculation. Projects like Render (RNDR) and Ocean Protocol (OCEAN) are designing tokenomics that reward immediate data and computational resource sharing, rather than waiting for ecosystem maturity.
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Velocity of value accrual: With development cycles compressed, token appreciation may occur more rapidly. This creates both opportunities and risks, as seen with AI tokens like AGIX and FET, which have experienced extreme volatility alongside genuine technological progress.
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Network effects at speed: The ability to onboard users and developers exponentially faster changes token distribution models. Projects that can rapidly deploy AI-enhanced developer tools, like Bittensor (TAO), may capture network value much sooner than previous generations of protocols.
Investment Risks in the Accelerated Landscape
The shift to the “Fast-Pass Era” introduces new risk dimensions for crypto investors:
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Premature scaling: Unlike traditional software where failure costs were contained, crypto projects that scale too quickly without proper security or governance foundations can lead to catastrophic failures. The collapse of several AI-driven DeFi protocols in 2023 demonstrated this risk vividly.
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Regulatory arbitrage: As AI capabilities advance, projects that push regulatory boundaries may face sudden crackdowns. The SEC’s recent actions against AI-related token offerings highlight this emerging risk vector.
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Market saturation: With development barriers lowered, we’re seeing an influx of AI-blockchain hybrids, potentially leading to market saturation. Investors must now differentiate between truly innovative projects and those merely riding the AI narrative.
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Concentration risk: The fast-pass model favors well-funded teams, potentially increasing centralization in the AI-blockchain space. Projects like Near Protocol (NEAR) and Avalanche (AVAX) with strong backing may dominate, leaving little room for smaller players.
Strategic Opportunities for Crypto Investors
Despite these risks, the AI-driven transformation presents compelling opportunities:
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AI-enhanced infrastructure: Projects that provide the foundational AI-blockchain infrastructure are positioned to benefit from the accelerated development cycle. Fetch.ai’s autonomous agent framework and SingularityNET’s decentralized AI marketplace exemplify this thesis.
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Tokenized AI models: The ability to tokenize and trade AI models creates entirely new markets. Projects like Bittensor are pioneering this approach, allowing AI developers to monetize their models directly through token incentives.
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Cross-chain AI solutions: As AI applications become more complex, the need for interoperability grows. Projects like Chainlink (LINK) that provide AI oracles and cross-chain data solutions are critical enablers of this new paradigm.
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Decentralized AI training: With large AI models requiring massive computational resources, decentralized training presents an opportunity to democratize AI development. Ocean Protocol and others are creating marketplaces for data and computational resources that can power the next generation of AI models.
The New Investment Framework
For experienced crypto investors, the “Fast-Pass Era” requires a reassessment of traditional due diligence:
- Team velocity assessment: Evaluate not just technical capability but the team’s ability to execute rapidly without compromising security or sustainability.
- Token utility stress testing: Assess how the token function performs in various accelerated growth scenarios, not just gradual adoption.
- Regulatory navigation capability: Prioritize teams with experience navigating complex regulatory environments, as AI-blockchain hybrids face increasing scrutiny.
- Ecosystem enablement: Look for projects that provide tools and infrastructure for others to build quickly, creating a flywheel effect similar to what we’re seeing in AI software development.
The convergence of AI and blockchain is not just another trend—it represents a fundamental shift in how value is created and captured in the digital economy. Projects that embrace the “Fast-Pass Era” while maintaining decentralized principles and robust security will likely emerge as the dominant players in the next cycle.
Conclusion
The death of the three-act play in software entrepreneurship signals a broader acceleration in technological development. For crypto investors, this means rethinking traditional investment theses and focusing on projects that can leverage AI to deliver comprehensive solutions rapidly. The most promising opportunities lie at the intersection of AI and blockchain, where the combination creates new possibilities for value creation that neither technology could achieve alone.
As we move further into this AI-driven era, the ability to identify and invest in projects that can execute at speed while maintaining decentralized integrity will separate successful investors from those who fail to adapt to the new paradigm.