The Death of ‘Zero to One’: Is AI Killing Classic Startup Theory?
For twenty years, Silicon Valley has operated on the ‘zero to one’ playbook, a enterprise idea obsessive about worth extraction, creating centralized monopolies, and capturing consumer consideration. But within the age of autonomous techniques, this traditional mannequin is being systematically optimized out by AI brokers.
This basic breakup of conventional startup fashions is forcing founders to reimagine how they construct, scale, and monetize.
A brand new thesis, titled “Zero to Many,” from research-led funding agency Outlier Ventures argues that AI brokers are systematically dismantling traditional startup idea.
This dramatic shift marks the start of the ‘Post Web’: an web the place autonomous brokers are the first financial actors, and success is outlined by enabling machines to uncover, transact, and execute duties fluidly at scale throughout decentralized ecosystems.
The Blueprint of the Agentic Web
To grasp this modification, take into account a mature decentralized finance protocol like Aave. While Aave began as a platform for people borrowing and lending, the bulk of its utilization at present is machine-driven.
Aave features as monetary infrastructure or a composable protocol, consolidating liquidity, oracle information (like Chainlink), wallets, bots, and cross-chain deployments into one system.
Humans might set preliminary parameters (e.g., “optimize for max yield on my stablecoins”), however brokers and bots execute the complicated methods repeatedly. Functions like looping methods and liquidations are executed by bots at speeds no human might match. This makes Aave an early real-world instance of the Agentic Web, demonstrating a essential evolution from a product designed for human interplay (UX) to one designed for techniques and brokers (AX).
The penalties of this agentic web basically redefine how founders design, construct, scale, and function.
The New User is a Machine: From UX to AX
The core of this transformation is the definitive shift from User Experience (UX) to Agent Experience (AX). When AI brokers change into the principle prospects, founders should construct their merchandise for seamless machine integration and be chosen by brokers.
The conventional deal with intuitive, persistent interfaces (like dashboards and GUIs) fades. Instead, merchandise are more and more constructed for brokers, shifting product entry from consumer interfaces to invisible, machine-first execution through APIs.
In this agent-driven economic system, merchandise are now not browsed; they’re triggered. The most crucial issue for choice is now not model repute or persuasive design, however verifiable proof, through Distributed Ledger Technology (DLT). If an end result can’t be confirmed, an agent will merely select a competitor that may present that verifiability. This is an element of the Agentic Product Lifecycle, the place merchandise are accessed through Agent Experience.
The End of Moats and the Rise of Machine-Speed Velocity
Classic startup idea depends on constructing moats; it’s based mostly on consumer lock-in and high switching prices that obtain winner-takes-all dynamics. These moats are slowly dissolving as gents can change companies immediately, making steady, real-time efficiency crucial sign. This implies that the one moat left for founders is the velocity at which they will construct and iterate.
Startup velocity now compounds at machine velocity. This acceleration is powered by two compounding forces:
1. AI compresses the time to construct, iterate, and ship a product. Real-world examples like Devin AI, an autonomous “AI software program engineer,” reveal how execution and progress cycles are compressed.
2. DLT compresses the time to type capital and coordination incentives (through tokens and good contracts).
This convergence has drastically accelerated technological paradigm shifts. For instance, ChatGPT reached 100 million customers in lower than three months, demonstrating this accelerated tempo of technological paradigm shift. This compression forces initiatives to quickly iterate, optimize, and adapt to stay aggressive.
The Collapse of the Marketing Funnel: Attention to Intention
The conventional Business-to-Consumer (B2C) funnel—constructed on discovery, engagement, and conversion by means of persuasion—is breaking down as brokers take over financial interactions.
Agents don’t browse, interact with adverts, social proof, or emotional persuasion. Instead, they benchmark and choose essentially the most environment friendly choice based mostly on structured information and provable efficiency. This transition marks the definitive finish of the “consideration economic system” and the start of an “intention economic system”.
In this new paradigm, brokers optimise customers’ desired outcomes in a trustless and verifiable method through Distributed Ledger Technology (DLT). Businesses should, due to this fact, monetize profitable outcomes, not display time or engagement. Loyalty is earned by means of steady, agent-led choice, the place suppliers should constantly outperform opponents in real-time on each transaction.
Why Crypto is the Missing Piece
The agentic web, by itself, lacks important infrastructure. Without verifiable ensures round identification, possession, and execution, there’s a restrict to what customers can safely delegate to brokers. Agents stay constrained, unable to tackle high-value duties or function autonomously at scale as a result of they lack belief.
Distributed Ledger Technology (DLT), together with blockchains, good contracts, and tokens, supplies this important layer of trustless coordination. The Post Web is explicitly outlined because the Agentic Internet plus decentralised infrastructure (blockchains, good contracts, tokens). This layer brings the required verifiability, composability, and trustless coordination to distributed agentic techniques.
In this machine-native atmosphere, tokens will function the core interface between human intent and machine execution. They govern programmable incentives, verifiable participation, and self-enforcing guidelines that autonomous brokers demand to operate effectively in distributed techniques.
Conclusion: From Startups to Self-Optimizing Systems
The classical startup mannequin is giving method to adaptive, autonomous techniques that self-reference and self-optimize at machine velocity. Software is turning into autonomous, capital is shifting from static to dynamic, and enterprise fashions are shifting from worth extraction to worth maximization.
Looking on the actuality of the place the trade is heading, it turns into clear that profitable merchandise are probably to shift from centralized, static functions designed for human engagement to modular, machine-first architectures. In this paradigm, success might be measured by seamless agent integration, composability, and steady execution. Founders want to rigorously take into account the implications of such a shift and adapt their pondering from specializing in constructing “startups” to constructing “techniques”.
As brokers change human customers as the first drivers of the Internet, founders should prioritize modular integration, verifiable efficiency, and machine-tailored techniques. These shifts basically signify inevitabilities fthat ounders should start planning for now, as they development mainstream over the following decade.
The future belongs to those that construct resilient, composable techniques that thrive in a machine-native atmosphere. This is just not merely an improve; it’s a structural realignment of how worth is created, coordinated, and sustained within the digital economic system.
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