AI-Friendly Is The New Instruction

By Sandra Grabowiec

When Web3 first emerged in 2014, with the term coined by Ethereum co-founder Gavin Wood, it was heralded as the genuine next evolution of the internet. It promised a decentralized, user-centric ecosystem where individuals could take back control of their data, finances, and social interactions, while potentially being rewarded for doing so thanks to unique token economics.

Now, a decade later, as the dust settles, a provocative new thesis is emerging – Web3 was never really built for humans – its architecture was predestined for AI agents. Whether intentional or accidental, the notion seems quite fitting considering the never-ending Web3 conundrum of UX being the main hurdle to mass adoption. So there you have it – all we need to do is take humans out of the equation and Web3 is hurdle-free.

All of a sudden Web3’s additional complexities, like trustless transactions, decentralized infrastructure, and inherent programmability, seem far better suited for AI-to-AI interactions. Take a step back to assess this idea and you’ll find it hard to argue that Web3’s architecture looks like it was designed for a future where AI agents are the primary drivers of economic activity.

The AI-to-AI Transaction Paradigm

The shift from human-centric to AI-driven economic interactions has been underway for some time now. In this new paradigm, transactions won’t be initiated, negotiated, or executed by humans (or businesses), but rather by autonomous AI agents working on their behalf.

Imagine a world where your AI assistant can haggle and barter with another AI to get you the best price for a particular service or product. In that world, it’s easy to see how AI agents could quickly take over entire supply chains, operating rapidly and collaboratively over decentralized networks. These would be the first signs of a new AI economy model, one with scalable microtransactions and dynamic real-time pricing systems. And it’s not a far-fetched reality. These AI-to-AI transactions are already happening.

The implications are profound. AI agents don’t need a lunch break or to sleep eight hours a night – they’re on 24/7. They don’t have trouble balancing monumental data loads, executing precise transactions, or managing hundreds or thousands of interactions simultaneously. But, what they do need is infrastructure, and that appears to be Web3’s important role.

Exploring the Architectural Alignments

It’s hard to argue against the case that Web3’s foundational traits make it uniquely suited for the AI economy. Starting with trustless transactions, it’s becoming more and more apparent that AI agents thrive in environments where trust is fully codified and verified, not just assumed. In addition, DLT ensures that AI agents don’t need intermediaries or third-party verification to do their finest work.

Fully decentralized systems, where no single entity has control, are also optimal for AI agents. Here, with distributed architecture to enjoy, they can act and move freely, released from the shackles and bottlenecks of centralized gatekeepers, even if there are still instances where autonomy is not a given for some agents like Truth’s Terminal. It is also here that they are able to execute complex transactions autonomously, across all platforms, protocols, and chains, potentially forming the backbone of the new AI economy. The idea is simple: let AI agents roam all available avenues to get the best results.

This is what Outlier Ventures calls “The Post Web” in a recent report, while also predicting that, “In The Post Web’s Intention Economy; intent-based AI agents prioritise users’ true needs, aligning counterparties with user intentions and enabling efficient, value-driven interactions with minimal extraction and rent seeking.” Sounds exciting? Because it truly is.

The Revolution Will Be Found On-Chain

It’s no longer a theoretical future where the onchain environment is the go-to playground for AI agents, especially those focused on trading. Right across the DeFi landscape, protocols are rapidly updating their infrastructure to accommodate AI-driven interactions. In fact, many cryptocurrency projects that previously had nothing to do with AI agents are now making pivots into the space, competing with established AI developments for mind and market share.

To keep up, DeFi projects must develop be AI-Agent-ready and they’re already exploring ways to do that via APIs and SDKs. There is an accelerating demand for infrastructure that can support AI agents as they begin to interact directly with blockchain networks on activities like automated trading and decentralized governance. It’s not enough to be human-friendly anymore. AI-friendly is the new instruction.

The Future Outlook

The future of Web3 is one where AI agents dominate economic activity. Shifting to that future, however, will involve brand new challenges and opportunities. On one hand you have serious questions about accountability, governance, and the human workforce in a machine-dominated world, while on the other you have the perks of unprecedented efficiency and innovation.

Now, whether by accident or design, the decentralized, trustless, and programmable nature of Web3 is perfect for the AI future. Outlier Ventures neatly summarizes the situation, stating, “We can look at a decade of Web3 as a battle hardening of a human-tested stack of distributed architecture and incentive games from smart contracts, token economics, DAOs, and DeFi. While too complex for people themselves to operate at scale, the stack is primed for AI and the agentic internet.”

All we can do now is understand where we, as users, fit in this new paradigm and watch it play out in real-time.

Author bio

Sandra Grabowiec serves as the Head of Partnerships at Singularity Finance, a project within the SingularityNET ecosystem that is building a financial layer for AI, tokenizing the AI economy, and developing intelligent multi-asset vaults.

Her journey in blockchain began in 2018, sparked by preparations for a conference where she explored technological development dilemmas using blockchain, specifically Bitcoin, as a case study. She went on to write her thesis on the impact of smart contracts on business process automation in B2C e-commerce and later earned a Master’s degree in Blockchain and Digital Currency, further solidifying her expertise in decentralized technologies.

As a speaker, Sandra frequently addresses topics related to the tokenization of real-world assets (RWAs) and is a dedicated mentor to those new to Web3. She supports Polish Blockchain Associations through educational and mentoring initiatives and also serves as a Web3 consultant at a software house, where she advises clients on go-to-market (GTM) strategies and product positioning.

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