From Code to Intelligence: How Yeager.ai is Building Internet-Native Smart Contracts

Blockchain technology and artificial intelligence are rapidly converging, creating new possibilities for decentralized applications. At the forefront of this intersection is Yeager.ai, a startup developing internet-connected smart contracts through their GenLayer technology.

Following their recent $7.5 million funding round, we spoke with Yeager.ai founder Edgars about the company's vision to transform traditional smart contracts. With experience from successful ventures including Radix DLT and StakeHound, Edgars brings unique insights into blockchain scalability and practical applications of decentralized systems.

Ishan Pandey: Hi, welcome to our 'Behind the Startup' series. Could you start by sharing a bit about your background and what inspired you to create Yeager.ai?

Edgars: I come from a software engineering background, with a degree in Artificial Intelligence from the University of Edinburgh. My entrepreneurial journey includes founding and being an early employee at several successful startups: Edurio, an edtech company revolutionizing school surveys; Radix DLT, developing highly scalable blockchain technology; and StakeHound, which pioneered liquid staking and grew to manage over $350M in assets.

Throughout my career as an entrepreneur, I've experienced firsthand the limitations of our current legal system. While it's been a transformative innovation that enabled modern commerce, it faces serious challenges: slow execution, prohibitive costs, and a fragmented approach that creates complications in our increasingly global world.

While platforms like Ethereum have attempted to address these issues with Smart Contracts, they face two critical limitations: they can't directly connect to the outside world (relying instead on trusted intermediaries called Oracles), and they can't understand natural language - a crucial element for representing the complex agreements that drive real-world commerce.

In 2023, while experimenting with Large Language Models (LLMs) alongside my co-founders Albert Castellana and José María Lago, we had a breakthrough realization: we could use this technology to overcome the traditional limitations of blockchain systems. This insight led us to create GenLayer, expanding the scope of what smart contracts can achieve.

Ishan Pandey: With AI becoming increasingly integrated into blockchain solutions, what role do you see AI playing in shaping the future of decentralized applications, and how does Yeager.ai stand apart in this space?

Edgars: We're seeing AI integration across the entire blockchain ecosystem - from decentralized model training and inference, to incentive systems for model creators, to platforms that enable AI agents to execute transactions autonomously. While these are all valuable innovations, they're just scratching the surface.

What fascinates me most is a challenge that few projects have tackled: using AI for trustless decision-making in smart contracts. This is where I believe the real transformation lies.

Imagine having a contract with all the expressiveness and flexibility of a traditional legal agreement, but instead of requiring years and tens of thousands of dollars to resolve disputes through the court system, conflicts could be settled within hours for a fraction of the cost. This is the paradigm shift we're working to create.

Ishan Pandey: You've been part of multiple successful blockchain projects, how do your experiences in these ventures influence your vision and approach for Yeager.ai?

Edgars: My experience across different blockchain projects has given me a unique perspective on both the potential and limitations of current blockchain technology. At Radix DLT, I learned firsthand about the scalability challenges that networks face, while at StakeHound, I gained deep insights into how decentralized financial services can work in practice. These experiences showed me that while blockchain technology is powerful, it often struggles with real-world integration and usability.

The most valuable lesson I've learned is that successful blockchain projects need to solve real problems in a way that's both technically sound and practically useful. With Yeager.ai, we're applying these lessons by focusing on making smart contracts more accessible and functional, bridging the gap between blockchain's theoretical potential and practical application.

Ishan Pandey:Yeager.ai is working on smart contracts connected to the internet. What are the primary use cases for these internet-connected smart contracts, and how do they differentiate from traditional smart contracts?

Edgars: We're seeing a lot of immediate interest in areas such as prediction markets and parametric insurance - systems which currently require humans in the loop to make decisions, making them inherently slow and expensive.

On GenLayer you can have an Intelligent Contract that says - go to BBC.com, fetch some articles, use the AI to extract who won an election, for example, and this happens orders of magnitude cheaper and faster than if you had to form a consensus between people.

A further theme for use-cases is any dispute resolution that currently cannot be done in a decentralized way, at least not cost-effectively. With GenLayer, you can build transparent and fair dispute resolution mechanisms for products like instant work platforms and credit card chargeback systems.

Beyond that, an area I'm particularly excited about is autonomous governance. Right now, DAOs are limited by the fact that they're not actually all that autonomous - it's just some token holders voting on what to do next. On GenLayer, you can use AI to make truly autonomous organizations that have a constitution that is enforced by the network itself, and that take actions to pursue their goals, automating away a lot of the minute decision-making that currently slows down DAOs.

Ishan Pandey: With blockchain and AI rapidly converging, what do you think are the major challenges in bringing AI-powered blockchain applications to the mainstream?

Edgars: Security and trust are obviously huge challenges - how do you get people to trust that these AI systems will make high-quality decisions? Our approach at GenLayer is to use a novel consensus mechanism that combines multiple different LLMs, rather than relying on just one. It's like having a panel of judges rather than a single judge, and it's based on an extension of the jury theorem - basically, the wisdom of the crowd applied to AI.

But that's only half the story. The other half falls on the developers themselves - because even the smartest judge can't help you if the contract itself is poorly written. The industry took years to develop best practices for traditional smart contracts, and now we're adding a whole new layer of complexity with natural language instructions.

So one of our biggest challenges is going to be figuring out the best practices for writing these Intelligent Contracts and helping our developer community master them. We need to make sure developers can harness the power of AI decision-making while avoiding the pitfalls.

Ishan Pandey: Yeager.ai recently raised $7.5 million for developing internet-connected smart contracts. Can you share the key focus areas this funding will enable, and what major milestones you're targeting in the near future?

Edgars: A new blockchain is a complicated system with many different components that need to work together - from the consensus mechanism and execution environment, all the way up to developer tools, wallets, explorers and so on. So naturally, the majority of our funding goes towards development costs.

We're focused on getting the system into the hands of builders as quickly as possible so they can start exploring what's possible with this technology. We've already released a local version of the network and a web-based IDE that anyone can try out today at docs.genlayer.com.

Our next major milestone is launching our public testnet before the end of this year. This will give developers a shared environment to deploy their applications and start preparing for our mainnet launch, which is planned for the first half of 2025.

Ishan Pandey: With the rapid growth of AI and blockchain, regulation is becoming an increasingly important topic. How do you see the regulatory landscape evolving for decentralized AI, and what steps is Yeager.ai taking to ensure compliance while fostering innovation?

Edgars: The regulatory landscape for decentralized AI is still evolving, and we expect to see significant developments in the coming years. I believe regulation will focus on three key areas: transparency in AI decision-making, accountability for automated actions, and protection of user interests. Rather than seeing regulation as a barrier, we view it as an opportunity to build trust and adoption in the industry.

At Yeager.ai, we're taking a proactive approach by building transparency into our system from the ground up. Our consensus mechanism that aggregates multiple LLMs' decisions creates an auditable trail of how conclusions are reached. We're also working closely with legal experts to ensure our platform can adapt to emerging regulations while maintaining its decentralized nature. The goal is to create a system that can operate within regulatory frameworks while still delivering the benefits of decentralized AI technology.

Ishan Pandey: How do you think the growth of decentralized AI will impact the broader digital economy?

Edgars: I believe decentralized AI will fundamentally reshape how value is created and exchanged in the digital economy. By automating complex decision-making processes and enabling trustless collaboration between parties, we'll see dramatic improvements in efficiency across virtually every sector. Think about supply chains that self-optimize in real-time, or financial services that can instantly adapt to market conditions. The real innovation won't just be in what these systems can do, but in how they'll enable new forms of coordination and collaboration that weren't possible before.

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