Trust in Today's Blockchain Space

What's your first memory of riding a bike as a child? Maybe it was the sound of air hissing as you pumped up the tires, cruising through the neighborhood, or taking a fun dirt path through the woods. For me, it started with a dream — a shiny bike hanging in my father's garage. It was old and creaky, but I didn't care. At seven years old, it became mine.

That joy was short-lived. First, I broke it. Then, after getting a brand-new one, something worse happened — someone asked to hold it for a moment, and that was the last time I saw it. If you've ever lived in a tough neighborhood, you know how that story ends. My mother's comforting words and a police officer's half-hearted search didn't bring it back, but I walked away with a lesson: trust is fragile.

And in Web3, that lesson still holds.

What does trust in Web3 look like?

When I started writing this blog, I dug deep into trust models — both in software and social systems. But no matter how much I researched, my mind kept circling back to that stolen bike.

Today, Web3 feels a lot like my old neighborhood: locked doors, high fences, and big dogs. We have audits, monitoring, and endless security tools — yet scams, exploits, and failures still happen. When an environment needs constant protection, it signals a lack of trust, and without trust, doing business becomes difficult and unwelcoming.

We’re missing out on billions of potential users who hesitate to step into Web3. Not because they don’t understand it but because they don’t trust it.

Trust in tools and intentions

Trust comes in two forms: trust in tools and trust in intentions.

The first is straightforward — would you ride a bike if you didn’t trust its brakes? In Web3, we trust tools like Geth because they’re battle-tested. But any new implementation? That takes time to earn trust.

The second is trickier. You can trust an audit, a smart contract, or a protocol, but do you trust the people’s claims about interaction with such protocols? Would you buy a brand-new bike from a stranger off the street? 

At Pi Squared, we understand the nuances of trust. Our team brings deep experience in formal methods, infrastructure, and security auditing — but we’re not just adding more fences and locks to Web3.

Instead, we focus on mathematical and proof mechanisms that are seamless, transparent, and explicit when it comes to proving intent. Because for Web3 to scale, trust can’t be an afterthought — it has to be built in.

Trust in tools and Proof of Proof

Building trust in Web3 means reducing blind faith in tools. If you have an execution of a transaction in a virtual machine (VM), you need to trust that the VM operates correctly. If you compile a program and run it with certain inputs, the so-called trust base would now include the compiler and the program itself.

In the modern blockchain stack, we have various VMs, protocols and components that are used for executing transactions. The trust base has immense size and formal verification is almost impossible in this case.

But even if it were possible, we also would have to trust the verification tool, and many of those are huge and developed by academic communities that don't have the resources or priorities to ensure the highest level of correctness.

That's where Proof of Proof — Pi Squared's approach to verifiable computing — comes into play. Proof of Proof allows us to drastically reduce the trust base required for executing transactions to a tiny proof checker with less than several hundred lines of code by making what previously constituted the trust base verifiable. 

Every major innovation builds on either mature technologies or new application domains. Proof of Proof does both, standing on three key pillars:

1. Formal semantics for your favorite programming language.
2. Mathematical proofs that verify the correctness of program execution traces.
3. Zero-knowledge proofs that compress large math proofs into compact, easy-to-store cryptographic artifacts.

Among the three components, the formal semantics of programming languages is a must for a trustless toolchain and infrastructure. 

When you write code, you trust your compiler to execute it correctly — but compilers are massive black boxes filled with millions of lines of code (and plenty of bugs). Formal semantics brings clarity by defining, in strict mathematical terms, all the behaviors of all the programs in the programming language; no compilers or interpreters need to be trusted.

At Pi Squared, we use the K framework, a system that's been in development for 20 years and is even used by NASA. K-based transactions are already fast — nearly 90% as fast as Geth depending on a smart contract —and with further optimization, we've even hit 157% for certain protocols. And we're not stopping there; every month, we're improving performance.

But trust isn't just about execution — it's also about proof.

Even if K correctly executes your program, can you trust K itself? After all, it's another black box. That's where Matching Logic comes in. Matching Logic allows K to generate mathematical proofs of execution that are fully machine-checkable. Proof checkers, in contrast to full compilers, are tiny — just a few hundred lines of code. So, the trust base gets reduced to a tiny checker instead of a huge K.

With formal semantics, K, and mathematical proofs, we don't need to blindly trust millions of lines of code anymore. Proof of Proof minimizes the trust base to formal semantics and a tiny proof checker.

Verifying intentions with USL

When interacting with blockchain systems, we’re constantly asked to trust claims about computation, blockchain state, or even consensus. But how do we know these claims are true?

That’s where one of the three core components of Pi Squared’s architecture comes in: The Universal Settlement Layer (USL). USL enables multiple ways to verify these facts, and Proof of Proof is one of them.

USL introduces the concept of various claims, an evolution of traditional blockchain transactions. For example, a block transition claim is not just a transaction or set of transactions; it also specifies conditions for the blockchain's before and after states. This means that when you sign a transaction, you're not just trusting code — you're verifying guarantees.

However, as seen in the figure above, block transition claims are just one part of the picture. USL supports multiple types of claims, each designed to enhance trust in different aspects of blockchain interactions.

USL is a distributed network for everyone to submit, verify, settle, store, and use claims about anything. In particular, computation claims and their Proof of Proof-generated proofs can be used in the USL, making verifiable claims a reality.

Bringing trust to every ecosystem

USL isn't another blockchain — it's a distributed verification service that integrates with existing ecosystems. Any protocol can generate claims and their corresponding proof for users to settle and once settled, any application can use it.

We're already taking the first steps — Wormhole is integrating Pi Squared's USL, bringing these principles to cross-chain interactions. We've integrated pod with USL to leverage its performance to enhance how the USL handles transactions. And this is just the beginning. The foundation is proven, the technology is ready, and the next step is expanding this across the entire blockchain industry.

Conclusion

When verification is seamless and built into the foundation of Web3, trust stops being a barrier—and people, businesses, and innovation thrive.

At Pi Squared, we’re making trust visible by reducing reliance on black-box tools and ensuring that intentions are verifiable.

With Proof of Proof, you no longer need to blindly trust execution, and with USL, you don’t have to guess the outcome of a transaction. These technologies aren’t just theoretical; they’re real, working solutions that are already shaping the future of blockchain.

To learn more about Proof of Proof, review our documentation and read our Pi Squared white papers.