The evolution of ZK development over the past decade has been remarkable
We went from PhDs writing circuits by hand to building DSLs where developers can write private applications without understanding circuit constraints at all.
Here's what we are a changing about blockchain systems and why it matters.
Traditional blockchains are like mainframes, everyone timeshares blockspace, bidding for milliseconds of execution in each block.
It's an auction model where the highest bidders get scarce computational resources, similar to how computing worked in the 1970s.
ZK enables a paradigm shift similar to the PC revolution.
Instead of competing for shared computation time, users compute locally on their own devices, then submit a succinct proof that the computation was performed correctly.
The network no longer re-executes every transaction, it simply verifies mathematical proofs. This architectural change unlocks massive scalability improvements and enables privacy simultaneously.
This fundamentally changes what's possible. Just as the PC revolution enabled applications that would have been impractical on mainframes, ZK enables blockchain applications that would be prohibitively expensive or technically impossible on traditional chains.
Models with millions of parameters, complex game logic with hidden state, and private financial transactions all become possible when we move from the mainframe model to the personal computing model.
This is why @AleoHQ has built from first principles rather than adding ZK as an afterthought to existing architectures. The future isn't just faster mainframes, it's a completely new computing paradigm.
I'd bet the (yield) farm that every new zkVM contains critical vulnerabilities.
From experience, they'll have unintentional but highly consequential backdoors. This is not surprising. The math behind ZK systems is extraordinarily complex, and generating proofs for off-chain executions while managing state requires years of specialized research.
The true test? Ask any team if they'd deploy today.
Banks keep your data private. Credit cards encrypt transactions. Even cash is anonymous.
But crypto?
Your ex can calculate your net worth. Your grandmother can see you ape into $FART at the top. Your employer can track you when you're off the clock. Foreign governments can freeze assets they don't like *at any time*.
This is INSANE.
We built the internet, then gave up privacy for convenience. We built social media, then got harvested for ad revenue. We built crypto to escape surveillance...
And made SURVEILLANCE the CORE FEATURE.
I built @AleoHQ to END THIS MADNESS.
Mathematical privacy. Cryptographic certainty. No trusted parties. No data harvesting. No surveillance capitalism.
Are you with the deep state or are you with $ALEO?
Right now, as you read this, your on-chain activity is being scraped, analyzed, and monetized by:
→ MEV bots extracting $1.4B annually from YOUR trades → Chain analytics firms selling YOUR data to governments for $100M+ → Competing traders copying YOUR strategies in real-time → Market makers front-running YOUR large orders → Surveillance firms building YOUR complete financial profile
You think you're using "decentralized" finance?
You're using the most surveilled financial system ever created.
Every smart contract interaction = permanent public record Every token swap = broadcast to the world Every yield position = analyzed by competitors Every wallet connection = tracked across protocols
- Private payments: Imagine USDC transfers that preserve transaction privacy while maintaining regulatory compliance, keeping your entire financial history from being exposed to everyone you transact with. - Identity verification: Using a passport's digital signature to prove you meet certain criteria without revealing personal details, enabling KYC without data exposure. - Gaming with hidden state: Creating games like Battleship, Poker, or strategy games where information asymmetry is fundamental to gameplay. - Machine learning: Run inference using private models where the model owner doesn't see your input data, and you don't see their model, only the verified output. - What excites me most is that we're moving beyond theoretical capabilities to practical applications built by teams focused on specific problems, not just "build an L1/L2."
Projects like ZKP2P and ZPass are tackling concrete use cases with clarity of purpose.
The true power of ZK isn't just theoretical math.
It's enabling real-world applications that were previously impossible.
It's very surprising how far we've gotten as an industry without private smart contracts.
We've found product-market fit in trading, stablecoins, and basic DeFi all despite lacking fundamental privacy. Imagine what's possible once we enable Web2-like UX on crypto rails.
Some Aleo lore (when we restarted the whole project):
Building a general-purpose ZK VM meant rethinking circuit architecture from first principles.
We moved from R1CS gadget libraries to an opcode-based design where every operation maps to a single circuit. This enables program-level upgradability and formal verification.
Two years into development, we hit a wall.
Our formal verification team discovered bugs in our circuits, but with the gadget-lib approach, we couldn't isolate which applications used the vulnerable components. It was impossible to trace and identify which parts needed fixing.
We made the painful decision to scrap our entire design and rebuild from scratch.
Instead of a monolithic circuit structure, we created a clean separation: every operation (add, mul, div) became its own distinct circuit with clear boundaries.
This architectural shift parallels traditional computing.
Just as bytecode creates an abstraction layer in the EVM, Aleo Instructions create a boundary between the language (Leo) and the underlying circuits. The language becomes a thin compiler targeting these instructions.
The benefits are enormous: if a vulnerability is discovered, we can precisely identify affected programs, upgrade specific instructions, and maintain backward compatibility. This is critical for a production system handling real assets.
This architecture also unlocks formal verification. Each instruction can be individually verified, creating mathematical certainty about system behavior. Without this architecture, upgrades would require replacing everything, creating massive security risks.
Sometimes the hardest decisions lead to the best outcomes. Rebuilding our VM from scratch cost us nearly a year, but created a foundation that can evolve securely for decades to come.