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Decentralized Finance (DeFi) has significantly evolved over the past few years, with Total Value Locked (TVL) growing from under $1 billion in 2020 to approximately $120 billion in 2024. However, challenges in scalability, flexibility, and transaction fairness continue to persist. Chirag Narang, Head of Growth at Uniswap Foundation, has contributed to efforts aimed at addressing some of these constraints through Unichain, an infrastructure focused on programmable liquidity, sequenced transaction ordering, and decentralized validation mechanisms.
Unlike traditional decentralized exchanges (DEXs) that rely on static liquidity pool structures, Uniswap v4’s Unichain enables configurable functionality within its liquidity pools. Narang has worked on the go-to-market strategy and ecosystem development for this system, which allows developers to create features such as dynamic fees, loyalty-based rewards, and automated rebalancing, without the need for separate smart contracts.
“Unichain lets each pool run its own rules safely,” Narang notes. “You can now build lending, insurance, or tiered pricing mechanisms directly into the pool using Hooks.”
Since its implementation, developers have deployed over 1,000 Hooks, which have facilitated more than $70 billion in trading volume and nearly $1 billion in TVL on Uniswap v4. These features have enabled various participants from small businesses to decentralized autonomous organizations (DAOs) to implement tailored financial logic within liquidity operations.
One persistent issue in DeFi is Maximal Extractable Value (MEV), where transactions are reordered to benefit certain actors, often to the detriment of regular users. Unichain introduces a sequencing approach that integrates Trusted Execution Environments (TEEs) to help mitigate these risks by ensuring that transactions are processed in the order they are received, based on gas prices rather than operator discretion.
Through encrypted mempools and public attestations, Unichain aims to limit the potential for MEV-related manipulation. “The sequencing model uses cryptographic protections to reduce the risk of transactions getting manipulated.” Narang explains. “Transactions are not visible to others in the mempool and follow a consistent queue.”
Initial data from pilot deployments suggest improved transaction predictability and reduced MEV leakage. Users interacting with time-sensitive applications, including market makers and on-chain insurance tools, have reported more consistent execution outcomes.
Many Layer 2 (L2) blockchain platforms rely on centralized sequencing, creating single points of vulnerability. Unichain’s Validation Network (UVN) introduces a distributed validation framework that uses staked validators, epoch-based attestations, and slashing incentives to maintain system integrity.
“UVN moves away from centralized coordination by distributing validation among multiple participants,” Narang says. “Validators are penalized for protocol violations to maintain system integrity.”
In this system, validators stake UNI tokens, earn rewards for uptime and compliance, and risk penalties for misconduct. This model is designed to increase fault tolerance and make validator behavior more accountable.
Early users of Unichain’s programmable liquidity and validation features include:
These examples reflect applications where developers have used Hooks to align financial mechanisms with specific community or operational goals.
Narang’s current focus includes expanding cross-chain liquidity coordination between platforms such as Unichain, Base, and Arbitrum, as well as exploring integrations with real-world asset tokenization and data-informed liquidity routing.
“Our ongoing work involves improving compatibility with other ecosystems and supporting structured deployments,” he notes.
Rather than emphasizing disruption, Unichain’s development is positioned to complement existing infrastructure by offering more configurable and transparent systems for DeFi builders. As components such as TEEs and UVN continue to stabilize, their performance and usability in production environments will determine future adoption.
