History of NEAR Protocol

Tracing the Origins and Evolution of NEAR Protocol

NEAR Protocol’s history begins in early 2018, not as a blockchain but as a machine learning project. Founded by Illia Polosukhin and Alexander Skidanov—veterans from Google and MemSQL respectively—NEAR started as a collaborative platform for researchers but pivoted to blockchain after identifying limitations in existing smart contract platforms, especially around scalability and developer usability.

The protocol officially launched with the NEAR Foundation's support in late 2020, following a phased mainnet rollout. Prior to the full mainnet release, NEAR leveraged a "proof of authority" model for early development and testing before transitioning into its eventual proof-of-stake (PoS) consensus mechanism.

From its inception, NEAR Protocol was designed around sharding, using a custom architecture known as Nightshade. Nightshade distinguishes NEAR by implementing a novel form of dynamic sharding, aiming to provide near-infinite scalability by splitting computation not just by transaction or block, but at a granular state level. This mechanism allows the network to process transactions in parallel across multiple shards, avoiding typical bottlenecks faced by monolithic chains.

Despite the innovation, Nightshade’s rollout wasn’t without obstacles. Modular sharding is notoriously complex to implement and test, particularly alongside NEAR’s governance and user-facing abstractions like “human-readable accounts” and gas fee delegation. Initial testnets were plagued with bugs and performance inconsistencies, which slowed adoption during a critical time when rival chains like Solana and Avalanche gained significant traction.

Moreover, NEAR’s early efforts to attract developers by offering simplified tooling with features like AssemblyScript and later Rust support posed challenges in developer migration. The ecosystem lacked robust interoperability in its first stages and had limited wallet infrastructure compared to more mature alternatives.

In terms of governance, NEAR Foundation’s centralized decision-making model drew criticism, echoing similar concerns raised in other ecosystems like Hedera Hashgraph, where centralized governance structures have sparked debates about decentralization and transparency. Although NEAR has moved toward a more decentralized council-based governance structure over time, questions remain about its long-term community involvement mechanisms and whether token-weighted voting adequately represents stakeholder diversity.

Lastly, NEAR’s grant programs and ecosystem funding, while substantial, have occasionally been critiqued for lacking transparency in selection criteria, leading some developers to migrate toward chains with more predictable funding mechanisms. However, the protocol’s evolution reflects a constant tension between innovation and governance complexity—a narrative not unfamiliar to others navigating the high-speed trajectory of Layer-1 development.

How NEAR Protocol Works

How NEAR Protocol Works: A Deep Dive into Nightshade Sharding and Web3 Infrastructure

NEAR Protocol is structurally distinct from many other layer-1 blockchains due to its implementation of Nightshade sharding, its developer-centric tooling, and an account model that enhances composability. Unlike traditional L1s that often struggle with scalability trilemma constraints, NEAR prioritizes parallelization through automatic resharding, allowing transaction throughput to scale linearly with network usage.

At the heart of NEAR is Nightshade, a unique sharding design where each shard produces its own block, but these individual shard blocks are presented as a single block to the main chain. This allows the network to maintain a single global state while still benefiting from the parallelism of shard processing. Importantly, this differentiates it from other methodologies where shard states can diverge, resulting in complex interoperability challenges.

NEAR achieves dynamic resharding — adjusting the number of shards based on demand — without forcing validators to coordinate shard splitting or merging manually. This is non-trivial from a consensus and validator assignment perspective and is enabled by thresholded signatures and stateless validator design. However, this elegant abstraction does obscure some of the internal shard logic, which can be a challenge for lower-level developers seeking deterministic performance profiling.

The protocol’s consensus mechanism, Doomslug, complements its sharding structure. Doomslug doesn’t wait for finalized blocks through full network consensus; instead, it treats blocks as finalized with a single round of communication between block producers. This results in faster finality but comes with assumptions about network synchronicity and validator honesty, which, if broken, could potentially increase the risk of forked chains.

NEAR’s contract execution layer is Wasm-based, supporting high-level languages like Rust and AssemblyScript. However, its current lack of EVM compatibility siloes many lending, DEX, or NFT primitives into a unique ecosystem. Composability is tightly coupled within NEAR-native applications, but interoperability with Ethereum-based DeFi remains constrained, typically requiring bridges like Rainbow, which present their own attack surfaces and performance limitations.

One unique element of NEAR is the human-readable account model, replacing cryptographic wallet addresses with named accounts (e.g., alice.near). While this improves UX, it introduces concerns regarding name squatting and added layers in identity resolution — similar to challenges seen in DNS and platforms with identity layers.

While NEAR’s architecture is technically distinguished from blockchains like Hedera Hashgraph, both represent efforts to rethink performance bottlenecks at the protocol layer. For a deeper understanding of similar governance layer innovations, explore Decoding HBAR's Tokenomics for Future Growth or Unraveling HBAR The Future of Distributed Ledgers.

Use Cases

Real-World and On-Chain Use Cases of NEAR Protocol

NEAR Protocol presents a wide array of use cases designed to exploit its high throughput, fast finality, and sharded architecture. While its core innovations position NEAR as a high-performance smart contract platform, the actual breadth of use falls into a few tightly-focused categories—each with its own nuances and limitations.

1. Developer-Friendly dApp Deployment

Perhaps NEAR's most significant use case lies in its attractiveness to developers building decentralized applications (dApps). With support for high-level languages like Rust and TypeScript via AssemblyScript, NEAR eliminates many barriers to entry that plague EVM-based chains. Its contract-based storage and "pay-as-you-go" model allow users to interact with dApps without needing to preload wallets or manage transaction fees, thanks to meta-transactions and contract-backed fee delegation.

Fragmentation among users and tooling may, however, hinder adoption. While its structure is ideal for simplicity and UX-focused applications, developers seeking broader community exposure often prioritize Ethereum compatibility, leaving NEAR’s ecosystem less saturated but arguably less liquid.

2. Gateway for Web2 to Web3 Integration

Projects leveraging NEAR are increasingly focused on hybrid Web2/Web3 products, from social applications to gaming platforms. NEAR offers a simple onboarding process (e.g., human-readable accounts without mnemonics) tailored toward mass adoption, aiming to bridge traditional applications into decentralized ecosystems. However, onboarding ease sometimes comes at the cost of decentralization purity; NEAR’s account abstraction model offers a smoother UX but introduces complexity for users demanding maximum custody and trustlessness.

3. Multi-Chain Interoperability via Rainbow Bridge

NEAR’s Rainbow Bridge facilitates token and data transfers between NEAR and Ethereum, giving it strategic utility in an increasingly multi-chain environment. Smart contract interactions across these chains can be permissionlessly bridged, enabling liquidity sharing and value interoperability. The vulnerability of bridges, however, remains a critical risk vector—several cross-chain exploits in the broader ecosystem underscore the need for cautious architecture assessment.

4. Governance and DAO Coordination

The NEAR ecosystem actively supports decentralized autonomous organizations (DAOs) through tools like AstroDAO. DAOs use NEAR to manage treasuries, conduct voting, and execute smart contract-based decisions. While infrastructure exists, DAO vibrancy on NEAR remains limited relative to EVM-centric chains, raising questions about activity and sustainability.

For those interested in governance structures in similar ecosystems, see https://bestdapps.com/blogs/news/decoding-hederas-innovative-governance-model which highlights Hedera’s approach.

5. NFTs and the Creator Economy

NEAR enables low-cost minting and interactions, making it suitable for NFT marketplaces and creator tools. Though platforms like Paras and Mintbase have taken root, overall network effects and secondary market liquidity are dampened compared to competitors. The low fees are attractive, but serious NFT players still view Ethereum and even Solana as default venues.

As use cases scale, the central technical challenge remains NEAR’s ability to onboard developers and users faster than competing L1s, while distinguishing itself in a saturated market.

NEAR Protocol Tokenomics

NEAR Tokenomics: Inflationary Model, Staking Dynamics, and Usage Utility

The tokenomics of NEAR Protocol's native asset, NEAR, is designed with a hybrid approach that combines inflationary supply with a deflationary burn mechanism to balance ecosystem incentives with token value retention. NEAR started with an initial total supply of 1 billion tokens, distributed through a mix of early contributors, grant programs, community incentives, and fundraising rounds. While this centralization at genesis raised concerns around token distribution fairness, NEAR has introduced mechanisms to gradually decentralize ownership over time.

Emission and Inflation Design

NEAR operates with a nominal annual inflation rate of 5%, of which 90% is allocated to validators and their delegators as staking rewards. The remaining 10% is directed to the NEAR Treasury, controlled by the NEAR Foundation for protocol development and ecosystem grants. However, transaction fees on NEAR are partially burned—currently, 70% of gas fees are permanently removed from circulation—with the remainder distributed to contracts, contributing to a negative effective inflation under high network utilization. This design resembles EIP-1559’s deflationary targeting, aiming to counterbalance token dilution as usage scales.

That said, the inflation schedule isn't capped or pre-programmed like Bitcoin, which introduces ongoing supply increases. Critics argue that this could suppress value accrual unless long-term usage significantly outpaces emission—a critique also raised in the context of dynamically inflated assets like HBAR.

Staking Participation and Validator Economics

NEAR uses a Thresholded Proof-of-Stake consensus model with permissionless validator entry but limited validator slots, which may impact decentralization if the number of active validators remains constrained. The network employs epoch-based rebalancing and a stake-weighted mechanism that requires validators to continually compete on efficiency and uptime. Delegators can participate through liquid staking derivatives, adding composability and DeFi utility, though it introduces smart contract risk.

Validator ROI depends on overall staked supply, often hovering in the 60-70% range, which affects yield dynamics and capital lockup. When staking saturation is high, smaller holders may face uneconomical reward-to-risk ratios, particularly as staking liquidity remains fragmented across custodians. These same criticisms apply to other staking tokens with similar validator concentration issues, mirroring debates seen in networks like Hedera Hashgraph.

Utility and Fee Mechanism

NEAR tokens are primarily used to pay for gas fees, stake with validators, and participate in governance (though on-chain governance is still nascent). Unlike blockchains that decouple gas and governance tokens, NEAR uses its native token for all roles, increasing its velocity. This broad utility design consolidates function but can introduce volatility in dApp cost estimations, especially during network congestion events.

Furthermore, gas fees are dynamically priced in NEAR units, with a fee market adapting per block load, adjusting gas prices depending on usage. This design aims for elastic scalability, but developers may find predictability lacking—particularly when deploying high-frequency smart contracts in volatile usage scenarios.

NEAR Protocol Governance

NEAR Protocol Governance: Validator Voting, DAOs, and Systemic Tradeoffs

NEAR Protocol employs a hybrid on-chain and off-chain governance model, structured to maintain decentralization while optimizing for scalability and usability. The protocol operates under a proof-of-stake consensus using the Nightshade sharding mechanism, where validators play a central role in protocol governance through block production and rewards allocation. However, their influence over systemic upgrades or economic parameters is limited compared to governance structures like those in more expansive on-chain systems.

At the core of NEAR’s governance is the NEAR Digital Collective (NDC), a meta-governance DAO meant to unify disparate ecosystem DAOs into a single framework. This multi-layered governance model introduces Council DAOs, House of Merit, and the Community Treasury, all intended to represent stakeholders and manage treasury funds. The ecosystem is attempting to decentralize control over protocol-level decisions, funding allocations, and developer incentives, but the current processes are abstract and often opaque. Decision-making transparency and voter turnout remain contentious points, especially when large token holders can disproportionately influence votes.

While attempts have been made to elevate governance through proposals and structured funding rounds, community engagement metrics reveal governance fatigue and centralization tendencies. Some critics argue that the presence of the NEAR Foundation as a centralized actor undermines the DAO-first ethos. This dynamic echoes concerns similarly raised in distributed ledger ecosystems such as Hedera, where questions about governance decentralization and council influence continue to persist.

NEAR token holders can theoretically influence governance through participation in DAOs and staking delegation, but these systems are constrained by limited tooling and coordination challenges. Unlike governance-maximalist chains like Polkadot or Cosmos, NEAR takes a developer-friendly approach prioritizing UX, sometimes at the cost of governance fluidity and transparency.

Additionally, while the protocol allows upgrades and parameter changes via governance mechanisms, the upgrade path is not fully autonomous. Decisions still funnel through off-chain coordination, including GitHub discussions and NEAR Foundation input. This dualism has drawn comparison to tech-centric governance models rather than ideologically decentralized systems.

Efforts to build reputation-based governance models within the NEAR ecosystem remain experimental. The use of quadratic voting or identity-linked systems is still underexplored, leading to participation inequality and reinforcing existing token-weighted governance issues. There is substantial room for better integration of governance primitives that empower smaller holders and domain-specific DAOs. Similar challenges, though addressed differently, are found in the critiques of Hedera governance structures, raising recurring questions about balancing efficiency with decentralization.

Technical future of NEAR Protocol

NEAR Protocol Technical Roadmap: Sharding Evolution, WASM Advancements, and Account Abstraction

NEAR Protocol’s technical roadmap continues to revolve around its foundational goal: scalability without compromising usability or decentralization. The network has already implemented the first stages of Nightshade, its sharding architecture, but further sharding refinements are ongoing. Nightshade differs significantly from typical sharding approaches. Each shard in NEAR carries out computations independently, but contributes to a single chain state. With the future move toward full dynamic resharding, NEAR aims to enable shards to be spun up or down automatically based on network load—an effort to mitigate both state bloat and validator inefficiencies. However, balancing shard security remains a concern. While the current validator set covers all shards, future parallelism could induce cross-shard communication latencies if not managed with zero-knowledge bridging or enhanced routing protocols.

The core of NEAR’s smart contract layer relies on WebAssembly (WASM), which allows developers to write in Rust and AssemblyScript. A key technical feature underway is the integration of the FastAuth model alongside WASM runtimes. FastAuth is designed to abstract complexities from end users by integrating account abstraction with native key management. While this supports seamless onboarding, critics highlight potential risks around centralization of authentication layers and fallback mechanisms, especially if tied to proprietary custodial services.

Another active area is NEAR’s focus on zero-knowledge (ZK) toolchains. Though defenses against MEV and ZK rollups are not yet native to NEAR’s architecture, current R&D suggests a strong interest in incorporating privacy-preserving computation and settlement layers. This direction could position NEAR as a potential candidate in layered DeFi stacks that require confidential transaction data but is facing stiff competition from other purpose-built ZK-focused chains.

Storage cost efficiency is also on NEAR’s agenda. With its rent-based storage model—where users pay to keep data active on-chain—there are scheduled updates to allow partial pruning for dormant contracts and orphaned state. While this enhances on-chain data hygiene and incentivizes lean contract design, it introduces developer burden in architecting smart contracts that manage state expiry and cache reconstruction.

Comparisons have been drawn to the adaptive state model discussed in Hedera Hashgraph’s roadmap (https://bestdapps.com/hederas-roadmap-pioneering-the-future-of-blockchain), which also looks to optimize storage-access patterns. However, NEAR’s emphasis on sharded storage execution diverges substantially, particularly in its reliance on WASM rather than virtual machines like the EVM.

As NEAR iterates toward a more modular and developer-centric ecosystem, several underlying mechanisms—from protocol-level crypto primitives to RPC optimization—remain in flux. These dynamics will shape, and possibly challenge, NEAR’s ability to maintain its current developer traction.

Comparing NEAR Protocol to it’s rivals

NEAR vs SOL: Examining the Technical Divergence Between Layer-1 Smart Contract Platforms

When comparing NEAR Protocol and Solana (SOL), the differences are stark in architectural design, consensus mechanisms, and performance trade-offs. Both target high-throughput and low-latency decentralized applications (dApps), but they diverge in how they manage scalability, validator requirements, and developer ergonomics.

Solana employs a monolithic architecture with its Proof of History (PoH) mechanism stacked on top of Proof of Stake (PoS). This has enabled Solana to boast extremely high throughput — frequently over 2,000 TPS with capacity for more — without sharding. However, this design has repeatedly exposed the network to liveness failures. Heavy network usage, validator miscoordination, and resource contention across executables have led to downtime events. In contrast, NEAR utilizes a sharded architecture (Nightshade) that parallelizes execution across multiple shards while maintaining a single chain head. This segregation aims to mitigate congestion bottlenecks but introduces additional synchronization complexity, especially in cross-shard communication.

From a validator standpoint, Solana's consensus model demands high-performance hardware, with GPU requirements for optimal block validation. Validator centralization has become a notable critique since fewer entities can afford such infrastructure. NEAR, by contrast, supports a broader validator set with lower system requirements, bolstered by its dynamic resharding capability. However, NEAR’s reliance on complex sharding logic makes its validator implementation harder to audit and contributes to a steeper learning curve for node operators.

In terms of developer experience, Solana favors Rust as the primary language and supports C via LLVM optimization, optimizing for performance but raising the entry barrier. NEAR offers both Rust and AssemblyScript support, targeting usability. Its human-readable account model and contract-based access management improve composability, though this comes at the cost of slightly increased execution latency due to overhead in runtime orchestration.

Solana’s execution layer is tightly integrated with its Sealevel runtime, enabling concurrent transaction execution on the same state, optimizing for DeFi use cases. NEAR, conversely, maintains serial execution within shards, trading raw speed for determinism and simpler rollback logic.

Both platforms experiment with radically different solutions to blockchain scalability, and while NEAR’s Wasm-based design offers extensibility, it lacks the battle-tested throughput figures Solana is known for — albeit with more consistent uptime.

To explore how divergent consensus models affect network performance, you can compare with innovations like those discussed in https://bestdapps.com/blogs/news/decoding-hederas-innovative-governance-model, which outlines Hedera’s unique use of hashgraph instead of conventional PoS mechanisms.

NEAR Protocol vs AVAX: Architecture, Performance, and Flexibility

When comparing NEAR Protocol to Avalanche (AVAX), a key distinction lies in their architectural choice: NEAR’s sharded chain versus Avalanche’s multi-chain subnet framework. NEAR uses Nightshade, a dynamic sharding mechanism that distributes data and computation across shards, updated by block producers in a single global chain. This design enables horizontal scalability without fragmenting liquidity—a central concern for dApp developers as state-sharing is native and seamless across shards.

AVAX takes a very different approach via its subnet system. Each subnet can host its own virtual machine (VM), tailoring consensus rules and runtime environments to specific use cases. While this offers high customization, it brings substantial complexity in inter-subnet communication. Cross-subnet interaction remains underdeveloped, often requiring manual bridges that introduce latency, potential security vulnerabilities, and poor composability. In contrast, NEAR’s sharded state allows smart contracts on different shards to call each other natively with negligible overhead.

Consensus performance is another battleground. Avalanche uses its Snowman protocol—a linear chain optimized for high throughput and low latency. However, network propagation relies heavily on subsample-based consensus, which can raise concerns around network size, latency sensitivity, and potential centralization of validator sets to maintain performance. NEAR uses Doomslug and a variant of BFT finality in conjunction with its block production, consistently offering single-block finality under typical conditions without requiring probabilistic guarantees. While NEAR's finality mechanism introduces longer confirmation delays under high network stress, it avoids AVAX's trade-offs in probabilistic agreement and validator syncing issues.

On the developer side, NEAR enables contract development in Rust and WebAssembly (WASM) via a high-level SDK, integrating ergonomic tools designed for mainstream devs. NEAR’s emphasis on account abstraction and human-readable accounts (e.g., alice.near) optimizes UX for application-level projects, particularly important in onboarding Web2 developers. By contrast, Avalanche requires deeper blockchain fluency, especially for teams building or managing custom subnets—a major barrier for rapid deployment or projects focused on faster go-to-market strategy.

Finally, despite the power of Avalanche’s subnet model, the fragmentation of validator participation across isolated ecosystems weakens network economic cohesion. Native token incentives can become siloed, and subnet governance splinters consensus, undermining any composability advantage. This echoes critiques levied at other fragmented ledger systems, such as those discussed in https://bestdapps.com/blogs/news/critiques-of-hedera-hashgraph-a-deep-dive, where disconnected governance and isolated state compromise user confidence in broader ecosystem value.

ALGO vs NEAR: Layer-1 Efficiency, Developer Experience & Governance Tradeoffs

When comparing NEAR Protocol to Algorand (ALGO), both emerge as high-performance Layer-1 infrastructures aiming to solve blockchain scalability and usability issues. However, their implementations of consensus, developer ecosystems, and network design diverge significantly — creating unique strengths and weak spots in ALGO versus NEAR.

At the consensus level, NEAR utilizes a sharded proof-of-stake mechanism called Nightshade, enabling asynchronous execution across shards and near-instant finality through its Doomslug protocol. Algorand, meanwhile, employs Pure Proof-of-Stake (PPoS) with cryptographic sortition, randomly selecting validators to propose blocks and vote. While Algorand’s approach yields fast finality (~4.5 seconds) with strong security guarantees, it lacks parallel transaction processing — a limitation when benchmarked against NEAR's dynamically scalable sharding and throughput growth potential.

For developers, NEAR's contract environment is WebAssembly (Wasm)-based with native tools for Rust and AssemblyScript. In contrast, ALGO contracts utilize TEAL (Transaction Execution Approval Language), a domain-specific, stack-based language with a steeper learning curve. While Algorand recently introduced AVM (Algorand Virtual Machine) features to improve flexibility, TEAL still lacks the expressiveness and broader third-party integrations seen in NEAR’s ecosystem, making smart contract development incrementally slower and less intuitive on ALGO — especially for teams coming from EVM or Rust backgrounds.

Ecosystem-wise, NEAR's focus on user-centric onboarding using human-readable accounts and Meta Transactions contrasts with ALGO’s more traditional cryptographic wallet structure. NEAR's progressive UX model, including zero-balance account creation and implicit accounts, lowers friction for non-crypto-native users, while Algorand’s approach prioritizes deterministic, low-cost transactions with sub-cent fees across the board, relying more on external abstraction layers to improve user experience.

In terms of governance, NEAR has progressively implemented on-chain structures to delegate protocol decision-making to token holders via the NEAR Digital Collective. Algorand, while initially more centralized with heavy direction from the Algorand Foundation, has more recently opened up to community grants and developer bootstrapping. However, transparency over validator influence and treasury allocation remains less fluid compared to governance models explored in other networks such as Decoding HBAR's Tokenomics for Future Growth and Decoding Hederas Innovative Governance Model, where structured council-based systems and open treasury management offer clearer community alignment.

ALGO’s strict emphasis on mathematical elegance and minimalism provides security guarantees, but this often comes at the cost of features like dynamic state sharding or richer development libraries, which NEAR incorporates natively. As such, Algorand’s architecture excels in lean, deterministic environments — but may pose constraints for builders needing more programmable flexibility.

Primary criticisms of NEAR Protocol

Primary Criticisms of NEAR Protocol: Exploring Architectural and Economic Limitations

Despite its technological ambitions, NEAR Protocol faces several pointed criticisms from the crypto-native community. These critiques primarily focus on centralization concerns, the architectural complexity of Nightshade, the tokenomics model, and developer adoption hurdles, all of which limit its broader appeal among decentralized network purists and builders alike.

Centralization and Validator Set Concerns

One of the most persistent criticisms of NEAR revolves around its relatively low validator set. Although Nightshade's sharded design is meant to allow horizontal scaling, the actual decentralization of its validator network remains underwhelming when compared to Layer 1 competitors. For a protocol that positions itself as a scalable alternative to overburdened chains, the number of validation nodes and their geographic and institutional distribution are still areas of concern, increasing the surface for potential collusion or censorship. This echoes similar apprehensions found in other high-performance chains such as Hedera. See comparative analysis in https://bestdapps.com/blogs/news/critiques-of-hedera-hashgraph-a-deep-dive.

Architectural Complexity and Developer Friction

NEAR's use of a sharded system via Nightshade theoretically improves throughput, but the added complexity can create significant friction for developers. Unlike monolithic blockchains that offer intuitive EVM compatibility and straightforward interactions with smart contracts, NEAR introduces a runtime and contract model that requires more specialization—specifically in Rust or AssemblyScript. This limits onboarding of Solidity-native developers and poses barriers for teams looking to port applications rapidly across chains.

Additionally, cross-shard communication in Nightshade can become non-trivial, increasing the risk of race conditions, state inconsistencies, and latency layers that complicate performance debugging.

Tokenomics and Inflation Misalignment

Another aspect that invites skepticism is the inflationary nature of NEAR's native token. The emission schedule—despite having deflationary mechanisms like transaction fee burns—still delivers net positive inflation. Critics argue that this dilutes value for long-term holders and fails to fully align with secure value accrual models, especially when staking yields sometimes depend more on protocol subsidies rather than organic network usage.

Contrast this with the tokenomic structure discussed in https://bestdapps.com/blogs/news/decoding-hbars-tokenomics-for-future-growth, where mechanisms for scarcity and utility are more tightly coordinated with actual on-chain activity.

Low dApp Stickiness and User Friction

Despite claiming a developer-friendly experience, NEAR has struggled with dApp retention and user stickiness. The use of human-readable accounts and shared transaction cost mechanics sounds user-centric in theory but diverges from established wallet norms. As a result, experienced crypto users often find the UX confusing, and migrating users from EVM ecosystems becomes a steeper challenge than anticipated.

Without greater wallet compatibility and cross-chain fluidity, NEAR's ecosystem risks remaining in a silo—technically robust but practically underutilized.

Founders

Meet the Founding Team Behind NEAR Protocol

NEAR Protocol’s founding team is rooted in technical depth and academic rigor, composed primarily of ex-Googlers, top-tier ICPC competitors, and veteran engineers with experience across high-performance systems and distributed computing. At the helm are Illia Polosukhin and Alexander Skidanov, two distinctly technical minds whose paths converged to build what would become one of the most developer-focused L1 blockchain ecosystems.

Illia Polosukhin, a Ukrainian computer scientist, brings a notable background in machine learning, including a significant role in co-authoring research foundational to transformer-based models at Google. His history includes work on TensorFlow and natural language processing models, which adds a nuanced approach to NEAR’s vision of integrating usability, scalability, and developer tools. His transition from AI into blockchain development highlights the team’s crossover appeal to modern technologies and showcases a capacity for abstract problem-solving across domains.

Alexander Skidanov, originally from Russia, was a developer at Microsoft before moving to MemSQL (now SingleStore), where he focused on high-performance databases. That experience shaped NEAR’s emphasis on asynchronous sharding and its focus on predictable latency. Skidanov’s practical knowledge of building scalable systems shows in NEAR’s Nightshade architecture and the protocol’s use of WebAssembly for contract execution, grounding its technical stack in performance-tested infrastructure.

However, the team’s strong technical orientation has occasionally been cited as a double-edged sword. Early iterations of NEAR CLI and dev tooling were denser and less intuitive for new developers compared to Ethereum's mature ecosystem—suggesting the initial engineer-first mindset delayed broader community accessibility. Governance criticisms have also emerged, partly due to the opaque nature of early decision-making processes and limited transparency around validator selection and grants distribution.

NEAR’s founders have expressed support for progressive decentralization, yet community involvement in core protocol decisions has lagged behind ecosystems like Ethereum or even Hedera Hashgraph—which has attracted attention for its unique governance model.

NEAR Inc. and the NEAR Foundation also operate as distinct entities, a structural choice intended to balance protocol development and ecosystem funding but one that introduces layers of centralization early contributors must navigate. This bifurcation has been somewhat mirrored in other networks like Hedera, where the interplay between technical steering and foundation control continues to invite critiques on decentralization.

The founding team’s DNA—steeped in systems engineering—has fundamentally shaped NEAR’s architecture and trajectory. Yet, like many technically driven projects, long-term sustainability depends on their continued ability to evolve community governance and developer experience beyond initial protocol design brilliance.

Authors comments

This document was made by www.BestDapps.com

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