Warden Protocol @wardenprotocol aims to be a layer 1 blockchain designed with AI integration in mind, featuring the AVR (AI Verification Runtime) plugin and SPEX (Statistical Proof of Execution) verification layer as its core differentiators, allowing off-chain AI models and on-chain smart contracts to interact. The project is based on the Cosmos SDK and utilizes the ABCI 2.0 hooks, with the mainnet targeting the pre-mainnet phase set for Q4 2025. The technical structure centers around the x/async framework and the AVR plugin. Contracts asynchronously call off-chain tasks (HTTP data collection, ML inference, etc.) through x/async precompiles, and after the solver node executes them, it hashes and compresses the intermediate state to return it on-chain. A Bloom filter is used for state compression, and results, intermediate hashes, and model identifiers are submitted together. This approach supports bidirectional interaction and workflow chaining (data collection → model inference → on-chain trigger) compared to traditional oracle dependency structures. SPEX provides sample-based probabilistic verification to handle the non-deterministic outputs of AI. Instead of deterministic consensus where all nodes re-execute the same computation, a random selection of validators checks a subset of states (e.g., 5-10%) to achieve a reliability threshold (typically 99%+) before finalizing the results. In cases where outputs can vary at the sentence level, such as with LLMs, equivalence is judged based on semantic criteria like embedding similarity. This approach aims for performance and cost advantages of 10-100 times compared to ZK circuitization, but due to statistical characteristics, there is a possibility of rare false positives, and oversampling may be required for high-risk transactions. Development and ecosystem indicators are relatively active for a pre-mainnet project. GitHub shows 2,282 commits and 67 contributors, with documentation covering concepts, node operation, tokenomics, and tutorials. Block generation is ongoing according to the testnet explorer, but the number of transactions and addresses is low, indicating it is still close to the demo and validation stage. In terms of applications, the beta app presents external indicators with over 2 million cumulative users, but this includes off-chain metrics based on app and API usage rather than on-chain deployment. The token (WARD) is based on a fixed total supply of 1 billion, with distribution plans presented for public goods, ecosystem, liquidity, developers, validators, finance, and core team. Major uses include public goods airdrops, agent and developer incentives, validator rewards, and finance/R&D, with some categories expanding distribution according to declared vesting schedules. The policy aims to manage long-term token circulation through adaptive inflation (1-10% annually) aligned with staking target ratios (e.g., 65%) and fee burning (around 3%). Partnerships and tool integrations are introduced with AI models and frameworks (Venice AI, LangChain), compute and storage (@0G_labs, TEN, @irys_xyz), interoperability (Hyperlane, Axelar), and data (Kyve, Skip). The goal is to provide an end-to-end agent stack that connects model identification hashes, provable inference logs, and on-chain payments and audits for off-chain computations. The dual compatibility of EVM and CosmWasm appears designed to lower the entry barrier for existing EVM developers. In terms of market and competitive environment, the AI×blockchain convergence market is projected to grow significantly in the medium to long term (estimated average annual growth of 22.93% until 2034), with increasing demand for verifiable AI in finance and logistics. However, there are large-cap competitors in this field (e.g., Bittensor, ASI Alliance, @NEARProtocol, Render, etc.), and if they absorb the verifiable and traceable layers, there is a risk of losing differentiation. Additionally, ZK and cloud-based alternatives could increase competitive pressure with rapid iterative development and enterprise suitability. The risks are clear. First, as a pre-mainnet, performance, stability, and economic design have not been validated under actual load. Second, it is uncertain to what extent the trade-offs of probabilistic verification will be acceptable in high-risk financial applications. Third, regulations intertwine issues of data retention, privacy, and security with multi-chain operations leading to multi-jurisdictional risks. Fourth, limited funding may put it at a disadvantage compared to capital-rich competitors in large-scale developer incentives, marketing, and R&D. In summary, Warden Protocol presents a clear identity with its verification and execution structure (AVR+x/async, SPEX) aimed at bringing AI on-chain. This structure is technically compelling as it aims for a 'verifiable integration' of AI inference and decision-making, complementing the limitations of existing deterministic VMs. However, the success of the project hinges on the execution challenges of mainnet launch, load testing, and the spread of production dApps. In the short term, compliance with the mainnet schedule, securing practical levels of verification costs and latency, and the security and distribution of the validator set are critical, while in the medium term, developer adoption rates and trust cases in high-risk domains are likely to determine competitive advantage. If successful, Warden could establish itself as an 'AI-on-chain intersection' L1 through probabilistic trust, but conversely, if execution delays or competitors' feature internalization accelerate, it may remain a niche infrastructure.