Author: momo, ChainCatcher
The decentralized perpetual contract (Perp DEX) market is currently undergoing a new round of reshuffling. Following Hyperliquid, protocols such as Aster and Lighter have entered the market, disrupting the existing landscape. This indicates that market competition is far from over until the infrastructure matures.
Against this backdrop, Honeypot Finance, a newcomer to the competition, provides a case study. It recently completed a new funding round at a valuation of $35 million, securing backing from well-known institutions such as Mask Network.
Unlike mainstream solutions, Honeypot differentiates itself with its "full-stack" approach, combining an AMM with an order book. It goes beyond simply optimizing the trading experience; it aims to integrate token issuance, liquidity management, and derivatives trading into a cohesive system. Its perpetual contract trading volume has exceeded $20 million since its launch.
This article will analyze Honeypot's products and mechanisms to explore whether its full-stack integration model can establish a sustainable and practical advantage in the current competitive landscape.
From Meme Launchpad to Full-Stack Perp DEX
Before entering the Perp DEX market, Honeypot's core battleground was Meme Launchpad. By creating its star product Pot2Pump, the team directly addressed and attempted to solve the core pain point of the Memecoin economy at the time: how to capture and retain real long-term value for the protocol during a frenzied but short-lived issuance cycle, rather than one-off traffic.
Pot2Pump revolutionizes the way early participants are directly converted into native liquidity providers (LPs), allowing liquidity pools to be created simultaneously with tokens. This design changes the vicious cycle of early Memecoin "scientists" arbitrage and rapid liquidity depletion, transforming high volatility into sustainable fee revenue for LPs.
With Pot2Pump, Honeypot successfully validated an important model: in the realm of highly volatile and game-theoretic assets like Memecoin, a cleverly designed mechanism can guide liquidity behavior and transform market enthusiasm into a stable stream of returns that can be shared by the protocol and the community.
However, Honeypot quickly realized that Memecoin was more of an entry point for liquidity experiments than its final form. The long-term viability of the protocol depends on whether capital can be continuously traded, priced, and liquidated within the system.
Based on this assessment, the team expanded its perspective from single issuances to a complete structure encompassing market making, trading, and risk management, making perpetual contracts a natural choice. Compared to spot trading or single issuances, Perp DEX can sustainably meet trading demand, generate stable transaction fees, and translate volatility into manageable risk exposure.
Honeypot Finance's Differentiation and Innovation
When Honeypot Finance entered the perpetual contract space, it faced two mainstream paradigms, each with its own flaws.
On one hand, there is the order book model that relies on market makers. It is highly efficient when the market is calm, but once volatility intensifies, liquidity can evaporate instantly, causing price gaps and resulting in users being liquidated under adverse conditions.
On the other hand, there's the AMM model, represented by GMX. While it uses oracle pricing to avoid information lag, it makes liquidity providers the direct counterparties to all traders. In one-sided market movements, these funding providers continuously suffer losses, resulting in funds often fleeing when the protocol most needs support.
A deeper problem lies in the imbalance between risk and fairness: to ensure the system does not collapse, some protocols adopt automatic liquidation mechanisms, sacrificing the interests of some profitable players to make up for losses in extreme cases, which raises widespread questions about fairness; at the same time, putting all funds in the same pool indiscriminately also hinders the entry of capital with different risk appetites (especially large funds seeking stability).
1. Building full-stack liquidity: Order book and AMM working together
To address these structural issues, Honeypot did not choose to patch up the old paradigm, but instead proposed a fusion approach. Its core is to build a "full-stack" perpetual DEX, allowing the order book and AMM to work together and automatically adapt to different market conditions.
Order book for efficiency and depth: By partnering with Orderly Network to integrate a high-performance on-chain order book, Honeypot provides traders with a near-centralized exchange experience of low slippage and high speed when market conditions are stable, meeting the needs of high-frequency and professional traders.
AMM provides resilience and assurance: Honeypot's self-developed AMM mechanism is based on a dynamic price band built around the oracle price. When the market experiences sharp fluctuations or black swan events, and order book liquidity dries up, AMM will serve as the final execution assurance layer, ensuring that trades can be executed at any time.
The system automatically selects the optimal execution path (order book or AMM) for users' trades based on market volatility and order book depth, allowing users to obtain the best experience without manual intervention. This truly achieves "efficient trading in calm times and predictable execution in turbulent times."
2. Implement structured risk control: tiered vaults and fair clearing process
Honeypot also thinks deeply about the core aspects of risk management.
They started with the capital structure and introduced a tiered treasury system.
This allows conservative funds seeking stable returns (such as potential institutional capital) to enter the "priority vault," enjoying priority in fee allocation and ultimately bearing losses, thus achieving risk isolation. Meanwhile, native crypto users can voluntarily choose to enter the "secondary vault," becoming the first line of defense in absorbing losses in exchange for higher returns. This design transforms risk from a "passive, mixed burden" into an "active, transparently priced choice."
Based on this, they restructured the liquidation process and designed a "waterfall" sequence with multiple buffers.
When a position is on the verge of liquidation, the system does not immediately trigger a margin call. Instead, it sequentially attempts to reduce positions partially, conduct a market-based "micro-auction" of the remaining positions, and have a secondary treasury absorb the losses. Following this, an insurance pool intervenes as a protocol-level buffer to cover extreme tail-end risk events. Only when all these mechanisms are insufficient to stabilize the system will the minimally impactful and fully auditable Automatic Debt Reduction (ADL ) mechanism be activated as a last resort. This transparent design, which postpones punitive measures, aims to truly deliver on its commitment to "process fairness."
Market feedback indicates that this systematic design, encompassing both liquidity and underlying risk management, is receiving initial validation. According to industry information, the platform's total trading volume has exceeded $120 million, and trading volume since the launch of perpetual contracts has surpassed $20 million.
This data powerfully demonstrates that the attractiveness of its risk tiering structure to sound capital has translated into real capital inflows. Through this series of designs, Honeypot is not only attempting to address existing pain points, but also exploring the construction of a next-generation on-chain derivatives infrastructure that can support more complex capital and emphasizes fairness.
How can token economics and NFT mechanisms achieve a closed-loop revenue cycle?
Honeypot Finance doesn't just aim to improve the trading experience; it's trying to build a self-sustaining revenue system. Its token and NFT designs revolve around the same core goal: to ensure that the real revenue generated by the protocol can be continuously recovered, redistributed, and in turn, support the ecosystem itself.
1. HPOT: As a tool for carrying and distributing revenue.
In many DeFi protocols, tokens primarily serve incentive or governance functions, with limited correlation to the protocol's actual revenue. Honeypot's token, $HPOT, with a fixed total supply of 500 million, is designed as a central hub connecting trading activity and value distribution.
A portion of the transaction fees generated by the protocol in products such as perpetual contracts will enter the All-in-One Vault, where it will be centrally managed and participate in on-chain strategies, thereby transforming into sustainable real yield. These returns are not simply retained but are explicitly allocated. One part is used to buy back and burn $HPOT, creating a continuous supply contraction; the other part is distributed to users participating in the Vault in the form of claimable returns.
In this structure, $HPOT is not just a speculative target waiting for price fluctuations, but a value carrier linked to the actual operating results of the agreement. Its role is closer to that of a "revenue relay" than a one-way incentive tool.
2. NFT: Transforming long-term participation into revenue weighting
Honeypot's HoneyGenesis NFT is not simply an identity or membership credential, but a revenue-generating component designed around "long-term engagement".
Holders can choose to stake NFTs, accumulating yield weights over time; or they can choose to destroy NFTs in exchange for a permanent, higher yield coefficient. This design essentially guides users to exchange time and commitment for higher long-term returns, rather than short-term arbitrage.
NFTs do not emphasize collectible attributes here, but rather serve as a "revenue weight amplifier," making participation itself a quantifiable and upgradable capital investment.
In summary, Honeypot attempts to avoid an "incentive-driven consumption" model, instead building its ecosystem growth on real usage and revenue. The result is not a one-way subsidy, but a positive feedback system operating around revenue recovery and redistribution.
Conclusion:
With its token about to launch, Honeypot Finance is moving from a project driven by early adopters and ecosystem builders to a broader and more complex public market.
Honeypot's current practices have provided a profound example of structural, risk, and fairness considerations for the on-chain derivatives sector. Its core value lies not in the enhancement of a single function, but in a series of coherent design principles:
Firstly, there is the compatibility and scalability of the structure. The "full-stack" model is not only a hybrid solution designed to cope with market fluctuations, but also reserves underlying interfaces to support longer-term and more diversified capital and transaction scenarios. The tiered vault design transforms risk from "passive sharing" to "active selection," paving the way for attracting traditional conservative capital.
Secondly, there is a long-term orientation in the economic mechanism. Whether it's using token buybacks and burns and yield claims to give back to users, or designing NFTs as upgradeable "yield positions," the goal is to build a value loop where "participation equals accumulation." This logic aims to reduce reliance on one-off liquidity mining incentives and explore the possibility of continuing to operate based on real-world use cases and sustainable yield distribution after incentive phase-out.
Thirdly, there is the potential for synergistic integration within the ecosystem. Honeypot's Perp DEX is not an isolated product, but rather a crucial link in its entire liquidity chain, from asset issuance and spot trading to derivatives hedging. This deep integration means that different products are expected to form a positive cycle of funds and user behavior, building a deeper competitive advantage.
But after the initial hype dies down, can Honeypot translate its carefully designed structural advantages into stable capital accumulation, sustained real transaction demand, and healthy protocol revenue? Can it prove that its advocated "process fairness" and risk stratification can truly protect users and maintain system stability in extreme market environments? These questions still need to be validated by the market.
