As we wrap up 2025 and gear up for an explosive 2026, I want to take a moment to thank every staker, partner, builder, and community member who has shaped Kofi Finance into what it is today.

What started as a simple idea in making liquid staking effortless has grown into a protocol powering 7.49M+ APT staked, ranking Top 10 on Aptos by TVL.

This year wasn’t just about growth. It was about proving that a small, focused team with an obsessed community can move fast, build boldly, and expand the boundaries of what Aptos DeFi can be.

Q1 Foundation & Testnet: The Spark That Started It All​

In March, we opened our testnet to the world. We delivered a staking experience under 45 seconds, fully mobile-friendly and compatible with every major Aptos wallet.

The response exceeded every expectation:

• 2.1K testers
• 59K APT staked
• $5K+ in bounties
• Dual security audits (Zenith + Ottersec)

From day one, our priority was clear: build the safest, fastest staking experience on Aptos.

Q2 Mainnet Launch: A Milestone That Defined Our Momentum​

On May 14, Kofi Finance went live. Within 24 hours, we crossed 1.5M APT staked, a moment that proved Aptos was ready for a next-gen LST layer.

We rolled out boosted yield campaigns, getting Kofi LST APRs with our partners (Tapp Exchange, Hyperion) above 15% APR. One of our biggest goal was to have stkAPT be used everywhere. We also integrated Kofi collateral into Echelon, Aptos’ largest lending protocol unlocking borrow loops and new strategies for our users.

We also began monthly community campaigns, a core part of our ethos: give value back to the people who trust us early. June expanded our presence globally. We hosted our first IRL meetup in Bangkok. And with the launch of weekly Brewing on Aptos spaces, we established a consistent rhythm for updates and community voice.

Q3 Integrations, Events, and Ecosystem Expansion 🌐​

Q3 was the quarter where Kofi LSTs truly went everywhere, with more partners such as Moar Market, Auro Finance and Goblin coming onboard.

We launched the Kofi Explore Page, a single dashboard for discovering all DeFi opportunities powered by our LSTs. These integrations gave our users yield multipliers and ecosystem points that later translated into major airdrops, making stkAPT one of the most versatile assets on Aptos.

IRL, we showed up strong at KBW and New York, building relationships with leaders across Move and the broader crypto world. We also integrated with Goblin Vaults to offer 1-click LP, making liquidity provision smoother than ever.

Q4 2025 - Media, Influence, and Social Trading Evolution​

Q4 we are now the top 10 dapps on Aptos. We are going capped off the year with something bold.

The launch of our social trading testnet, powered by Decibel Trade.

Because we believe yield doesn’t stop at staking. The next wave of DeFi will be social, transparent, creator-driven, and onchain.

Kofi Live will introduced:

• Revenue models for streamers
• High-value entertainment for viewers
• Smart discoverability
• Responsible, transparent copy-trading tools

Every position is routed publicly through Decibel, letting streamers showcase trades and viewers follow along with full clarity.

Moving into 2026​

From testnet sparks to 7.5M+ APT staked, from two audits to Top 10 status, Kofi Finance has grown into the liquid staking heartbeat of Aptos.

To every user, partner, validator, and builder. Thank you! You’ve turned Kofi from a product into a movement.

And as for 2026? Expect deeper integrations, explosive social trading rollouts, yield strategies that change the game, and features designed to onboard the next million users.

edit (April 22, 2025): Added profitability calculator to help estimate validator profitability at different APRs and APT prices.

Introduction​

As the founder of Kofi Finance, a liquid staking platform on the Aptos blockchain, I enthusiastically support AIP-119, which proposes reducing the APT staking reward rate from approximately 7% to 3.79% over six months. Detailed in the Aptos Foundation's GitHub issue #587, this visionary proposal enhances capital efficiency by prioritizing DeFi and infrastructure, aligning Aptos with leading layer-1 blockchains like Ethereum and Solana. While it presents challenges for smaller validators, we see it as a transformative opportunity to innovate. At Kofi Finance, we're committed to empowering validators with MEV-boosted yields and diverse revenue streams, leveraging our MEV infrastructure to deliver superior returns.

The Vision of AIP-119​

AIP-119 outlines a 1% monthly reduction in staking rewards over three months, with a six-month implementation to foster community collaboration. The current 7% expansion rate limits capital flow into high-impact areas like DeFi, restaking, and infrastructure (e.g., RPC, indexing, MEV). The target 3.79% staking reward encourages more network activity by encouraging participants to explore innovative opportunities that drive network growth, instead of just parking all their APT for "safe-yields"

Challenges and Opportunities for Smaller Validators​

We recognize that the reduction in staking rewards poses a challenge for smaller validators, who may struggle to maintain profitability without the scale of larger players.

The estimated annual profit for a validator can be calculated using the formula: Profit = (Total Stake Delegated × APT Price × Network APR × Validator Commission Rate) - Annual Validator Cost

Use the calculator below to estimate profitability based on different inputs. We've used an average validator cost of $35,000 per year and assumed a 5% commission rate for the defaults and the table that follows (note: the table simplifies the calculation by showing profit based on total rewards before commission for brevity, but the calculator uses the full formula).

At 3.79% APR, 5% commission and at current APT price of $5, a validator would need about 3.7M APT staked to break even.

At Kofi Finance, we're inspired to empower smaller validators through our liquid staking protocol. By delivering MEV-boosted yields, as demonstrated in the table, and pioneering new revenue streams, we aim to ensure all validators thrive in Aptos' evolving ecosystem. The Foundation's community-driven approach, combined with our innovative strategies, sets the stage for a vibrant future.

A Call for a Stake-Matching Program​

To fully realize AIP-119's potential, we urge the Aptos Foundation to enhance its community validator program with a stake-matching initiative. We propose matching delegated stake for smaller validators, doubling their staked APT up to 3M APT where these validators can break even.

This program would:

• Strengthen Decentralization: Supporting smaller validators ensures a diverse validator set, reinforcing Aptos' decentralized foundation.
• Inspire Participation: Matching stake lowers barriers, inviting new validators to enrich our community.
• Better Governance: Empowering smaller validators fosters trust and collaboration, aligning with Aptos' inclusive governance.

New Revenue Streams: Fueling Validator Success​

We're thrilled by AIP-119's push toward a dynamic economy, opening exciting avenues for validators to offset reduced rewards. At Kofi Finance, we're leading with:

1. MEV Capture​

Our MEV infrastructure, leveraging insights from our research with Aptos core engineers, enables validators to profit from transaction ordering.

2. Transaction Tips​

We see tips for prioritized processing as a key revenue stream. Inspired by Ethereum's EIP-1559, we're developing tip-sharing in our protocol, distributing earnings to boost yields for validators and stakers, enhancing our platform's appeal.

Our Role at Kofi Finance​

Our liquid staking protocol, built by a team with expertise in MEV, DeFi and liquid staking, delivers MEV-boosted yields via kAPT and stkAPT. Partnerships with Tapp Exchange, Aries Markets, Joule, and Hyperfluid amplify returns, while our Discord community fosters collaboration. With mainnet deployment, audits with Zenith and Ottersec, and ongoing MEV research, we're aligned with Aptos' vision. By offering tips, DeFi rewards, and infrastructure services, we aim to make Kofi Finance the premier liquid staking platform, delivering yields exceeding 3.79%.

Transaction lifecycle on Aptos​

edited 2025-02-21

On Aptos, transactions follow a structured lifecycle to achieve finality. Initially, transactions are submitted to full nodes, which propagate them to validator nodes. Within the consensus layer—powered by AptosBFT—transactions are collected into a proposed block and reordered using a pre-execution shuffling mechanism to balance the load and enhance fairness. Once consensus is reached among validators, the agreed-upon block, containing the shuffled transaction order and cryptographic proofs, is finalized. The execution engine then processes these transactions, leveraging Block-STM for parallel execution, and updates the ledger, achieving rapid finality with robust security. This design integrates shuffling within consensus to determine the transaction order, followed by efficient execution and ledger confirmation.

Pre-Execution Shuffling

In between consensus and execution, Aptos uses a pre-execution shuffling mechanism to order transactions. This mechanism is used to:

• Balance the Load: Prevent a burst of transactions from the same sender or of the same type.

As noted in AIP-68:

"...This (Long block latency) is expected to happen in this particular situation where spikes of conflicting/sequential transactions from a popular module (smart contract) dominates the traffic"

How transaction shuffling works on Aptos​

Example 1​

The diagram above illustrates how transaction shuffling works in practice. Let's break it down:

1. Original Transaction Order:

   • The top row shows transactions in their original order (0-9)
   • Transactions of the same sender have the same letter
   • Transactions of the same use case (smart contract) have the same color
   • Each circle represents a transaction, with numbers indicating their original position

2. Shuffled Transaction Order:

   • The bottom row shows transactions after shuffling
   • The numbers below show their new positions
   • With sender_spread_factor = 1, transactions from the same sender are spread apart
   • Notice how green "A" transactions that were originally clustered are now distributed

3. Shuffling Parameters:

   • sender_spread_factor = 1: Spreads transactions from the same sender
   • platform_use_case_spread_factor = 0: No additional delay for platform transactions
   • user_use_case_spread_factor = 0: No additional delay for user transactions

4. Result:

   • Transactions from sender A (green) are spread out evenly
   • Transactions from sender B (blue) and C (orange) maintain relative ordering
   • Each transaction is shifted by 1 slot relative to others from the same sender

Example 2​

Let's analyze this diagram which shows a more complex shuffling scenario:

1. Original Transaction Order:

   • Similar to Example 1, transactions are shown with sender (letter) and use case (color)

2. Shuffling Parameters:

   • sender_spread_factor = 2: Spreads transactions from the same sender further apart
   • platform_use_case_spread_factor = 0: No additional delay for platform transactions
   • user_use_case_spread_factor = 1: Slight delay for user transactions

3. Key Effects:

   • "Same context transactions are spaced by 1" - Transactions with the same use case maintain a minimum spacing
   • "Same sender transactions are spread by at least 2 slots" - Due to sender_spread_factor
   • "Both spreads are applied independently" - The transaction will be delayed by whichever spread factor results in a longer delay
   • Some sender spreads "could not be fulfilled" due to competing constraints

This example demonstrates how multiple spread factors interact and sometimes compete, leading to a complex but deterministic reordering that balances various constraints.

More examples can be found in test cases in the Aptos codebase

Live Parameters​

The current live parameters for the transaction shuffler are:

Code

pub fn default_for_genesis() -> Self {
    TransactionShufflerType::UseCaseAware {
        sender_spread_factor: 32,
        platform_use_case_spread_factor: 0,
        user_use_case_spread_factor: 4,
    }
}

Implications for MEV Strategies​

Aptos's transaction shuffling mechanism fundamentally alters the landscape for Maximum Extractable Value (MEV) strategies by introducing dynamic, consensus-driven reordering before execution, building on an initial gas-based queue. This design imposes significant challenges for MEV extractors:

• Reduced Predictability in Ordering: Transactions enter the consensus phase with an initial order based on gas prices, reflecting submitter priority. However, the UseCaseAware shuffler, with parameters like sender_spread_factor (32) and user_use_case_spread_factor (4), then disperses these transactions across the block based on sender and use-case constraints. This interplay transforms the predictable gas-based sequence into a complex, volume-dependent order, making it harder for MEV actors to anticipate final positions.

• Disrupted Concentration and Fairness: While gas offers a starting advantage, shuffling prevents bursts of related transactions (e.g., multiple trades from one sender), diluting opportunities for MEV tactics like front-running or arbitrage. This fosters a more equitable market by reducing the dominance of high-gas bidders who might otherwise cluster transactions for profit.

  The shuffling process—integrated into the AptosBFT consensus layer—begins with a gas-prioritized queue, then applies use-case prioritization (e.g., spacing user transactions by 4 slots) and sender-specific spreads (e.g., up to 32 slots). This layered approach, backed by a priority queue system, evolves transaction ordering beyond simple gas auctions. For instance, a bot attempting to front-run a large decentralized exchange trade with a high gas bid might still lose its edge if shuffling spreads its transaction apart from the target. While this enhances fairness and load balancing, it may slightly delay time-sensitive trades initially favored by gas, a trade-off for resilience.

MEV strategies must now adapt, potentially shifting from exploiting gas-driven order to analyzing shuffle patterns across blocks. As MEV techniques advance, Aptos's tunable shuffling parameters, layered atop gas prioritization, will be key to sustaining an equitable ecosystem, indirectly bolstering network integrity by curbing manipulative reorderings.

Maximal Extractable Value (MEV) has become a crucial concept in the blockchain world, with implications that are particularly relevant for emerging networks like Aptos. As the blockchain ecosystem evolves, understanding MEV is essential to exploring resilient and innovative infrastructure on platforms that are shaping the future — and Aptos is at the forefront.

Understanding MEV​

Maximal Extractable Value refers to the maximum value that can be extracted from block production beyond standard block rewards and gas fees. This potential is realized when block producers — whether they are miners or validators — manipulate the ordering, inclusion, or exclusion of transactions in a block to secure additional profit.

Originally coined as "Miner Extractable Value" in 2014 by a pseudonymous trader, this concept predicted that miners could leverage transaction ordering for gain. It was later formalized in the seminal 2019 research paper "Flash Boys 2.0," which drew parallels between blockchain transaction manipulation and the practices of high-frequency trading in traditional finance.

A brief timeline for the evolution of MEV​

In essence, MEV is extracted through the reordering of transactions within a block, and the methodology of said has evolved over time. Let's take a look at its evolution.

1. Miner Bribing (2015-2022): In the early days of Ethereum's Proof of Work era, users could attempt to influence miners to include or order their transactions in specific ways. This was often done through smart contracts that offered additional rewards to miners for favorable transaction placement.

2. Gas fee reordering (ordering not guaranteed) (2015-2021): Miners typically ordered transactions based on gas fees, with higher-fee transactions getting priority. Users could increase their gas price to improve their chances of earlier inclusion, though this didn't guarantee a specific order.

3. Priority fee reordering (ordering not guaranteed) (2021-present): Introduced with EIP-1559 in August 2021, the priority fee allowed users to directly incentivize miners (later validators) to include their transactions. While higher priority fees increased the likelihood of quicker inclusion, they still didn't guarantee a specific order.

4. Flashbots / Bundling (2020-present): Flashbots introduced a more sophisticated approach to MEV extraction. It allowed users to submit bundles of transactions with specific ordering requirements, providing a more reliable method for transaction ordering and MEV extraction.

5. MEV on Solana: JITO (2022-present): As MEV concepts expanded beyond Ethereum, other blockchains like Solana developed their own MEV solutions. JITO on Solana represents an adaptation of MEV extraction techniques to Solana's unique blockchain architecture and consensus mechanism.

6. MEV on Aptos: ???

Aptos Architecture and MEV Potential​

The architectural design of Aptos, particularly its BFT consensus mechanism and Block-STM parallel execution engine, introduces significant challenges and changes to how MEV (Maximal Extractable Value) can be extracted. These design choices fundamentally alter the landscape of MEV extraction compared to traditional blockchain architectures.

AptosBFT Consensus and MEV​

Aptos uses AptosBFT, a consensus algorithm based on HotStuff, which implements a round-by-round consensus and block chaining mechanism according to Chorus One's analysis. This approach has several implications for MEV:

1. Faster Finality: AptosBFT's design allows for quicker transaction finality ~0.9s, potentially reducing the window of opportunity for MEV extraction.

2. Validator Rotation: The consensus mechanism rotates proposers (aka validator leaders), making it more challenging for a single entity to consistently control transaction ordering.

Block-STM Parallel Execution and MEV​

The Block-STM parallel execution engine introduces a paradigm shift in how transactions are processed, significantly impacting MEV extraction:

1. Dynamic Reordering: The engine may reorder transactions across one or more blocks to optimize concurrency—meaning that the order of transactions might change dynamically between blocks, as explained in the Aptos whitepaper. MEV extractors will need to adapt their strategies to account for both sender-aware and use-case-aware shuffling, potentially reducing the effectiveness of certain MEV extraction techniques that rely on precise transaction ordering.

2. Conflict-Induced re-execution: When conflicts occur, transactions may be re-executed, altering the state that subsequent transactions interact with and potentially invalidating MEV extraction strategies.

3. Ripple Effect: When a transaction aborts due to a conflict, all higher transactions in the block are scheduled for re-validation. This cascading effect introduces further unpredictability in the final transaction order and state.

Why MEV Matters for Aptos​

Understanding and proactively managing MEV is critical for ensuring the success and integrity of the Aptos ecosystem:

• Promoting Fair Markets: By managing MEV effectively, developers and network architects can mitigate economic inefficiencies across DeFi protocols built on Aptos.

• Improve Validator Revenue: MEV can significantly boost validator earnings, incentivizing network participation and security. On Ethereum, MEV Boost has increased validator revenue by up to 75%. Similarly, on Solana, MEV rewards have become a substantial income source for validators, with the network earning $8 million in total economic value from tips and transaction fees in a single week.

As we continue our exploration into MEV infrastructure on Aptos, future discussions will dive into tailored strategies, potential challenges, and innovative solutions to ensure a secure and efficient blockchain environment.