DUSK has designed an interesting solution on the DuskDS layer—a single chain that supports two completely different transaction logics simultaneously. One is Phoenix, based on the UTXO privacy model; the other is Moonlight, based on the account-based transparent model. Both systems can switch seamlessly on the same chain.

The engineering difficulty behind this is not trivial. But it solves a practical problem: not all transaction scenarios require privacy. Overly enforcing privacy can actually hinder efficiency and usability. Sometimes you need transparent settlement; other times, privacy must be protected. Supporting both in one system is its cleverness.

Let's first look at Phoenix. It uses a UTXO logic, similar to Bitcoin, but with added ZK-SNARK privacy protection. Each transaction generates a note containing the amount and the recipient's public key, but all this data is encrypted. On-chain, only two things are visible: a commitment and a nullifier.

When you want to spend this note, you need to provide a zero-knowledge proof. You must prove two things: first, that you know the private key of this note; second, that this nullifier has never been used before. But this proof does not reveal the note's actual content—it's quite clever.

What are the benefits of this design? Complete transaction privacy. On-chain, you can't see who transferred how much to whom; you can only see that a transaction occurred. The amount, sender, and receiver are all encrypted. For organizations that need to protect trade secrets, this is a hard requirement. You don't want competitors to figure out your fund flows and transaction rhythm; Phoenix provides this layer of protection.

Moonlight, on the other hand, is the opposite. It uses an account model with fully transparent transactions. Who transferred how much to whom is clear on the chain. This model is efficient and suitable for high-frequency trading and clearing scenarios.

The key is that these two models can switch flexibly. You can choose to use Phoenix for privacy-sensitive funds and Moonlight for transparent channels—based on specific needs. This design reflects an understanding of real-world scenarios: privacy and efficiency are often a trade-off, and there is no absolute optimal solution.