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Unveiling the SUI Blockchain: Pioneering Features and Unique Advantages


Episode 12 - The Open Metaverse Podcast

In this episode, Mehdi Farooq (Animoca Brands' tokenomics team), is joined by Evan Cheng, Adeniyi Abiodus, and Sam Blackshear, the co-founders of Sui, a protocol revolutionizing the blockchain space. Sui is disrupting traditional L1 models by pioneering an object-centric data approach. This innovation allows simple transactions to bypass consensus, effectively enhancing throughput. The throughput of Sui is not only impressive but also horizontally scalable. As more computing power is added to each validator within the existing validator set, the network throughput correspondingly increases. Sui also introduces Programmable Transaction Blocks (PTBs), supporting the large-scale grouping of atomically composable transactions. Furthermore, Sui incorporates user-friendly features like sponsored transactions, making gas costs virtually invisible to the end user. Join us on this episode to learn more about how Sui is redefining the boundaries of #blockchain technology and Web3.

00:43 Decoding SUI Key Innovation - 1) Object Centric Data Model

05:24 Decoding SUI Key Innovation - 2) Parallel Transaction Execution

09:44 How is Parallel Transaction Execution of SUI different from Solana, Aptos, Near

13:30 Special Sauce behind SUIs Tokenomics

16:40 Does on-chain storage allow SUI to also compete with Filecoin and Arweave?

19:09 TPS SUI is targeting by 2025

21:44 Nakamoto coefficient SUI is targeting by 2025

27:14 Best BD strategy for an L1 like SUI 33:55 Dapps on SUI

36:20 Novel innovations stemming from Sui's low latency and scalable infrastructure

37:45 Rapid Fire Round

38:01 Pet Peeve in crypto

40:17 Better Tech or Better Network Effects

41:33 Optimizing for Scalability or Composability

42:08 Favourite thing about Web3

42:54 Question Mehdi should’ve asked but didn't


Mehdi Farooq: Welcome to the Open Metaverse podcast. I'm your host, Mehdi Farooq, Senior tokenomics analyst at Animoca Brands. Today, we have special guests with us, and I'm honored to have them on the show. We have co-founders of Sui. 

Guys, welcome to the show. 

Adeniyi Abiodun: Thank you for having us. Thank you very much.

Decoding SUI Key Innovation - 1) Object Centric Data Model

Mehdi Farooq: I first want to touch on Sue's key innovation, and I want you to explain it to me like a 10 year old. So the first key innovation I want you guys to explain to me is object centric data model that you guys have developed.

Evan Cheng: So let me take a, from a very high level point of view first, right? Uh, if it's explained to a five year old. So everybody talks about blockchains power as being tokenization assets, right?

So when you think about how tokens work today on all the other blockchains, like EV and chains in particular, right? Tokens sort of represent. An ownership in your underlying asset that lives off chain, right? And that means you can only tokenize assets that's basically finalized. That's already completed.

That's not gonna change. It's not going to incur, you know, you're now attaching more information to it, which is a very, very big limitation. If you think about it, right, if you're thinking of signing a business contract, you have parties, counterparties, you have this process where you accumulate a lot of information along the way, and then at that point in time it's finalized.

So, that's very, very different. Uh, that's very limiting. Even thinking about using this as a business contract, uh, for, you know, as, as something for kind of tokenizing a business contract. So, uh, we build SW to really change that, right? So when you're thinking about an object centric model, you can accumulate a lot more information.

You keep a lot more information. The developer can define it onto the chain, right? What the asset looks like, what actually fills the metadata. Actually, you know, Captures and if you want to append more information to it later on, you can basically attach another object to it, right? So think about something as trivial as, uh, an asset such as a baseball car.

Uh, if I have two identical baseball card, both pristine, you know, you create them as let's, for the lack of better turn, AFTs later on, I want to, I meet that baseball player in real life, I should be able to pull up my phone, look at my. A f t, that's your baseball card. Can you sign it for me? And that adds more information, and may add more data to that object, to that asset that makes it hundred times more valuable.

What's the equipment? This in the blockchain world? So tokenization, the model that. The work in the past with all these blockchain opinions just fundamentally is very flawed. So, uh, and that's very limited and that's the primary reason why we haven't seen much innovation, uh, in terms of user, consumer facing product as a result.

Uh, another thing that's very, very important to know, right? What comes along with an asset, Rules around the asset. Right? What are the rules you have to satisfy before you create the asset? What are the rules before you can transfer the asset to another party? Uh, just look at the issue with a FT Markets, right?

Right now what we're seeing is the marketplace decided they're not gonna pay royalties because it's fundamentally misaligned with their interest. They want to increase the volume of trading. They don't care about satisfying the demand of the creator of the asset, which the creator says, pay me royalties.

When they're a secondary sale. Everybody in art knows that's where you make the money, is collecting royalty in secondary sales. But the marketplace decided, eh, not gonna do it. We're just gonna do whatever you want. What is the whole point? This we go back to centralization. Uh, so you have to enforce rules around this asset, and the only way to do it is embedding this restriction, these rules, verification inside the smart contract that defines the behavior of these assets.

Now rely on it. Sort of essential social consensus among all the players such as marketplace, such as everyone else is involved in the transaction to be the good player, right? Again. Uh, so that might be a long answer. Hopefully it's not, you know, it's clear to you, uh, you know, this is a very, very different way of thinking about, uh, the blockchain.

Uh, cuz ultimately a blockchain is useful for, as a platform for this inter. Intermediation of assets and in opinion, all the blockchains have failed at that.

Decoding SUI Key Innovation - 2) Parallel Transaction Execution

Mehdi Farooq:

So, so, so a follow up question on, by the way, it's a, it's a good explanation. So a follow up question that naturally comes after this is, uh, within circles, the most disgusting about sui is peril execution. And an object centric data model actually helps with that. Uh, so can you also explain to our audience what is peril execution and, and how does the DA data model help with that? 

Sam Blackshear:

Yeah, sure. So I can go into more detail on that. So, right. If you look at what a blockchain is doing from a competition perspective, you have a transaction, it's creating assets, it's reading and writing.

Existing assets are deleted. That's sort of all it's doing. And so when you're talking about parallel execution, what you wanna know is when can two d, when are transactions touching distinct objects? And when they're touching distinct objects, that's when you can do parallel execution. If they're touching the same object, then well, maybe you can, maybe you can't.

It depends on the flavor of operation, but like the flavor of parallelism that's most useful is, Hey, these are touching different things, so I know I can do them in parallel. And the way the object centric data model helps us with this is that. Each transaction specifies the objects that it's going to touch.

It says, Hey, like, I'm gonna use this NFT that I own. I'm gonna be touching this marketplace. Uh, I'm probably gonna be putting in this Multisig wallet. And this is transparent in the transaction format. You can see it without even running the transaction. So from the runtime perspective, we have a couple of different tricks that we play.

So one trick, and this is probably the one you've heard about the most, if you heard about Swees, sometimes we don't, for certain types of computations, we don't need full consensus. If you have a transaction that's only touching single owner objects, maybe it's an N F T transfer. Maybe it's combining two coins, um, maybe it's doing a payment, things like that, then we actually don't need to go through full consensus at all.

We can use something called visiting consistent broadcasts. That's a lot lower latency, and that's trivial, paralyzable, you just say, okay. Every, every transaction that falls into this bucket is paralyzable by construction. And we see in practice that many, many transactions fall into this bucket. And then for the, for many other cases we have, you know, we pass on, it's not inherently paralyzable because it has what we call a shared object.

Maybe you have a Dex and there's two different users that are making a trade on it. Well, you know, we have to sequence those trades to see who gets which price. Or maybe two folks are trying to buy an NFT in our marketplace, and we have to know who bought it and who, um, misses buying it. And so what we do there is in other blockchains, these, these transactions would all be sequenced with respect to each other.

And we'd either be executed sequentially or sort of try to discover the parallels on the fly. Whereas for us, we can see. We just generalize the logic that we're using for single owner objects a bit. We say, okay, if you're touching distinct shared objects, I can run those transactions in parallel, no problem.

And if I'm touching the same shared object, then we have all sorts of execution strategies that we use. You know, we sort of have worker threads. We throw transactions that are touching the same object on the same worker thread, and other ones get run in different threads. And so we maximize the parallel as much as possible.

And then the other thing that this lets us do, which is quite interesting, is. Okay. Like if someone gives you a workload with a lot of parallelism, great, you can execute it in parallel. But the thing in blockchain, a lot of the workloads that are doing touching shared objects are creating a lot of contention.

So you wanna have your economic model also hooked into this and make sure that you're incentivizing users to give you workloads that don't create a lot of contention. And so what we're doing is something that we called. Object centric fee markets where we sort of track the hotness of a shared object, like how many transactions have touched this, uh, in the last couple of checkpoints.

And then you have to pay a higher gas price to have the transactions touching that hot object, um, be executed in. In a fashion with the better quality of service. And so what this does is if there's some hotness that's going on in some area of the chain, uh, it's re the gas price will go up there. But the gas prices that are touching other shared objects that are under normal operation that aren't hot won't go down.

And there's a huge problem. And basically every other blockchain where it's like, oh, you know, you have something really hot that's going on and the chains, uh, even if you have para execution, the chain slows to whatever its sequential throughput is. And we have this economic feedback mechanism that will prevent that from happening because the prices will basically go up in one spot, but then the other lands will just keep running long at full speed.

Mehdi Farooq:

So, so am my understanding is correct. Does that lead to a local and a global fee market? 

Sam Blackshear:

Yeah, that's right. So it leads to, I guess, these hyper-local fee markets. So the fee markets can be per object or poor collection of objects, that there's a lot of shared objects that tend to be used together. Instead of having something global where, you know, the analogy we like to use is if, if there's uber search pricing in San Francisco that shouldn't make that, like, that shouldn't cause there to be Uber search pricing in New York.

Uh, but that's how, but other blockchains do work that way because there's a globalism and so we're doing something a lot more fine. 

How is Parallel Transaction Execution of SUI different from Solana, Aptos, Near

Mehdi Farooq:

So just to understand this better, how, how is the per execution of why we different from some of the other competitors, like near is using shorting Aptos and Solana also using some different approaches.

So can you just highlight to audience what are some of the similarities or differences, uh, in, in terms of the approach SWE is taking? 

Sam Blackshear:

Yeah, so I think the, each of these is doing something quite different, and so like, uh, I could talk through each of those, but I think it's easier to paint with a broad brush on their general themes.

So I think the general themes are, so the biggest general theme is I think this thing of can you hook in, can, does your economic model prevent hotspots? That's something that we're doing. That's something that Solana is also doing. You know, they have these local fee markets that have been rolled out recently.

I think that's extremely important because otherwise you're relying on your users to give you, A workload with a lot of, and uh, we've seen, we've seen from the way folks use blockchains, that that just won't happen. So I think like, you know, check mark for say the Solana and for SWE on that and on that point and not for others.

And then this is related to this concept of optimistic versus pessimistic parallel execution. If you know upfront what a transaction's gonna do, then you have perfect visibility into, okay, you know, this is touching something hott, I should charge more for it. Whereas if you have something that's doing optimistic execution, You're gonna discover that you're creating contention at runtime when it's already too late to punish.

Punish the user by charging them higher fees. So I think that that's another important access to consider here. Uh, and something that, uh, that we're doing with Swei. And then in terms of, and then in terms of starting this is, you know, this is not the same thing as pro execution, but closely related, like an important problem is, okay, if your strategy for pro execution is I have everything in memory and, and trying to do something optimistic by, you know, sort of detecting conflicts in memory on the same machine, that's hard to scale up, uh, because you have to keep getting a bigger and bigger machine and more and more cores.

Whereas if you have something where, The data model lets you do cross machine charting, uh, and this is the direction we're going eventually. I have 20 machines, and then like, these machines are responsible for these shared objects, and this machine is responsible for these ones. And each of these is independent workers, and I know where to throw things so I can schedule them in parallel.

Then that's a very different approach than something that's detecting conflicts in memory. 

Evan Cheng:

I'll say something more, just kind of summarize it. Um, execution usually is only a small part of the entire transaction pipeline. It's often not even the bottleneck. At least based on our, our data, uh, Execution is only a small part.

Uh, we can potentially paralyze the entire pipeline of transaction processing, not just execution. Because we have, uh, dependency information, we can aggregate transactions, uh, processing based on, uh, actually dependency, not having to do total ordering of unrelated transactions for us.


Adeniyi Abiodun:

And that benefit here is ultimately, um, SWE gets to behave, kind of like you expect a really large distributed database that large companies already run.

So with Google or Facebook, as you have more load, you throw in more resources and you can take on the load. At Christmas, if everyone's, uh, posting pictures, you need more machines to manages, um, their increased load. And when Christmas is over, you can turn those machines off. That's kind of like how people should start thinking from a suite perspective because we enable.

Validate to essentially scale up, um, um, their resources to accommodate for the increased demand. And similarly, the economic models been designed as such a way to take advantage of that, namely the price that you pay for gas is pretty much flat. Um, over and over again, unlike traditional blockchains where things, you know, the fee, depending on the price of the token, can really get away from consumers.

Whereas in swe, even as you see volatility in the price of the token, you shouldn't see vol. You shouldn't see great, um, difference in price that you're paying for gas from a dollar perspective, which we think is a better form of UX as well across the board. 

Mehdi Farooq:

Um, so you did highlight the economics of the gas fees.

Uh, I would also love to learn more about the storage fund, which I think is, is, is pretty noble. So if you, if you guys can highlight like what's happening there in terms of tokens and economics behind that. 

Sam Blackshear:

Okay, so let me backup and talk about the problem that the storage fund is trying to solve. So there's basically two different things that we care about, right?

One is making sure that folks have an incentive to clean up the, the crop that they leave on the blockchain. Um, and then another problem is the, the sort of, I call it a time travel problem where if I'm a validator today and someone allocates a bunch of storage, um, You don't want it to be the case that that validator gets paid by the gas fees of the current transaction, but then some different validator, you know, two years in the future that's still storing the same thing, has no economic benefit from that, that that doesn't work.

It doesn't help validators, uh, fund their operational costs or set up storage for the long term. So the way we solve both of these problems is with this storage fund mechanism. And so what happens is when you send a transaction and it creates some objects or otherwise allocates some storage. Each object remembers, Hey, I've paid this many suite to allocate this object.

And we basically have a price per bite. And then if you come back and later free that storage, then you get a refund. Not quite a hundred percent, but I think today it's 99% of the amount that you paid. So that way you're not just gonna leave objects sitting around because you're literally leaving money on the table.

Uh, your incentive is to free these objects and reclaim the the storage fee. And then the other thing. And so that solves the cleanup problem. And then the other problem of this like tran of having this transfer across time, when you pay this money, it doesn't go to the current validators, it goes into a big pool on chain.

And that's what this storage fund thing is. And the current validators, they earn staking rewards from the funds that users to stake with them, but they also earn staking rewards on the money and the storage fund. And so what this does is it creates this professional revenue stream that's proportional to the size of the, the data the validators are storing.

So they don't have this issue of, oh, you know, um, the, I'm having, having to store terabytes and terabytes of data, but they're, no one is paying me for that. Like, they'll get stick awards that are proportional to the size of that storage fund. So the, our brilliant head economist, Alonzo, came up with the scheme. I think it's quite clever and we see it working out pretty well so far. 

Adeniyi Abiodun:

Yeah. Interesting thing about that. If you think about NFTs, right? You have a bunch of NFTs sitting around. Um, some that I have no value, some with value. And imagine five years time, you know, the U NFTs no longer popular, no one's, no one's really trading it or no one's has much interest in it, but the amount of storage that it consumes is a, is significant enough where you just think, well, if I just burn this nft, I will get the SW token at least 90 to nine point.

9% of the suite back that was used to pay for storage, which is quite an interesting way to imagine what UX people could build there to give you an idea of, uh, here's this value, this NFT, why don't you just destroy it and get some money back rather than keep it lining around. Um, also it, it gets people thinking separately about what storage really means.

Uh, if you're paying for storage, you can almost argue storage is relatively free. You're holding some capital on a table to store, um, uh, an asset. And once you clear that asset up, you can get some of that. Storage back. So we, we built SWE to enable people to store the JPEGs on chain. You can actually store more complex data structures on SWE than you can on other blockchains, and that allows you to create more innovative ways of engaging with consumers.

So we're very excited about that. 

Mehdi Farooq:

So, so a follow up, is that in terms of a tam or in terms of the opportunity, many L ones do not have on chain storage. And then some of the competitors out there, let's say RV and, and Filecoin has on chain storage. So in terms of the TAM available, is it, is it, is there a correct mental model to kind of think ofWe as a hybrid of L one as well as a.

On chain, on chain storage is, is the right way to think about this. 

Adeniyi Abiodun:

I, I'll probably say no in a sense that, you know, if, imagine what you do in the CM today. You store a record of ownership and then you store a link to some JPEG on ipfs. Ipfs. It's great for that, but really that asset is really static. I think the value that's true Suite brings is you have assets on chain that are no longer static that can actually be dynamically.

Change with respect to how you engage with them, which is way more valuable than just dumb storage. So we like to think SWE is a better model in the sense that, you know, you have, you know, really, you know, dumb block storage that is always gonna be there if you just wanna have static assets and never change.

But if you want assets that have behavior, uh, mechanisms where you can dynamically change 'em based on how the N F T performs, or there's a game that wants to change the look and feel of a character over time, that's more valuable in terms of storage. And, you know, it's, we're not, I don't think we're arguing as we will be cheaper than ar we, it certainly will be a lot cheaper than, um, storing on Eve or Solano any of the other blockchains to a large extent, right.

So, and then you, you, you add on the fact that you can get money back if you destroy, uh, assets. It's, it's an entirely different game. Evan, sorry, didn't cut you off. Yeah, yeah. 

Evan Cheng: Let me add on to it. Right? It's coming back to our first conversation. We talk about tokenization on token is very static. It's very one-dimensional.

Uh, so think about it, right? You know, when you find things, it's object, right? And the objects are virgin, right? So when blockchains are basically ledger the tracks, the history of. Transfers of the static asset, you add a dimension beyond that, you're also tracking essentially the state changes of these assets on chain as well.

So that's the better way to think about it. Uh, we are now trying to build another blockchain that basically do very, very basic stuff, right? We're tracking the record of how these static assets are changing hands. Right. We are also changing tracking, basically sort of almost like having another ledger for each of the assets, track the history of how these assets changes over time.

So that's the way to think about it.

Mehdi Farooq:

Excellent. So I, I, I wanna go back to horizontal, um, scaling. Um, so hypothetically, imagine we are in 2025. Uh, so what will be the North Star in terms of TPSs, uh, that Swei will be targeting? And when I say tps, I, I'm, I mean, average of, let's say simple transaction as well as complex transaction combined together.

What will be the North Star for you guys 

Evan Cheng:

In 2021, there's roughly 5 million activities that happen per second, uh, in the act. In the internet, right? So the activity can be a Google search, can be, uh, liking, uh, Instagram photo, can be watching, uh, TikTok video. Um, you know, these days can be probably increasing.

So on one hand, that's no North Star. On the other hand, that's completely wrong way thinking about doing things right, because TPSs is not going to be this. Sort of thing. You look at when this space matures, when you're thinking about using infrastructure, you don't ever think about capacity being a limiting factor.

You want to think about what they can do for you, uh, and you want to, depending on them as your business grows. Right. There's just never gonna run out. So this is why horizontal scaling is very important. It's not just horizontal. It's horizontal and done by on demand. When you need to increase capacity to meet demand, you can increase on the spot.

That is the important feature you're looking for. Now, oh, next month or next. Few weeks on down the road, I can increase my capacity to meet the demand that's coming today. That's completely pointless, right? Because when you have infrastructure that doesn't meet demand, you have failed completely. What we're seeing today on Ethereum is complete failure.

Uh, people talk about it, uh, in a way that's almost like good thing. It's not, it's terrible, right? This prevent real product builder, they want to build a business from using your infrastructure because you cannot allow the underlying infrastructure limitation in capacity to stop you from making business, right?

Stop you from serving your customer. Um, so I think. I hope, uh, in a few years time, people don't talk about TPSs. People just talk about, you know, is this a infrastructure, a blockchain infrastructure has uptime, has a guarantee to service my product, right? And that's the one only important thing that we should care about.

Mehdi Farooq:

So, to follow up on that, since we are in, in, in web three business, Um, let's say we have that infrastructure, which is scalable enough to support many businesses. Is there any nakamoto coefficient, like, which is sufficient enough that that allows that security, that that trust, um, guarantees whilst having that scale? Like is like, do you guys have any uh, north Star for that? 

Evan Cheng:

So here's another thing we think somewhat differently from everyone else, right? Can you have, you can have several thousand validators and all that, but we all know because we're in the Byzantine, you know, kind of model only the truth. The majority, we have the most, you know, kind of voting power can make the decision.

So, So what we do is we want to encourage open market co, you know, dynamics, uh, for everyone that, uh, everyone that that runs a do run a validator to want to be in the top two thirds. So they can actually actively gain involved in the TR transaction processing, right? Because they can get the booster reward, which then pass on the booster reward to their, you know, their customer, that stake.

With them, right? So that's very important. This is why this model where you've perpetually sort of incentivize validators to be, to be writing a note is, is a bad one because you know, once you fall out that top one third percent, you don't actually have the incentive to improve among your service. Right.

We're seeing this a lot, right? You can have multiple, many, many thousand validators. The one have 0.01% just collecting money for nothing, for doing no work, right? You're kind of in the validator set, but you're doing absolutely nothing. You never called upon to vote. You never call one to do anything, and you don't have incentive to improve a young upon your service because I'm getting money for free, right?

So, uh, we think this is a wrong model. Uh, so. You know, we want sufficient, uh, you know, degree of decentralization, nakamoto, you know, kind of numbers are important. Uh, this will increase over time. But the most important thing, what we want to see is open, uh, market dynamic where the validators are working hard to improve on their service, to offer their customer better.

Returns. So more people stick within so they can squeeze into that top, you know, two third or whatever the number. So they actually participate in the consensus, in voting, in everything. So then they gain more business, right? So that dynamic between the validators is very important. So that is the model we are, uh, kind of utilizing.

Adeniyi Abiodun:

Running a valid data inwe o over time is actually gonna be very competitive because there are a few things you gotta keep, um, aware of as a validator. One, you're gonna be actively called to vote on what the gas fee should be for transaction. That's something where it's gonna be dynamic. You're gonna be pricing gas fees relative to your infrastructure costs, so you're incentivizing people to run.

Efficient infrastructure that scales, but also is something they can make money on. And if you are running very expensive hardware and you can't com compete, you'll be kicked out of and run outta business very quickly. So there's a, there's basically a market to compete as a validated from that perspective.

Also, if you don't scale your hardware fast enough and everyone else is, Plus more transactive than new. Then what happens is you essentially get slashed as valid data and you start to lose reward. And hence you would have a sufficient amount of vote, um, um, stake leaving your val data and going to others who are scaling the infrastructure.

So one where, Theos has opened a way to encourage validators to run efficient hardware and be profitable. Secondly, it encourages them to actually scale the network as the demand actually increases and the requirements for applications increases over time as well. So it's not a network where you sit, there have been a dumb validator and do nothing.

There's element of like participation that's required on a regular basis from Val to Swei. Sam, you wanna go ahead? Yeah. 

Sam Blackshear:

The thing we really think about as the North Star with respect to decentralization is about third party validation of state. Like, you know, the, we're talking about how a validator is gonna be really competitive, how you need a lot of operational sophistication.

Well, decentralization is about allowing anyone to participate. Not everyone's gonna be a Google or an Amazon or like a sophisticated validator that can run a cluster, uh, or a small data center. But we do want it to be the case that everyone can. Validate the network or validate the subset of the network that they care about.

So one important thing that we're doing along these lines is leveraging our data model is introducing this new kind of node that's like a full node, but we call it a sparse node where instead of validating all the network traffic, where if you're pushing hundreds of thousands or millions of tps, like that's gonna be expensive to do for a third party.

You can say, I would like to track only the state related to these objects or to these addresses. And you can do this on sort of an a, an individual level, like maybe a, A wallet is a sparse node that tracks the address that it's spending for. Maybe a game developer is a sparse node that tracks the objects involved in the game or the NFTs of that game issue, so the player objects or these sorts of things.

And then you pay a cost for validation That's proportional to the amount of traffic that's going through. Your particular objects or addresses of interest rather than the network as a whole. And we think this is the way you really get to decentralization cuz anyone can run on their phone and have a completely verifiable view of everything that happens to the things that they own for the, to the things that they own and not have to worry about the rest of the network.

So that's really the thing that we focus on the most. I mean, of course like there are many, many facets to decentralization, but like that's a thing where even as these networks really scale up, we think can still be tractable to, for everyone to do. 

Mehdi Farooq:

Excellent. Um, so we did discuss a lot on the system side of things, so I, I wanted to now discuss a bit more on the business side of things.

Um, So, so what is the correct business development strategy for layer one? Like, we are seeing different approaches being taken by different L one s, like some are focusing more on web two, some are focusing more on web three DGen types of folks. Uh, some are focusing on accelerators hackathon, some are focusing on grants to web two, uh, projects.

What's, what do you guys think is the best way for L one to scale in terms of network effects and, and from business development standpoint? 

Evan Cheng:

Yeah. So, so I, I want to take this, uh, from the top level, which is sort of describe what each of these, sort of participating in the network, what their roles are, right.

So, uh, why is it important to have a, a, a, you know, big ecosystem? A big community, they basically solve the CoStar problem. For the developer to, basically, these are the same base that's going to be purchased. Their wares, uh, gonna be participating in their offerings. So that's very important to continue to grow their community.

And it's also very important to grow the bigger, the developer community. Um, because ultimately each one, the layer ones is a developer platform, right? The only way for layer one to be successful is for more and more specifications, reach the. The audience, uh, that you generate more fees and more activities on gym.

So that's important from both angles, right? You do need people who are independent, small startup enthusiasts, right? They really, really fundamentally understand what is it they want to build. What is they want to change? Uh, they're more willing to try new ideas and try things. They tend to iterate much quicker.

But on the other hand, right, building a product is very complex. Look at all the gaming in the space.The independent studios just can't do it, right? Because gaming takes a lot of money, a lot of time. So you also need to be, bring more established, established players. Um, You know, veterans have built games before, uh, to come into the space and ultimately you bring the two sides together, right?

That makes a healthier ecosystem, which in turn bring other developer tooling, uh, you know, kind of service provider into the space. Because when you're thinking about building a developer platform, right, you build underlying technology, you build the essential tools and the essential libraries, reusable blocks, and early on you have to build.

Build a lot of bespoke solutions for your partners to show them how to build these kind applications, how to build new kinds of product. But that's not really where you want to go for the long run, right? You want to abstract away all those complexities. You want people providing tools, ready to use libraries and all that, and they require third party application, [00:30:00] I mean, developer, tool provider to come in.

So that's. We are at the stage, we're basically cranking the flywheel, right? Getting all the activities happening on G, getting all the community coming, getting some big companies to experiment with new ideas, and then it becomes more vibrant ecosystem. Uh, You know, people will build more layers on top of it to abstract away blockchains in the long run.

If you want to build a webstream enable product, you shouldn't have to think about writing your smart contract. You should be thinking about these are the building blocks are used, these are the things I work together. Kind of like how Web two company build. Products where you think about, do I use React native for my front end?

US use this backend, this kind of service, this kind of, you know, product. You don't think about writing underlying protocols yourself. 

Adeniyi Abiodun:

Yeah, I wanna broaden that in the sense that I, I, I think there's a lot of over-indexing on the existing market that exists today, namely the market that gets people generally excited, which is mostly, um, defi DS and NFT enthusiasts.

We, we like to broaden that market. Uh, our goal when we set up to build Mis and Labs is to build the infrastructure that makes it possible for people to make as a ownership. Occur at scale. And to do that, you have to make it possible for existing, um, businesses to integrate with Ledger at scale. And there are two, well, actually a few things we've been doing along those lines.

One, it's the idea of sponsored transactions. And in Swei, every, you don't have to write a special contract to enable this, but every asset in Swei supports the idea of gas list transactions, if we wanna call it that. And the idea is that I can, as a consumer, engage with a smart contract and gas is completely hidden away from me.

Another account pays it on my behalf. And that's something completely transparent to the user, which is a big barrier to entry for many consumers. Imagine you wanna onboard them into an experience. You ask them to go to an exchange to buy a token before they can start engaging. That's just a non-starter for like, Four, three to 4 billion people in the world.

Um, secondly is the idea of, um, even, um, on on chain identity. We believe the way to actually scale web three is allowing to you to existing identities. So for example, we, you know, there's something invented by missed and recently called zk login. And what ZK login does enables you in. In a completely decentralized form, but using only the chain as the authenticator to basically verify your existing web, two credentials to create an a, um, an account on chain.

So the use case is I wanna onboard into a game rather than being asked to Reem remember some mnemonic or some br bring up some latest device. I don't even know if the experience is gonna be valuable yet. Why don't I just let people sign in with Gmail? Facebook id or even, you know, any kind of, um, primitive that supports, um, you know, open id, um, connect.

That's something that's gonna be supported on swe. Namely now it means anybody with a web two identity, uh, amongst those partners, which is our many, uh, it's at least, uh, a billion and a half people in the world can [00:33:00] leverage their existing identities that they've. Spent time curating in web two to engage in web three and not thinking about the chain.

So you have two things. You not worried, you're not, as a consumer, you're no longer thinking about gas, and you're also no longer thinking about, you know, some crazy, um, credentials you have to keep in store under your bed. So that is a web two experience and we've always maintained. Web two has great product experience and I think Web Three needs to catch up there.

Web three has a lot to offer in terms of decentralization and ownership of assets and agency over ownership that we think Web two Disk doesn't give. But what we're bringing is the web two experiences natively on chain. You do not have to use some third party vendor that is to be something you, you can engage with on day one.

And that's, uh, that's something we're very excited about, namely, Just bringing in more, you know, day-to-day users to leverage Swei and the fact that it's very low fees means use cases are previously were not possible, are now possible on Swei as 

Mehdi Farooq: well. Yeah, yeah. Uh, talk about day-today, users. If I were to go and explore Swei ecosystem today, what will be some of the dabs you'll recommend? I'll explore apart from the z. 

Adeniyi Abiodun:

So there are a few things that you can explore on, on, on Suite today. There's Suite Friends, which is a showcase that we built that, um, is an NFT project that enables you to engage with assets on chain. Namely you can buy an NFT and over time you're able to have um, um, Accessories to it that you can basically onboard.

And you know, whether it's a shirt, whether it's, whether, whether it's um, you know, a shoe, whether it's anything that's consumer related, you can a ado your NFT with that. And the reason why we've built that crafting tool is it's, that's gonna empower games to think about how they enable crafting within the games directly on chain and monetize that.

Um, they're also, of course, defi, you know, there's Kirk decks, there's um, of course there's Deep Book as well that we've, that is being built as well on Suite, which is a decentralized cent limit order book they can use on, they can use on swe. Um, beyond that as well, we have a few other applications in a, in a sense of, if I really off my head, sweet friends suite, name Service Worm, home Connect Turbos, um, which is a defi, um, pro protocol CSS Finance, which is, I, I think they've already got over 30 million worth of liquidity.

Clutchy was an NFT marketplace, SWER, which is a social app and enables it to build online communities, one mind and NFT marketplace keepsake. So, We've seen the ecosystem grow. I think we captured over 200 apps already have signed onto the Umwe network, um, um, website, and that's only growing over time. So there's been a ridiculous amount of growth in ecosystem so far.

Evan Cheng:

So starting from the fifteens, I think the gaming partners gonna start launching, I think two per day for from the fifteenths.

Adeniyi Abiodun:

Yes. So I can even, I can even give you some alpha, right? The, I think between, um, I believe between the. Between the 15th and the 21st, there's gonna be final star dust product in Loon and run legends.

So that's by orange, um, our event and Toho games. And then all the way even into, um, June we have, um, you know, one net lucky cat and orange Come Love. [00:36:00] Releasing the walkin dead pan. Dogs on, bushie on. So at least 14 games over the next like six weeks are gonna be launching on SW with two launching every, every single week.

So there's gonna be a drumbeat of activity and new experiences that we think are gonna be super excited for consumers. 

Mehdi Farooq: Okay, this  is what I'd like to hear. Um, so apart from, apart from these, um, since, since we have a very scalable infrastructure and, and we have very low latency, what are some of the unique use cases that, that you guys are excited about that we haven't seen yet, either from a token model standpoint or a business model standpoint, uh, that hasn't been popped up and you guys think in the, in the future because of this infrastructure will be something to kind of look forward to.

Adeniyi Abiodun:

Well, there are a few things being worked on by our cryptography team that we can probably share more details soon, but one of them is like private NFTs and time capsules, and with private NFTs, what it means is, you know, I own an asset, but only I can see the high resolution version, or at least something private about that NFT as an owner.

Whereas the gen general public has no idea what the asset is, but they could only see partial elements of it that's gonna inc. Create new forms of activities for N F T ownership that we think just don't exist today. And then you add on top of that what we call time capsules. It's the idea that, you know, some element of the asset can be revealed in the future time.

So I will send you something today and maybe on your birthday you'll be able to unencrypted and see what, what's inside the box. So imagine given red letters and they could only open a certain days that you know what amount you receive or what value you receive on a particular day. Um, We, we think, you know, web three should be fun and, you know, we, they call us a gaming blockchain, but we, we are more than that.

I think everything we talk about here permeates just basic asset ownership of NFTs. It permeates everything you could do on a day to day basis. 

Mehdi Farooq:

So the last segment of the podcast is a, is a rapid fire round. Typically, we do it one-on-one and sometimes, uh, two on one. So in, in, in our case, we have, we have three, three people.

Maybe we start with Evan. So this will be like a short response answer. Right? Um, so, [00:38:00] so the first question is, uh, Evan, what's your pet peeve in crypto? 

Evan Cheng:

I think people are looking backwards very much in crypto and people equating crypto with Web three. Uh, people mostly don't understand what, you know, decentralization is solving from, uh, sort of consumer behavior or how pro you know, how products are getting built and, and what is the.

What's the problem in the world, in the internet today? Right? And if you ask around, most people, even in this space, probably won't give you a good answer. Like, what is wrong with the internet today? Why do we even care about decentralization for consumers? That will be my biggest pep peeps. 

Mehdi Farooq: Sam, perhaps you go next.

Sam Blackshear:

Too hard to define metrics for product market fit and the speculative nature of crypto distorts, uh, the ways we would find that in other industries. What about sini?

Adeniyi Abiodun: 

Yeah, Overin indexing on short term, um, gains or short term, um, value capture and [00:39:00] not thinking long term. I, that's, that's been my, my biggest fa especially as a product person, right?

Like, you know, the short term thinking mindset and at least the, um, I always say subsidy driven nature of like the economic models that we see is just not sustainable. I'm surprised it's still here. 

Mehdi Farooq:

So, so when you say subsidy, um, are we, are we talking about liquidity provisioning or are we talking about grants 

Adeniyi Abiodun:

I think, I think that, for one, I can argue the grant system is just not worth, they're not many killer apps have actually come out from grant programs.

Um, separately, the idea that you can run our data, Indefinitely and keep losing money and sustain it forever. It's just not something that you'd see in other businesses. I, I do think over time, you know, when you can actually have apps that matter that people use, validators can be, um, successful and can be profitable.

But today those apps are very limited and only catered to very small, um, subset of the, of the population, which we want to change. 

Evan Cheng:
This is why several of the blockchains are inflationary, right? They're printing more tokens to pay for validator. Basically. They subsidize them forever and ever, right?

I mean, coming back to the early answers, right? They're, they have no incentive to prove upon their service in a lot of cases. 

Mehdi Farooq:

Um, so, so the second question is, this might be a bit of a tricky one. Better tech or better network effects. 

Adeniyi Abiodun: You need both. 

Evan Cheng: Yeah. You absolutely need to have, you need both. Both. I mean, I'll say you need both and neither is enough.

Right. You have to understand why they're important. Technology enable products being built rather than selling complexity in technology as a product themself, which we're seeing left and right. Right. 500 different row ups. Different kinds of row ups, right? That's complexity as a product. So pro uh, technology, service products, uh, network effects solve the CoStar problem for product builders.

But even those are insufficient, right? You actually have to sort of change consumer behavior, uh, which means consumers, you have to understand coming back, what is the whole point of decentralization? Why is it important for they have agency over the assets or own? Why does it improve upon their life? Then you have the whole thing actually going off. 

Sam Blackshear:

I do think it's a good thing about this space that folks are very tech focused and they're very on top of what's what's happening, and they get excited about new things. So it's actually possible to build network effects, at least from the best builders, by having really great techer, by doing something new. Folks are interested and they'll try it out. 


Mehdi Farooq:

Optimizing for scalability or composability. 


Evan Cheng:

There's no this, these are not the trade-offs, right? We have shown, actually, you improve upon composability because you're thinking about a different data model that allow you to capture the dependency, you know, allow you to know whether there's conflicts between transactions.

You can actually improve upon scalability and allow us to have object. Level compostability, which cannot be done with anything else. Uh, so it's both, it's not one or the other Favorite thing about Web3 very fast iteration, right?

Evan Cheng:

People are constantly trying new ideas. Uh, and this is the way product should be built is try new idea doesn't work or, you know, or, or works to a certain extent, but fail to, you know, Kind of reach, escape velocity.

You try a different model, right? So, so I think Webstream enabled this blockchain, enabled 


Sam Blackshear:

I like that folks don't take themselves too seriously. And although like they're serious responsibilities in building these systems and building these products, like there's always a na, there's always a nature of like poking fun or just like cultural thing that I think is, uh, is uh, pretty enjoyable and unique.

Adeniyi Abiodun:

They have the good answers. Honestly, I don't have much add on that 

Mehdi Farooq: Last question before I, um, conclude the podcast question I should have asked you guys, but didn't.

Adeniyi Abiodun:

Why are we so excited about sw? 

Sam Blackshear:

This is very technical, but I would've asked about programmable transaction blocks. Uh, we talked a lot about the sort of, uh, tech stuff we've been talking about for a while, but this is a very, uh, new and exciting feature that I think, uh, builders are really starting to figure out how to leverage.

And you're gonna be here a lot more about in the future.  


Evan Cheng:

I think, I think generally anything wrong, developer productivity, right. While we're taking the long road to. Like really changed the game, right? Everything from the programming language, which you know, others are using in terms of move, but even beyond move, we changed the programming model.

And why is that? Right? So a again, this, this has to do with, you know, kind of capture dependency information and utilizing that. In ways to process, uh, uh, kind of transaction more efficiently and have a better data model. Everything works together, right? This is why I don't believe in this concept, you know, like, you know, a lot of things that's been bending about, like this is the first industry in the world where people are sort of, a lot of the existing programming models sort of saw away information that can be used to improve upon your system, right?

Nobody think about critical information like the dependency. 


Mehdi Farooq:

Thank you guys for, for joining us today. Um, it, it was, I, I learned a lot about Sui and I also learned a lot about you guys. So again, thank you very much for coming and I think we are on on  time as well. 

Adeniyi Abiodun: Thanks, Mehdi. It was our pleasure. Thank you for your time.

Mehdi Farooq: Wow, what an interview. Personally, I think Evan Samini are giga brains. If you agree with me or if you disagree with me with regards to the fact that they are giga brains, please comment below. Give me your feedback and whilst you add it, also hit that like button. Uh, so in this last segment of the podcast, I, I actually go about summarizing some of the points discussed, uh, decipher and make some of the content easy to digest.

So I'll share some of my summary notes with you guys. And I also leveraged Maari Twitter thread that, um, kind of summarizes all the points discussed in a, in a very visual way. So in terms of the, in, in, in terms of various topic discussed, uh, we started off the podcast, uh, with swe objective centric data model.

Now, this is very important and it's a zero to one kind of innovation. Uh, the reason why, uh, Sui is not using the original programming language move, which was created in Facebook and is also kind of leveraged bys. They have, they, they have done this innovation to do few things. So the first thing that, uh, Evan highlights WA was the fact that because of this, Project centric data model, uh, you get to get that expressivity that allows you to create assets which are more complex.

So just to give you an example, you can create a object, uh, as, as NFT and, and that NFT could have a. Can own other NFTs, could have a child parent relationship, could basically do interesting things with regards to what's happening in the real world. The met its metadata might change and you don't have that currently with, with E V M.

So that's number one reason why object centric data model helps. The other part. The more, the more important part is that, um, in, in, in Sue's world, transactions can be grouped by object. And then can be processed in, in peril. So this, this, this diagram, um, which, which Maari made, kind of summarizes this very eloquently.

So imagine you are minting nft. Um, let's say there are two folks, me and you. We have minting Nft here and the folks who are doing liquidity mining on, on a, on a deck. Now these two transaction might be independent of each other and they might not interact simultaneously with each other. Because of this, I'm minting, N F T, and somebody else is doing liquidity mining.

These transactions can then be processed independently by the computing resource. Once that's done, these validators can, can process this, um, uh, transaction independently, but can also scale the transaction horizontally when, let's say, when they have more compute. Uh, so this is one of the innovation that is being brought by Swei while they're object centric data model, which helps in, in.

Paralyzing objects. No. Another thing that's very unique about Swei, again, I've touched upon this earlier, is that simple transaction, let's say peer-to-peer transfer or nft. Min can, can be done without consensus and uh, without ordering of transactions. And that also allows transactions to be done quickly.

However, when it comes to shared or complex transactions, so for example, me minting, N f t, then doing lending and borrowing, and then going to a aex, all of these in, in, in, in one go. For that purposes, um, they, it has to go through ordering in consensus. And, and for that, um, they, they use Novel and Bullock, which allows them to do this.

Another interesting use case, uh, of Sweet Token and also something novel about this project is the token omics, which from intellectual standpoint also made me very curious. So one thing they're, they're innovating on is that they, they have an on chain storage, which a lot of, um, el ones do not have, or even if they do have, it's, it's very expensive.

So when you are using gas or when you're using, uh, sweet Token as a commodity, you are, you're not only paying for computation, but you're also paying for on chain storage. Now, this is very important because let's say if your, if your on engine activity leads to. Of future validator set, there is opportunity, cost and bad actors.

If, if, if given, there is no storage cost. Bad actors can just bam the blockchain to avoid this bad network externality. They have a unique token utility where you also have to pay for compute, which also creates another sync for the token. It creates additional utility and I think it's, it also kind of solves that time travel issue where validators in the future, uh, will be storing way more than current validator sets.

So I think that is also very noble, which I don't think, apart from near any other blockchain is kind of thinking about or doing. One thing I missed actually on the podcast was programmable transaction blocks, which is a, again, another, um, dev tool Sue is working on. So, programmable transaction blocks actually allows, um, users to create composable sequence of many transaction, let's say a thousand transaction that can all be executed at, at, at one go.

So, for example, think of it as like packaging. You can package multiple operations in one go. So since you're packaging multiple transaction in one go, uh, the chain again achieves throughput and, and it also lowers, uh, cost per per transaction. So let me give you some example. Mass minting of thousand NFTs.

All of this can be done in one go and, and sequence of thousand transaction can be, uh, used as one sending payments to multiple parties or doing complex arbitrage or triangular arbitrage or, or defi derivative strategy, which has multiple sequences. All of that can be done in one goal with, with lower cost, and that is something that they, they've also introduced, which from a developer's standpoint is amazing.

They have other, other innovations as well, such as subsidizing gas fees on the backend, which I think is also interesting. Evan is also a, a visionary, like you can sense that he hates Geomorphic products, uh, even like in, in, in web three. And that was evident the, the way he started the interview and also when I asked him about his pet pee.

Uh, so the reason he created this expressive, um, uh, Expressivity with the object centric data model was to avoid that and, and, and create these unique use cases that Web three should be, uh, useful. So I thought that was interesting. Uh, also there was a lot of alpha, uh, kind of leak, but also discussed, which also different projects being built, and there were a lot of names that were dropped.

So do check out. So if, if you're just looking at the synopsis or, or the summary of the podcast, I. Urge you to go back and listen to the whole podcast, to the section where I gives you, gives you the alpha. Again, thank you so much guys, and I do appreciate you listening to the whole podcast. If you have, again, please hit hit the like button, subscribe and share your love on on.

This podcast is for information purposes only and should not be considered as financial advice. Any opinions provided in this podcast reflect the views of the speakers only.

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