GRTiQ Podcast: 120 Mihai Grigore

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Mihai Grigore (00:18):

So by far, The Graph is one of the most important innovations out there in the space and is a very, very critical piece of infrastructure.

Nick (00:58):

Welcome To the GRTiQ podcast. Today I’m speaking with Mihai Grigore, head of Web3 Protocol Research at Messari. Mihai leads Messari’s Web3 protocol research team covering infrastructure, base layers, and consumer apps. If you’re a member of The Graph ecosystem, then you already know Mihai and his team’s work. They publish a well-known research report on The Graph every quarter entitled The State of The Graph. During this interview, Mihai talks about his professional background working in the banking and finance industries, his education in computer science and math, his move to Messari, including a fun explanation of where Messari got its name, and his incredible perspective of the entire web3 landscape. We then talk about The Graph and all the observations he’s made by virtue of his research into the protocol.

(01:51):

As always, we start the discussion talking about Mihai’s educational background.

Mihai Grigore (01:57):

My background is in mathematics and computer science. When I was a child, I was attracted by numbers and how different things relate to each other. So this got me into math in the first place. And then I was quite fortunate to have both my parents work in IT. And they were smart to see the need of having a computer at home already in the nineties. And this gave me the chance to experiment very early on with writing code in Pascal and C. And that’s what drove me towards studying math and computer science and then eventually do a PhD at the IT Zurich.

Nick (02:39):

Have you ever thought about what it is about math that drew your interests, why that was something you were attracted to? When it seems sometimes people aren’t attracted to math, right? It’s a little intimidating or overwhelming.

Mihai Grigore (02:51):

Yeah, it is how numbers relate to each other and putting everything into an equation.

Nick (02:57):

So as you mentioned there, you studied mathematics and computer science. At first glance, and this has come up a lot recently on the podcast, in fact, I’ve had a lot of people that have studied computer science and math. But I like to ask this question about how those two fields relate. Because you can argue those don’t really relate to one another, but how would you explain that relationship?

Mihai Grigore (03:16):

Computer science is mathematics in practice. And what I mean by that is that it can decompose pretty much any component of a computer and any line of code down to mathematical operation, which is fascinating to me. But nobody does that nowadays. And there’s less and less awareness about how this relationship between math and computer science works. And that’s for a good reason. It’s similar to driving a car. If you drive a car, you essentially don’t need to know what each component of a car actually does in order to drive the car.

Nick (03:56):

Mihai, it’s happened on the podcast before where a guest has said, “My parents brought home a computer. I started playing on this thing and I really fell in love with technology and it set me in a course on my own life of what I was curious about.” But then there’s this other component where some guests talk about taking the computer apart, putting it back together. And I’m just curious, you’ve got the parent component. They brought home, the computer sparked your interest. Were you also one of these people that took the computer apart and reassembled it?

Mihai Grigore (04:26):

Oh yeah. Putting the pieces apart was something very fun to do. And it was very stimulating for me to realize how things come together. And dissembling the computer itself was a way to train myself how to decompose more complex problems into smaller pieces that I can handle or that at least I can see what what’s inside there.

Nick (04:51):

I also like to ask this question about computer science when I interview somebody that studied it. And longtime listeners of the podcast know I’ve had a lot of guests that have studied computer science. And what’s interesting to me is the timeline at which they’ve studied it. So some guests studied computer science maybe in the nineties, and then some of the younger guests have done it quite recently. But you mentioned there, you studied it in university. And my question typically is: during your course of study, did you ever hear about blockchain or distributed systems or cryptography?

Mihai Grigore (05:26):

That’s a great question. I started my studies in computer science in 2005. So somehow in between the two types of guests that you had previously with the podcast. And I remember learning about the RSA cryptography algorithm as part of the information security course. I also remember having learned computational logics, which is the fundamentals of today’s zero knowledge proofs, and also about computer networks and distributed systems. So these are all fundamental pieces of what we collectively call today blockchain as a standalone subject of study. But I haven’t studied blockchain per se in my bachelor or master studies.

(06:12):

Other things that I covered during my studies were object-oriented programming, algorithms, databases, computer graphics, and statistics and machine learning.

Nick (06:24):

Well, Mihai, as we’re about to discuss, a lot of this education took you into the route of data analytics and data science. And so before I ask some of those types of questions, I want to ask you about where you’re joining me from. So you’re joining me from Zurich, Switzerland. I think you’re the second guest that I’ve had on the podcast from Switzerland. I always like to ask this question about the local interest level or atmosphere as it relates to crypto and web3. What can you share with us about what’s going on where you live in Zurich?

Mihai Grigore (06:57):

Yeah, I think the atmosphere is very active, especially during the past two years. I was able to see quite a lot of startups, smart people willing to build and having the energy to build. Then there’s also financial institutions that are definitely looking for onboarding more clients and experimenting with the infrastructure reels. And then there’s also a high level of interest among both institutional and retail investors, I would say. And there’s larger events now than four or five years ago, irrespective of the market conditions. And I see this as a very encouraging sign.

(07:45):

And one more aspect not to forget, is that the government institutions in Switzerland are quite supportive of crypto and of innovation in general, which is definitely an advantage versus other geographies.

Nick (08:00):

So if any of our listeners ever find themselves in Switzerland or Zurich, surely there’s something they need to go see or some food they need to eat there. Do you have any advice for listeners, whoever find themselves there, of things they should do while in Switzerland?

Mihai Grigore (08:15):

Well, there is a lot of crypto events of very high quality happening these days in Zurich and in the greater Zurich area. But what I would say, especially given that there is a lot of travel in the markets and a lot of events happening nowadays, I’d recommend pretty much anyone to take a day off and go to the Swiss Alps. You won’t regret it.

Nick (08:41):

Mihai, you studied mathematics, computer science, and eventually you graduate from college and enter the workforce. What can you tell us about your professional background and what you did after college?

Mihai Grigore (08:51):

So after college I did a PhD. And afterwards I wanted to go ahead and apply both my technical and research skills to the industry. So I went to work as a data scientist in the financial industry. And through work colleagues I started to get educated on blockchain technologies and eventually ended up joining Messari.

Speaker 1 (09:16):

The GRTiQ podcast is made possible by a generous grant from The Graph Foundation. The Graph Grants program provide support for protocol infrastructure, tooling, gaps, subgraph, and community building efforts. Learn more at thegraph.foundation. That’s thegraph.foundation.

Nick (09:48):

Hi, this is GRTiQ, and thank you for listening. Listeners who enjoy this content can help support the GRTiQ podcast by leaving a review or a five-star rating wherever they download podcasts, by sharing episodes on social media, or by simply telling a friend or colleague about something they heard or learned from one of our guests. It’s support from listeners like you that make it possible for us to keep shining a light on the people and stories behind web3 and The Graph.

(10:23):

Well, part of the reason we’re speaking today is because as a member of the Messari team, you have been helping publish and do the analytics for these quarterly reports that everybody in The Graph ecosystem and community are excited to read and review. And we’re going to talk a lot about that work. But before we do, I want to ask you some questions about your professional background. And I want to ask this question about data science. How do data scientists create value for companies in something like the financial industry? What were you doing?

Mihai Grigore (10:56):

Yeah, I would say in simple terms, a data scientist can create value by helping to grow revenue or to decrease costs of companies in the financial industry.

(11:09):

So in terms of growing revenue, it’s about informing product decisions. So think of better pricing. A data scientist in a financial industry works on producing statistical models to quantify risk and come up with a better way to price that risk. Or we could also think about improving sales and distribution. So thinking of selling more. A data scientist can develop a recommender system on which clients to target for the next campaign, for what product, for which channel, and so on.

(11:46):

And on the other side, if we think in terms of decreasing operational costs, one could do that by automating complex processes. And here think for instance of extracting relevant information buried in long PDF documents.

Nick (12:04):

Is it strange that somebody who studied mathematics, had an interest and studied computer science, ends up in data science? I mean, would you explain how that came about?

Mihai Grigore (12:15):

Oh, data science is a combination of computer science and mathematics. It’s a nice rebrand of the term “statistician” or “applied statistician” that works very extensively with a computer. And this happened the same in the field of statistics, machine learning, and now artificial intelligence. They’re essentially a very, very close to each other. And one shouldn’t distinguish them too much from each other, because at the end of the day, they use the same methods at the back.

Nick (12:51):

Well, that makes a lot of sense. And so you decide to go to work professionally in data science, you’re working in the financial industry. Eventually you become aware of crypto. When was that? And what can you tell us about your first impressions?

Mihai Grigore (13:06):

Yeah, I first became aware of crypto during my research time at ET Zurich. And I remember my office mate in 2014 speaking about Bitcoin and also about Kraken at that time. I only started to pay more attention and comprehend it only after Ethereum came to life.

Nick (13:27):

Do you remember what drew your interest in crypto and why you thought these things were something to pay attention to?

Mihai Grigore (13:34):

The interest started with Bitcoin. And from a macro perspective, I’ve been working in the financial sector. And I was often thinking of quantitative easing and what are some of the unintended consequences of doing quantitative easing at-scale in US and in Europe, also in China, Japan. And this made me get more into Bitcoin and what it means from a macro standpoint.

(14:04):

But then Ethereum came as well, and this was interesting from a tech perspective. And what fascinates me is that Ethereum is a computer that enables decentralized infrastructure for stuff like decentralized storage, decentralized data indexing, decentralized compute. So yeah, it all came together beautifully and just motivated me being a student of blockchain technologies.

Nick (14:33):

At this time in your life, you’re working in financial services, you’re in data science. Are you having realizations that blockchain, things like Ethereum, are disruptive? That they might change or innovate legacy systems and things you’re working on?

Mihai Grigore (14:51):

Well, what actually first comes to mind here is when we’re analyzing data is you can reach one conclusion by analyzing, let’s say, the entire dataset. But you can draw a fairly different conclusion by employing the same method or the same model, but choosing to analyze only a subset of that dataset.

(15:15):

So with blockchain, the entire dataset is available, which actually means that post transactions cannot be skipped over or altered. So blockchain can help alleviate some of these integrity shortcomings when analyzing the data. And I think this applies to any industry where we’re currently maybe seeing accounting gymnastics being done at scale. So essentially having data on the blockchain would alleviate some of these gymnastics.

Nick (15:50):

When you think about everything that’s happening in web3, crypto, blockchain, this revolution, if you will, how do you see it? I mean, do you see it as a movement about data and data integrity? Do you see it as economic or financial? Or about equality? I mean, there’s so many different ways to interpret this movement. How do you see it?

Mihai Grigore (16:15):

I think all these aspects can be an anchor for the current movement. But as a matter of fact, I do not really see it as a revolution, but rather as a continuation of a longer-term process of countries and societies getting mature. And as a matter of fact, there is a book by Neil Howe on generations where he explains that things happen in cycles of 20 to 25 years. And that we’re currently in such a cycle where organizations and societies are being rethought. And people are currently trying to take more initiative on their own and to get self-organized.

(17:07):

So perhaps this entire movement is driven by that cycle we’re currently in. And it’s being expressed with the help of the blockchain technology

Nick (17:19):

That idea’s come up on the podcast before. And in fact, I think it’s a brilliant understanding of what we’re experiencing. But in essence, are you arguing or taking the position at least that web3 is just the natural next evolution that mankind is going to explore and adopt as part of these cycles? And if that’s the case, I presume you feel like Web2 is an inevitability? I mean, this is just a natural step along the path.

Mihai Grigore (17:47):

I indeed see web3 as a natural next step. But then at the same time, I do believe that web3 will coexist with Web2. There are certain cases where web two is probably better suited for any kind of technical implementation, and maybe it’s also cheaper than building in web3. So it’s definitely dependent on the case-by-case basis. But I do see web three happening as a natural, normal consequence of where we are at the moment.

Nick (18:24):

What was then the path you took as somebody working in data science in the financial services industry and eventually working full-time in web3?

Mihai Grigore (18:35):

Yeah, so it all started with chatting with my colleagues at work, reading a lot of research, going to local meetups, and watching many hours of videos explaining core concepts of distributed ledger technologies. And one day Messari opened its research cup for research contributions on various crypto topics. So I started doing that. And several months later, I got an offer to join the Messari research team. And here I am after almost two years.

Nick (19:14):

Mihai, as you probably know, I’ve had the opportunity to interview other members of the Messari team, very fortunate to have Vincent Wen and Ryan Selkis on the podcast about a year ago or so when The Graph announced this incredible new subgraph core developer partnership with the team at Messari. But for listeners of the podcast who aren’t familiar with Messari and what it does, can you provide just a brief introduction?

Mihai Grigore (19:41):

Yes. In a nutshell, Messari is a provider of data and research services. And if you’re wondering what Messari means, it’s the name “Messari” that comes from the Renaissance monks that propagated the practice of double-entry bookkeeping. And they basically tried to determine merchants to use sound accounting and avoid any accounting gymnastics. And that’s essentially what we do at Messari as well. We bring transparency to the entire space.

Nick (20:18):

Well, Mihai, I didn’t know the origins of the name Messari or what it exactly meant. But now that you explain it makes a lot of sense to me. Because of course, double-entry accounting was an important standard that really shaped the way accounting was done throughout the world. And now we have this company Messari working in web3. And I think it often gets overlooked. I think people see Messari as a research analytics firm, but in addition to all of that great content and all the great work, they’re also about this business of setting standards kind of hearkening back to the origins of their name.

(20:52):

And I first became aware of this because of that Core Subgraph Developer relationship with The Graph. The team led by Vincent Wen is trying to build some incredible standards around subgraphs at The Graph, and I see it in other places as well. And so I do want to ask this question. I mean, is it part of the mission of the team at Messari to start setting and shaping standards in this emerging industry?

Mihai Grigore (21:18):

You are absolutely right that standardization is at the core of what we do at Messari. Through standardizing key performance indicators of protocols, we are trying to introduce an industry-wide standard for research.

Nick (21:37):

Well, it’s an incredible goal and ambition. And I really have a lot of respect for the team at Messari, and I’m very happy that you are all leading this charge. I’d like to ask you what you do at Messari. So once you took that position, what are the types of things you’ve been working on and what is your role with the team?

Mihai Grigore (21:55):

At Messari, I lead a team that produces data-driven research on base layers. So this includes both layer 1s and layer 2s. Mid-layer infrastructure, this includes data storage, distributed access, data indexing, and also consumer applications. So think here of web3 social.

Nick (22:53):

Well, Mihai, as I mentioned earlier, one of the reasons we’re talking today is because you and the team at Messari create these incredible quarterly reports called The State of The Graph. Although there’s a ton of interest in The Graph community and ecosystem when these reports are published, it’s worth noting that the team at Messari publishes these reports on all the protocols and different projects working in web3. Can you take us back in time? When did you first become aware of The Graph and what did you think about the nature of the problem the protocol wanted to solve?

Mihai Grigore (23:23):

I became aware of The Graph for the first time when I was trying to get on-chain data. I think that was back in 2021. And the problem that I had back then was that I was relying too much on third-party data providers that often had incomplete data. And it was hard for me to understand how some of the metrics were computed and displayed. So what I did is I started Googling about how to query on-chain data, and that’s how I got into GraphQL and eventually into The Graph.

Nick (24:10):

Oh, wow, Mihai, that’s interesting to me. So what you’re saying is not only are you creating these research reports, in this case, The State of The Graph, something that everyone’s looking forward to on a quarterly basis, but you’re also leveraging The Graph to get access to blockchain data to do some of these other quarterly reports or analytics?

Mihai Grigore (24:31):

Absolutely. We at Messari are core consumers of data from The Graph. And we use it in order to gather core metrics and insights from a wide variety of networks that we cover in our research. And what we’ve learned from using The Graph is that these networks aren’t created equally. In fact, they are quite different from each other in terms of for instance, how they accrue value. And to give an example here, it is not trivial for us in research to come up with a unified methodology that actually quantifies revenue accrued by each participant of the network. And this is why we put together research where we properly specify and apply this methodology across multiple networks. And in this process, we leverage The Graph very intensively.

Nick (25:36):

Miha. I think listeners would be interested to get your perspective on any observations or things you’ve learned by virtue of the research you’re producing and the analytics that you and the team perform. So what are you seeing in terms of data or trends or anything that’s piqued your interest as you’ve done research about The Graph?

Mihai Grigore (25:56):

Something that I’ve learned, and that’s specific to The Graph, is incentivizing the key ecosystem players to interact with each other. So we do have indexers, we do have curators and delegators who have very, very specific roles in the ecosystem. And what we’re observing through the past year is that the community and the whole ecosystem are growing at a significant pace. So we definitely see positive trends in the number of indexers on The Graph, and this is a sign of a healthy ecosystem.

Nick (26:39):

Well, bolting onto that, since you have this really incredible perspective of the industry as a whole, as we’ve said, you and the team are producing a lot of these research reports. We’re obviously talking just about one, but there’s I think probably over 30 of these research reports. What can you share about how The Graph’s performance, either in terms of adoption or growth, compares to what you’re seeing with other protocols in the industry?

Mihai Grigore (27:07):

Oh, yes. We’re analyzing The Graph in the context of other web3 infrastructure projects like data Indexers, Oracles, data storage, and decentralized compute protocols. And yeah, compared to a year ago, we definitely see growth in the usage and adoption of these infrastructure projects. And a likely explanation for this is that infrastructure fuels the building of applications even in the current bear market. And this is a very encouraging sign for the entire space. Because these applications that are currently built are expected to drive further demand.

Nick (27:53):

What if we zoom out a little bit then and we talk less about The Graph and more about the industry as a whole? From this perspective of growth and the research that you’re doing, what types of things are you observing at the industry level?

Mihai Grigore (28:07):

That’s a great question. I think web3 infrastructure has managed to grow better or at a more accelerated pace than other verticals take here. Some of the layer ones, some of the DeFi protocols, or some consumer applications. So whereas we see in the overall market that there is a slowdown or some decelerated growth, we also are able to observe that web3 infrastructure has managed to gain further usage and further adoption throughout the past year.

Nick (28:43):

Mihai, in a lot of ways, your story is not dissimilar to what I suspect a lot of listeners have experienced. That is they become aware of Bitcoin and Ethereum, they get a little bit of interest, and then they look for ways to go full-time in web3. You’ve successfully done it. You’re at Messari, a powerhouse and a very well-recognized name throughout the industry. But it’s also given you a unique perspective, I got to imagine, on what the future of the industry looks like. You’re seeing growth, you’re doing research, and you’ve got all these great analytical tools and savvy. How has this perspective shaped how you think about the industry and its future?

Mihai Grigore (29:22):

Indeed, my thinking about the industry has shifted in the sense of working a hundred percent, dedicating my full-time to crypto made me also observe that the pace of innovation in the whole space is accelerating. And it’s hard for me personally to keep up with everything, even when working full-time in the industry. So this gives me more confidence in the space and in its future given that I see a lot of talent currently putting a lot of energy into developing new applications.

Nick (30:04):

There’s so much speculation, there’s so much hype about this industry. And Mihai, in my mind, in just about any other situation when there’s a lot of hype and a lot of noise, what you need to do is just go to the data and get super objective. And so you’re one of the few guests that I’ve had the opportunity to ask a question like this because of the nature of your work and where you work at Messari. But when you get super objective and you just look at the data and you get away from the noise, you get away from the hype. Are you optimistic about the future of crypto and its adoption throughout the world?

Mihai Grigore (30:44):

Indeed. I am rationally optimistic when I look at the data and when I see that there’s an increasing number of developers building new applications. And my hypothesis is that these applications will fuel the next wave of adoption and usage of crypto protocols

Nick (31:08):

Specific to The Graph, then, I want to ask this question about data points that you’re watching as signals? Or important signals for growth or greater adoption of the protocol?

Mihai Grigore (31:20):

Yes. For The Graph specifically, I am looking at the demon side of the network. And the metrics that I follow are query fees from applications that leverage The Graph. Also, the number of subgraphs has been a good precursor for future usage.

Nick (31:42):

When you think about how The Graph fits into the industry, then, you have this great perspective of different protocols and projects within the space. How do you explain the importance of a solution like The Graph and how it fits in?

Mihai Grigore (31:56):

I see The Graph as a critical piece of infrastructure for data consumers. Think for instance here of app developers trying to get on-chain data to power their apps. So instead of building that infrastructure on their own, they can rely on The Graph to query on-chain data and being able to use it for their apps. So by far, The Graph is one of the most important innovations out there in the space and is a very, very critical piece of infrastructure that most of developers should use.

Nick (32:39):

Mihai, I’d love to get your opinion on the future of L1 and L2s. And this was a topic that I really had to educate myself about. And it becomes confusing sometimes when people think about the future. Is it multichain? How do L2s interplay with all of that? Based on what you’ve studied and your own thinking on the subject, what’s your opinion on the future of L1s and L2s and that relationship?

Mihai Grigore (33:04):

Yeah, my sense is that blockspace will become a commodity and will consolidate around several major L1s at some point. And my thinking here is informed by a pattern that we tend to see in most mature markets. So these markets tend to consolidate around two to three major players that are capturing maybe two-thirds of the market. And then they’re followed by a longer tail of mid and small players. I think something like this may happen in the case of L1s.

(33:48):

When I contrast these [L1s] with L2s, my sense is that there will exist many service providers that will specialize on niche use cases, and that these use cases are going to be demanded by applications. So the L2 space will become more fragmented than the L1 space. And there’s not going to be such a big consolidation as I assert that might happen in the L1 space.

Nick (34:21):

Well, Mihai, I only have one final question for you before I ask you the GRTiQ 10, and it’s about going back in time to early on in your career when you were doing research as a data scientist in the financial services industry. When you think about the nature of your work or the nature of those industries, and you apply the knowledge you have now about web3, crypto, and blockchain, do you see that the work you were doing or those industries are ripe for disruption due to the things we’re working on in this industry?

Mihai Grigore (34:53):

Yes. I do believe that financial services are ripe for disruption, and that the nature of the work of a data scientist in a financial services institution will be quite different. I foresee that many financial and physical assets will be stored on the blockchain, and this will make it much easier for everyone working with risk to distinguish who owns what and where. And what this essentially will do, this will unlock more transparency with respect to what the risks are, and hence the work of data scientists will be transformed. So essentially everyone will have more transparent data at hand, and these insights will be accessible by anyone.

(35:53):

And when it comes to research, I do believe that the decentralized science space is very fascinating. We already see initial signs of being able to publish research and experiments that are replicable. And this will mean a big step forward for the whole research industry. So essentially this will enable everyone to redo or to recreate the results that previous scientists have been working on and have been publishing. So again, it’s about improving transparency also in the research field.

Nick (36:37):

Well, now I’m going to ask you the GRTiQ 10. These are 10 questions I ask each guest of the podcast every week. And Mihai, I ask them because I think it’s fun for listeners to learn something new, try something different, or achieve more in their own lives. And so these questions are one way to kind of help listeners explore those things. And so are you ready for the GRTiQ 10?

Mihai Grigore (36:57):

I’m ready.

Nick (37:09):

What book or article had the most impact on your life?

Mihai Grigore (37:13):

It’s “Algorithms to Live By”, it’s written by Brian Christian, and it’s a set of practical ways to apply statistics in your favor in life and make better decisions. And if I’m allowed to choose a second book that’s “Factfulness” by Hans Rosling. This is a rational reminder of where we are as a human species, and that we’re objectively doing much better today than 30, 50, or a hundred years ago. And this is an important driver for action instead of staying anchored in today’s problems.

Nick (37:57):

Is there a movie or a TV show that you think everyone should watch?

Mihai Grigore (38:01):

Yes. The TV series is called “Financial History of the World”. It’s by Nile Ferguson. It’s a must-watch in my opinion, because financial education in school nowadays is quite sparse. And this TV series gives the right level of detail for someone who wants to get started in financial education.

Nick (38:27):

If you could only listen to one music album for the rest of your life, which one would you choose?

Mihai Grigore (38:31):

Oh, that’s Trilogy by ATB. It’s a perfect combo of piano and modern tunes. And it’s very relaxing and gives good energy at the same time.

Nick (38:47):

Mihai, what’s the best advice someone’s ever given to you?

Mihai Grigore (38:50):

I think the best piece of advice is to actually ask for advice and to do reality checks as often as I can.

Nick (39:01):

What’s one thing you’ve learned in your life that you don’t think other people have learned or know quite yet?

Mihai Grigore (39:06):

Well, that’s an interesting one. Because I think we live in a day and age where we are all very well-informed. We are just bombarded by so much information. And at least in theory, we should know it all. But I think what’s less known or what people are less aware of is actually how to transform all that information into action. I think this is currently lacking, and I think most people don’t know how to make that information actionable.

Nick (39:42):

What’s the best life hack you’ve discovered for yourself?

Mihai Grigore (39:45):

I think the best life hack for me is to stay curious. And this opens many doors. And if I could pick a second one, that would be going out for a walk with a friend or a partner. This gives a great view of the day.

Nick (40:05):

Based on your own life experiences and observations, what do you think is the one characteristic or habit that best explains how people find success in life?

Mihai Grigore (40:15):

It’s getting things started and not overthinking.

Nick (40:20):

And then the final three questions are “complete the sentence” type questions. So the first one is, Mihai, complete the sentence: the thing that most excites me about Web three is…

Mihai Grigore (40:29):

It’s a collaboration that happens, open source, and permissionless.

Nick (40:34):

And how about this one? If you’re on Twitter, then you should be following…

Mihai Grigore (40:38):

@MessariCrypto for the high quality of research and for the depths of our data.

Nick (40:44):

And finally, I’m happiest when…

Mihai Grigore (40:47):

When I create something new.

Nick (40:58):

Mihai Grigore, thank you so much for taking the time to speak with me today. And I really appreciate that you shared not only your personal story, but all the great work that you and the team at Messari are contributing. And for any listeners that haven’t seen one of these quarterly reports, The State of The Graph, you got to go out and check this out. Super informative and always at the forefront of what’s happening within The Graph ecosystem.

(41:21):

If listeners want to stay in touch with you Mihai, and follow the things you’re working on, what’s the best way for them to stay in touch?

Mihai Grigore (41:28):

Go to messari.io/research. Or follow me on Twitter @tech_metrics. That’s tech_metrics.