In this theCUBE + NYSE Wired: Mixture of Experts segment, theCUBE’s Dave Vellante sits down with Jim McNiel, Chief Growth Officer at TAE Technologies, to demystify fusion vs. fission and explore how proton–boron fusion could reshape energy economics for enterprise and Wall Street alike. McNiel explains why TAE targets abundant, low-cost boron fuel and how its approach avoids long-lived radioactive waste, requires only light shielding and eliminates meltdown risk. He breaks down siting and regulation – fusion treated more like medical isotopes than fission – and outlines first-gen levelized energy costs in the 7–9¢ range with a path to sub-5¢ as the technology matures. The conversation ties these fundamentals to market dynamics: dispatchable, carbon-free baseload power for data centers, safer urban siting and a financing narrative that aligns with investor expectations and hyperscaler demand.
Listeners also get a clear milestone roadmap: Copernicus (commissioned to operate in 2028) targeting net energy out; Da Vinci as a 50-MW commercial prototype; and TAE Fusion 1 designed for 350 MW—scalable units that could colocate with gigawatt-scale AI facilities. McNiel details how AI already governs plasma stability via TAE’s “Optometrist Algorithm” developed with Google and notes strategic investors (e.g., Chevron, Sumitomo) plus near-term revenue from TAE Power Solutions and TAE Life Sciences. The discussion frames emerging trends in enterprise strategy – from energy as a core input to AI-driven productivity gains – and why the go-to-market has shifted from utility-first to hyperscaler-led demand for dispatchable, clean power.
Forgot Password
Almost there!
We just sent you a verification email. Please verify your account to gain access to
theCUBE + NYSE Wired: Mixture of Experts Series. If you don’t think you received an email check your
spam folder.
Sign in to theCUBE + NYSE Wired: Mixture of Experts Series.
In order to sign in, enter the email address you used to registered for the event. Once completed, you will receive an email with a verification link. Open this link to automatically sign into the site.
Register For theCUBE + NYSE Wired: Mixture of Experts Series
Please fill out the information below. You will recieve an email with a verification link confirming your registration. Click the link to automatically sign into the site.
You’re almost there!
We just sent you a verification email. Please click the verification button in the email. Once your email address is verified, you will have full access to all event content for theCUBE + NYSE Wired: Mixture of Experts Series.
I want my badge and interests to be visible to all attendees.
Checking this box will display your presense on the attendees list, view your profile and allow other attendees to contact you via 1-1 chat. Read the Privacy Policy. At any time, you can choose to disable this preference.
Select your Interests!
add
Upload your photo
Uploading..
OR
Connect via Twitter
Connect via Linkedin
EDIT PASSWORD
Share
Forgot Password
Almost there!
We just sent you a verification email. Please verify your account to gain access to
theCUBE + NYSE Wired: Mixture of Experts Series. If you don’t think you received an email check your
spam folder.
Sign in to theCUBE + NYSE Wired: Mixture of Experts Series.
In order to sign in, enter the email address you used to registered for the event. Once completed, you will receive an email with a verification link. Open this link to automatically sign into the site.
Sign in to gain access to theCUBE + NYSE Wired: Mixture of Experts Series
Please sign in with LinkedIn to continue to theCUBE + NYSE Wired: Mixture of Experts Series. Signing in with LinkedIn ensures a professional environment.
Are you sure you want to remove access rights for this user?
Details
Manage Access
email address
Community Invitation
Alex Gallego, Redpanda
In this theCUBE + NYSE Wired: Mixture of Experts segment, theCUBE’s Dave Vellante sits down with Jim McNiel, Chief Growth Officer at TAE Technologies, to demystify fusion vs. fission and explore how proton–boron fusion could reshape energy economics for enterprise and Wall Street alike. McNiel explains why TAE targets abundant, low-cost boron fuel and how its approach avoids long-lived radioactive waste, requires only light shielding and eliminates meltdown risk. He breaks down siting and regulation – fusion treated more like medical isotopes than fission – and outlines first-gen levelized energy costs in the 7–9¢ range with a path to sub-5¢ as the technology matures. The conversation ties these fundamentals to market dynamics: dispatchable, carbon-free baseload power for data centers, safer urban siting and a financing narrative that aligns with investor expectations and hyperscaler demand.
Listeners also get a clear milestone roadmap: Copernicus (commissioned to operate in 2028) targeting net energy out; Da Vinci as a 50-MW commercial prototype; and TAE Fusion 1 designed for 350 MW—scalable units that could colocate with gigawatt-scale AI facilities. McNiel details how AI already governs plasma stability via TAE’s “Optometrist Algorithm” developed with Google and notes strategic investors (e.g., Chevron, Sumitomo) plus near-term revenue from TAE Power Solutions and TAE Life Sciences. The discussion frames emerging trends in enterprise strategy – from energy as a core input to AI-driven productivity gains – and why the go-to-market has shifted from utility-first to hyperscaler-led demand for dispatchable, clean power.
>> I'm Gemma Allen with The CUBE here at the New York Stock Exchange. This is our Redpanda series for mixture of experts. Joining me today in studio, I have CEO of Redpanda, Alex Gallego. Welcome, Alex.
Alex Gallego
>> Thanks for having me.
Gemma Allen
>> Thanks so much for being here. You were here in May, back at the NYSE. I think the data's faster, traders are louder, and things are moving faster in your world. Let's unpack that. How are you holding up?
Alex Gallego
>> It's been a phenomenal summer for us, really in terms of growth from the number of customers. I think, as we'll talk later today, we're expanding the product portfolio in a meaningful way. We've been really thinking deeply what's next for Redpanda. So, excited to be here to share with the rest of the world today.
Gemma Allen
>> Great. And when you were here in May, you spoke a little bit about how you want to see the world move from batch to batch, which is no longer relevant to real time, and event to event type of scenario. Right? Tell me what's happened since May in the space you're in. It seems as though the world of AI is moving so fast.
Alex Gallego
>> I would break up the world into three big epochs. At first there was the movement and the creation of the idea of the data warehouse. It was self-hosted data, really hard to scale, really hard to manage. You move it to the cloud, you separate compute and storage, and now you have a really cost-effective way, but most importantly, really scalable to do analytics. Part of the problem with self-hosted provision is that it's just hard to scale, hard to operate, really expensive, brittle. Really, the cloud gave people elasticity. It gave people a way to really actually get value out of the data that they were generating. That was data warehouse. And tabular data separated compute and storage. The next evolution from that was this idea of the lake house. For lack of a better word, it became a dumping ground, not just of tabular data, but on any kind of data, video data, music, images, things that didn't really have shape, PDFs that had to be extracted and meaning had to be created for, et cetera. But the idea was, look, these tools are so useful that why don't we throw all our data into this one place? And then we led the query engine deal with the complexity. I think we're in a new transition for the world right now that we're calling the agentic data plane transition. Which is, lakes are stagnant. They're vast and large, but they're stagnant. And I think agents need this bidirectional way of communicating what they're both consuming but also contributing back information to this idea. And I think the world needs a new system. It's not just that code was generated, it's that the architecture is so different from what we're building that you really need a new fresh take, if you will.
Gemma Allen
>> And what you described there, it's high impact, it's high value. We have some phenomenal guests in the mixture of expert series. And one thing we hear a lot is that a lot of enterprises feel that they're not still deriving the value that they expected from this world of AI, and even especially agentic AI. Tell me about some of the customers you work with, like you work with the Olympics, some very big names known to everybody. Share some of those use cases.
Alex Gallego
>> We grew up really powering tier zero mission-critical systems. Examples of those is we protect Whitehouse.gov. Through Akamai, we power all of the electric car companies in the US. We power probably the largest banks in the US right now, so it's likely that your paycheck is actually clear because Redpanda's up and running. Or that you are able to get to work. Because when you tap your iPhone onto the payment device, it went through eventually to a system that's powered by Redpanda. That was our bread and butter. If your business depended on this messaging infrastructure to make money to function, now those were the kind of businesses that we wanted to power, and they tended to be the G2K. Now, with agents, the next challenge from them is really two things around governance: access controls and observability. Are these agents accessing the data that they're supposed to access? That's one. And two, when something goes wrong, let's say that this model had a gender bias. Can I go back and figure out why this model denied my credit? How did this happen? And so you really need a different take on the architecture. Those are the next challenges that we're trying to help enterprises with.
Gemma Allen
>> Tell me a little bit about what's been happening from you as a company. Earlier this year there was rumors of a Snowflake acquisition. I know you've hired the CTO of Snowflake since, you were going to have him later on this segment. But tell me what's been happening from an acquisition market perspective. You guys have been busy, some big announcements.
Alex Gallego
>> Yeah. I think Redpanda has always had people that basically every big business in the world has had many offers for exit. We've remained pretty focused on helping what we call the builder makers and doers shape the future. Tyler joined me from Snowflake as my new CTO, and we're super thrilled to have him. There are a few people in the world that have his level of expertise. In particular, around processing large scale data. First, his experience at Google building some of the largest query engines in the world. And then later on he went on to build really large scale systems for the next generation of query and at Snowflake for these things called dynamic tables. Those were his core ideas that he brought to the world. For us, it's actually the opposite. And I think today we're just super excited to announce that we've made an acquisition of a distributed query engine. And Tyler is going to join us later today to give us the details as to, how does this complement the Redpanda product portfolio? Where does this fit in the enterprise? Why was this such a critical thing? The tracing argument I can give you is that ultimately these agents need to process large scales of data. They need to filter and aggregate. And you need this very specialized columnar engine to be able to give results in time to these agents that are trying to make real-time decisions.
Gemma Allen
>> I love what you're saying, true to the value. Maybe you'll be hearing the bell one day. I'm sure the guys at the NYC certainly hope so. But tell me, I think a lot of people understand Redpanda as a very fast growing, very successful competitor to Kafka. Tell me a little bit about the differentiators. What is it? Is it speed? Is it cost? What do you think really sets you apart? And when you make these acquisitions, what are you hunting for from a commercial perspective?
Alex Gallego
>> Yeah. In many ways there's really two dimensions. We are either trying to help enterprises do more with less. I don't think you can meet a CIO who's like, "Oh, I want more vendors. I want more people. I want more complexity." That's not a thing that they want to say. We started true, we started with the Kafka replacement for mission-critical systems with some of the examples that I mentioned. Last year we bought one of the largest connectivity companies in the world, it was called Benthos. We rebranded it as Redpanda Connect. And the whole thesis there is you need to get data to go from place A to place B and really integrate. Look, it turns out people call this system's legacy because they largely don't understand them, but that's the thing that makes the world tick. One would consider parts of the tech of the New York Stock Exchange legacy if people didn't understand it. Connectors are a way to help us bridge the old world with the new world. It's a way for us to do cross-database replication or extract data from the exchange floor and send it to Snowflake is another good example. That's what the connectivity does. And then this reason acquisition with Oxa, which is a distributed query engine, is a way for us to make sense of all the data. Once it lands in a bucket, in an iceberg table or a lake, in a data lake of sorts, how do you make sense of this data? For us, it's been this very steady evolution into becoming what we're calling this agentic data plane. I think we talked about that evolution from data warehouses into data lakes, now into this agentic data plane. For me, the future is very much focused on that. And the focus has been the same. How do we continue to help the global Fortune 2000s tame the chaos and complexity?
Gemma Allen
>> And when we think about chaos and complexity, one thing we think about a lot is compliance. You've coined them for your own cloud term, which I love. I think it's so smart. But when you think about data and bring your own cloud, you think about technology. But a lot of people actually think about trust and the emotional element of that, especially in regulated industries like some of the Fortune 200. Tell me a little bit about how you approach that, especially from a commercial sales perspective.
Alex Gallego
>> Governance, it's really the current struggle for people to adopt agentic systems, really. And largely is around two things, access controls and observability. But BYOC is something that we really need to talk a little bit more about. Which is, it all builds on this idea of data sovereignty. How does sovereignty differ from privacy? Privacy is largely a checklist. A CIO says, "I need to be HIPAA compliant. And if you're a vendor, I need you to have 52 checks." Make it up, because I don't know. It's actually hundreds of checks. But sovereignty says more. It says, I own the data. What happens with previous generation systems is, sure they gave you scale, sure they give you some security, but in a way you gave up ownership of your data. You now send it to their walled garden. And one, it's very expensive. But two, you're limiting your design and in the things that you can build in your enterprise because you no longer own your data. You're paying for the service. BYOC brought back this idea that you own your data, you own your destiny. In the age of AI, that's really ever-presence because data is the mode. Your private data is the mode in the age of AI.
Gemma Allen
>> For sure. And I'm sure for so many of these companies too it's about mission control. It's about ensuring that if you have a span of agents, they have guarded access to certain parts of your infrastructure and your workflows, as opposed to the risk that can happen with fraud.
Alex Gallego
>> Right. It's audited. Make sure that the things that when something did whatever, took an action, let's say move money from account A to account B, you can actually trace it. The right system, move the right money to the right destinations. So tracing, auditing, observability, compliance, sovereignty, confidentiality, I think those are the pillars here that we're working with. And actually, the partnership with Pluralsight today that we're also super, super thrilled to announce is that we are going to market where Redpanda provides this agentic data plane that feeds their reasoning layer. In a very simple diagram, you have agents at the bottom that are taking actions. They are taking information from the trading floor and actually making a trade, or sending an email, or sending a notification. That's the action layer. The next layer is the data layer. I was like, okay, well, those agents need access to private data, that's where Redpanda comes in. And the last layer is the reasoning layer. This is where you find companies like OpenAI and Anthropic, and that's what the partnership with Pluralsight is about. It's about bringing a frontier model, a company that also cares about confidentiality and privacy and BYOC. In the same, they see the world in the same way that we see it so that you have a truly end-to-end execution. So you can go from agents to GPU execution in a full confidential way.
Gemma Allen
>> Well, I'm excited to chat with both Jason and Tyler. But before you go there, let's talk a little bit about you. You are a Colombian immigrant here to the US. I read that you once, as a child, loved to make dirt bikes. You consider yourself a builder. Tell me a little bit about your own leadership journey. This is a very exciting time, but I'm sure a stressful and chaotic one.
Alex Gallego
>> Yeah. For me, it has been this, I don't know, identity evolution in many ways. I think the job of the CEO, it's like, at every stage of the company you're really trying to redefine who you are. What is the best value? And frankly, you're incompetent at the new job that you're doing, and really competent at the previous job. And so, an example. When we were super early, I didn't have a world-class marketing leader. I didn't have a world-class sales leader. I didn't have a bunch of other functions, but I was the best person at the time to do that job. And so the CEO, it's a weird job from an identity perspective because you're always doing things that you're the most qualified for, but really, there's probably someone better in the world. But you have to figure out, who do I hire? How do I ask those questions? It was this journey of my personal identity from being really good at engineering. I built the original Redpanda code base, but I didn't build a connectors, I didn't build a query engine. So into evolving as a leader, as a builder. I think my journey identity is that of a builder. And as long as I feel authentically for myself that I'm continuing to build the future and I'm shaping the way that the future is built, I feel true to myself and proud of the work that I do.
Gemma Allen
>> We have a phrase in Ireland, a jack of all trades but a master of none. But as long as you're and you get it done. Well, I think one thing you're obviously very, very good at is talent spotting. Now, we're going to be joined by Tyler, who's going to join us for this next segment, so stay tuned.
>> I'm Gemma Allen with The CUBE here at the New York Stock Exchange. This is our Redpanda series for mixture of experts. Joining me today in studio, I have CEO of Redpanda, Alex Gallego. Welcome, Alex.
Alex Gallego
>> Thanks for having me.
Gemma Allen
>> Thanks so much for being here. You were here in May, back at the NYSE. I think the data's faster, traders are louder, and things are moving faster in your world. Let's unpack that. How are you holding up?
Alex Gallego
>> It's been a phenomenal summer for us, really in terms of growth from the number of customers. I think, as we'll talk later today, we're expanding the product portfolio in a meaningful way. We've been really thinking deeply what's next for Redpanda. So, excited to be here to share with the rest of the world today.
Gemma Allen
>> Great. And when you were here in May, you spoke a little bit about how you want to see the world move from batch to batch, which is no longer relevant to real time, and event to event type of scenario. Right? Tell me what's happened since May in the space you're in. It seems as though the world of AI is moving so fast.
Alex Gallego
>> I would break up the world into three big epochs. At first there was the movement and the creation of the idea of the data warehouse. It was self-hosted data, really hard to scale, really hard to manage. You move it to the cloud, you separate compute and storage, and now you have a really cost-effective way, but most importantly, really scalable to do analytics. Part of the problem with self-hosted provision is that it's just hard to scale, hard to operate, really expensive, brittle. Really, the cloud gave people elasticity. It gave people a way to really actually get value out of the data that they were generating. That was data warehouse. And tabular data separated compute and storage. The next evolution from that was this idea of the lake house. For lack of a better word, it became a dumping ground, not just of tabular data, but on any kind of data, video data, music, images, things that didn't really have shape, PDFs that had to be extracted and meaning had to be created for, et cetera. But the idea was, look, these tools are so useful that why don't we throw all our data into this one place? And then we led the query engine deal with the complexity. I think we're in a new transition for the world right now that we're calling the agentic data plane transition. Which is, lakes are stagnant. They're vast and large, but they're stagnant. And I think agents need this bidirectional way of communicating what they're both consuming but also contributing back information to this idea. And I think the world needs a new system. It's not just that code was generated, it's that the architecture is so different from what we're building that you really need a new fresh take, if you will.
Gemma Allen
>> And what you described there, it's high impact, it's high value. We have some phenomenal guests in the mixture of expert series. And one thing we hear a lot is that a lot of enterprises feel that they're not still deriving the value that they expected from this world of AI, and even especially agentic AI. Tell me about some of the customers you work with, like you work with the Olympics, some very big names known to everybody. Share some of those use cases.
Alex Gallego
>> We grew up really powering tier zero mission-critical systems. Examples of those is we protect Whitehouse.gov. Through Akamai, we power all of the electric car companies in the US. We power probably the largest banks in the US right now, so it's likely that your paycheck is actually clear because Redpanda's up and running. Or that you are able to get to work. Because when you tap your iPhone onto the payment device, it went through eventually to a system that's powered by Redpanda. That was our bread and butter. If your business depended on this messaging infrastructure to make money to function, now those were the kind of businesses that we wanted to power, and they tended to be the G2K. Now, with agents, the next challenge from them is really two things around governance: access controls and observability. Are these agents accessing the data that they're supposed to access? That's one. And two, when something goes wrong, let's say that this model had a gender bias. Can I go back and figure out why this model denied my credit? How did this happen? And so you really need a different take on the architecture. Those are the next challenges that we're trying to help enterprises with.
Gemma Allen
>> Tell me a little bit about what's been happening from you as a company. Earlier this year there was rumors of a Snowflake acquisition. I know you've hired the CTO of Snowflake since, you were going to have him later on this segment. But tell me what's been happening from an acquisition market perspective. You guys have been busy, some big announcements.
Alex Gallego
>> Yeah. I think Redpanda has always had people that basically every big business in the world has had many offers for exit. We've remained pretty focused on helping what we call the builder makers and doers shape the future. Tyler joined me from Snowflake as my new CTO, and we're super thrilled to have him. There are a few people in the world that have his level of expertise. In particular, around processing large scale data. First, his experience at Google building some of the largest query engines in the world. And then later on he went on to build really large scale systems for the next generation of query and at Snowflake for these things called dynamic tables. Those were his core ideas that he brought to the world. For us, it's actually the opposite. And I think today we're just super excited to announce that we've made an acquisition of a distributed query engine. And Tyler is going to join us later today to give us the details as to, how does this complement the Redpanda product portfolio? Where does this fit in the enterprise? Why was this such a critical thing? The tracing argument I can give you is that ultimately these agents need to process large scales of data. They need to filter and aggregate. And you need this very specialized columnar engine to be able to give results in time to these agents that are trying to make real-time decisions.
Gemma Allen
>> I love what you're saying, true to the value. Maybe you'll be hearing the bell one day. I'm sure the guys at the NYC certainly hope so. But tell me, I think a lot of people understand Redpanda as a very fast growing, very successful competitor to Kafka. Tell me a little bit about the differentiators. What is it? Is it speed? Is it cost? What do you think really sets you apart? And when you make these acquisitions, what are you hunting for from a commercial perspective?
Alex Gallego
>> Yeah. In many ways there's really two dimensions. We are either trying to help enterprises do more with less. I don't think you can meet a CIO who's like, "Oh, I want more vendors. I want more people. I want more complexity." That's not a thing that they want to say. We started true, we started with the Kafka replacement for mission-critical systems with some of the examples that I mentioned. Last year we bought one of the largest connectivity companies in the world, it was called Benthos. We rebranded it as Redpanda Connect. And the whole thesis there is you need to get data to go from place A to place B and really integrate. Look, it turns out people call this system's legacy because they largely don't understand them, but that's the thing that makes the world tick. One would consider parts of the tech of the New York Stock Exchange legacy if people didn't understand it. Connectors are a way to help us bridge the old world with the new world. It's a way for us to do cross-database replication or extract data from the exchange floor and send it to Snowflake is another good example. That's what the connectivity does. And then this reason acquisition with Oxa, which is a distributed query engine, is a way for us to make sense of all the data. Once it lands in a bucket, in an iceberg table or a lake, in a data lake of sorts, how do you make sense of this data? For us, it's been this very steady evolution into becoming what we're calling this agentic data plane. I think we talked about that evolution from data warehouses into data lakes, now into this agentic data plane. For me, the future is very much focused on that. And the focus has been the same. How do we continue to help the global Fortune 2000s tame the chaos and complexity?
Gemma Allen
>> And when we think about chaos and complexity, one thing we think about a lot is compliance. You've coined them for your own cloud term, which I love. I think it's so smart. But when you think about data and bring your own cloud, you think about technology. But a lot of people actually think about trust and the emotional element of that, especially in regulated industries like some of the Fortune 200. Tell me a little bit about how you approach that, especially from a commercial sales perspective.
Alex Gallego
>> Governance, it's really the current struggle for people to adopt agentic systems, really. And largely is around two things, access controls and observability. But BYOC is something that we really need to talk a little bit more about. Which is, it all builds on this idea of data sovereignty. How does sovereignty differ from privacy? Privacy is largely a checklist. A CIO says, "I need to be HIPAA compliant. And if you're a vendor, I need you to have 52 checks." Make it up, because I don't know. It's actually hundreds of checks. But sovereignty says more. It says, I own the data. What happens with previous generation systems is, sure they gave you scale, sure they give you some security, but in a way you gave up ownership of your data. You now send it to their walled garden. And one, it's very expensive. But two, you're limiting your design and in the things that you can build in your enterprise because you no longer own your data. You're paying for the service. BYOC brought back this idea that you own your data, you own your destiny. In the age of AI, that's really ever-presence because data is the mode. Your private data is the mode in the age of AI.
Gemma Allen
>> For sure. And I'm sure for so many of these companies too it's about mission control. It's about ensuring that if you have a span of agents, they have guarded access to certain parts of your infrastructure and your workflows, as opposed to the risk that can happen with fraud.
Alex Gallego
>> Right. It's audited. Make sure that the things that when something did whatever, took an action, let's say move money from account A to account B, you can actually trace it. The right system, move the right money to the right destinations. So tracing, auditing, observability, compliance, sovereignty, confidentiality, I think those are the pillars here that we're working with. And actually, the partnership with Pluralsight today that we're also super, super thrilled to announce is that we are going to market where Redpanda provides this agentic data plane that feeds their reasoning layer. In a very simple diagram, you have agents at the bottom that are taking actions. They are taking information from the trading floor and actually making a trade, or sending an email, or sending a notification. That's the action layer. The next layer is the data layer. I was like, okay, well, those agents need access to private data, that's where Redpanda comes in. And the last layer is the reasoning layer. This is where you find companies like OpenAI and Anthropic, and that's what the partnership with Pluralsight is about. It's about bringing a frontier model, a company that also cares about confidentiality and privacy and BYOC. In the same, they see the world in the same way that we see it so that you have a truly end-to-end execution. So you can go from agents to GPU execution in a full confidential way.
Gemma Allen
>> Well, I'm excited to chat with both Jason and Tyler. But before you go there, let's talk a little bit about you. You are a Colombian immigrant here to the US. I read that you once, as a child, loved to make dirt bikes. You consider yourself a builder. Tell me a little bit about your own leadership journey. This is a very exciting time, but I'm sure a stressful and chaotic one.
Alex Gallego
>> Yeah. For me, it has been this, I don't know, identity evolution in many ways. I think the job of the CEO, it's like, at every stage of the company you're really trying to redefine who you are. What is the best value? And frankly, you're incompetent at the new job that you're doing, and really competent at the previous job. And so, an example. When we were super early, I didn't have a world-class marketing leader. I didn't have a world-class sales leader. I didn't have a bunch of other functions, but I was the best person at the time to do that job. And so the CEO, it's a weird job from an identity perspective because you're always doing things that you're the most qualified for, but really, there's probably someone better in the world. But you have to figure out, who do I hire? How do I ask those questions? It was this journey of my personal identity from being really good at engineering. I built the original Redpanda code base, but I didn't build a connectors, I didn't build a query engine. So into evolving as a leader, as a builder. I think my journey identity is that of a builder. And as long as I feel authentically for myself that I'm continuing to build the future and I'm shaping the way that the future is built, I feel true to myself and proud of the work that I do.
Gemma Allen
>> We have a phrase in Ireland, a jack of all trades but a master of none. But as long as you're and you get it done. Well, I think one thing you're obviously very, very good at is talent spotting. Now, we're going to be joined by Tyler, who's going to join us for this next segment, so stay tuned.
Gemma Allen