The New Defense Prime: Breaking Innovation Theater, AI Adoption, and Data Fusion with Raft CEO Shubhi Mishra

In this episode, we’re joined by Shubhi Mishra, founder and CEO of Raft, to talk about what it takes to become a new defense prime. Shubhi challenges the dominance of legacy primes and makes the case for smaller, faster-moving companies that can deliver what the warfighter actually needs. Through her work at Raft — a defense technology company building agile, AI-driven solutions for data fusion and rapid decision-making — she’s tackling one of the most urgent problems in defense: integrating siloed, vendor-locked systems. Shubhi shares her perspective on breaking free from “innovation theater,” reforming acquisition processes, and building real, interoperable solutions at the speed of relevance.

Read more about Shubhi here.

Transcript

Unknown: 0:00

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A'ndre Gonawela: 0:09

Hi, my name is Andre Gonawela. Welcome back to the Burn Bag podcast. Today, we're going to take a little break from all of these geopolitical developments to talk about a key issue that we've talked about a couple of times over the years, but we haven't really delved into too deeply, defense innovation work. So some of you may know that I used to work in defense innovation. I'm still very passionate about it. You know, how do we get the U.S. Armed Forces the latest and greatest in technologies and capabilities? But how do we do that swiftly How do we do that on an accelerated timeline? But most importantly, how do we actually get the military what they actually need versus these nice-to-haves that cost billions of dollars that then bloat our DoD budget into this $1 trillion monster? I have a really great guest today. Shubhi Mishra is joining me here today. She is the founder and CEO of Raft, a cutting-edge defense technology company delivering AI-driven, modular solutions to some of the U.S. government's most complex digital challenges. She is quite the star herself in DC Circle. She is a two-time WASH 100 awardee. She is also a very vocal advocate for overhauling defense acquisition processes to break free from, quote, innovation theater and empower agile, non-traditional firms She also champions a mission-focused, buy-what-you-need approach to modernization, emphasizing speed, interoperability, and real impact at the tactical edge. These are all things that I believe we need to be working more adequately towards. So Shubhi, thanks for joining me here today. I really appreciate it.

Shubhi Mishra: 1:45

What a great introduction. No, thank you so much. Looking forward to this fun conversation.

A'ndre Gonawela: 1:50

Yeah, and it's nice to also have another like South Asian American, you know, in this podcast room. I mean, so often, right? Like I sort of kid that this podcast or our guest line is like big white wall of men who dominate our sector. I'm South Asian myself, and it's really nice to see another, you know, doing such incredible work in this field. So

Shubhi Mishra: 2:09

thank you. No, super excited to have this conversation. And yeah, looking forward to a very cognitive leader of our conversation.

A'ndre Gonawela: 2:17

Yeah. Before we dive into some of these specifics, Shubhi, can you tell us a little bit about yourself, a little bit about your life, your bio, and a little bit more? Because I found it really interesting, and I'd love to let the audience know about that.

Shubhi Mishra: 2:30

Yeah, absolutely. Let's see. So I've been in this country for almost a decade now. I grew up back home, which is India, North India, specifically Delhi. So I came here with a biggest and beautiful dream of, you know, solving a lot of hard problems and making global impact and have just been focused on that every single day. And it's compounded interest has resulted in where I am today. And, you know, being in the, I feel the best city in the world, the impact this DC, Washington DC has and the entire world is phenomenal and being surrounded by and being in the defense ecosystem, you know, for all the reasons you just introduced the audience with has been phenomenal. And I'm an engineer and a lawyer. I have two beautiful kids, 10 and 8. And I'm a big Peloton and tonal fanatic. And let's say, and on vacations, I mostly, you know, go to national parks and hike and go away from the people. And it's been fantastic. And yeah, you know, and my purpose in life is really all about finding the best version of myself and realizing and trying to understand why I was born. And in the team that I surround myself, I push them to do the same. So it's been an incredible journey thus far.

A'ndre Gonawela: 4:02

Now, that's awesome. And when you say, you know, you take vacations in national parks to get away from people, when we're talking about that bureaucracy, when we're talking about that acquisitions process, boy, oh boy, are there a lot of people in there. So not to, you know, have a very odd segue, but, you know, I think, you know, when I was doing some research for this interview, when I was, you know, trying to get these questions together, one of the things that I noticed about Raft's website, Raft being the company you run, is that when you open it, you sort of see the words new prime. And a lot of folks in the defense ecosystem, they've heard of this word prime. But can you tell us, you know, what does prime actually mean in the defense industry for those who aren't as familiar?

Shubhi Mishra: 4:45

Absolutely. Prime to our definition of prime is really using a lot of people, and to solve the problems versus products to solve the problems. And that is really differentiated by, you know, the scale automatically turns into how do these prime have these physical, large physical infrastructures from office space to locations to their presence and a lot of people with an idea and intent to solve these mission problems. But the gap always happens is they are not making operators faster, quicker, or better. They are just providing more people to do the job, which doesn't scale in today's era. These

A'ndre Gonawela: 5:48

primes, for example, I don't want to name who these primes are, obviously, in case I have them as guests on in the future. But when we're thinking about these primes and we think about how large they are, how many people there are, do you think they're almost becoming an extension of the government in a way, an extension of DoD with the reliance on these types of companies?

Shubhi Mishra: 6:12

I would absolutely agree. And I think, you know, in the past, it has worked because we were in the peacetime, like I would say. And now we're in a very different time, whereas there is a really race against a lot of the technology that our adversaries have and are investing so much more intentionally into to get them far ahead. And not only they are a reflection of the big bureaucracy in the government and, you know, the government has bureaucracy for the right reasons. There are a lot of irreversible decisions they make, and bureaucracy helps prevent these decisions and makes them slow down. But what you need as a partner is absolutely opposite to that. And what you need in a partner is scaling rapidly, fast, pivoting until you find the best version of the product that you deliver, and finding the gap that the government cannot find. such that you make them better and not a mirror. And so I think going forward, this dynamic will completely change. More new, new primes will emerge. And with this idea of where the gap is and let's really attack the gap versus creating a mirror.

A'ndre Gonawela: 7:26

So can you tell us a little bit more about Raft, what the company does, and especially for those who aren't as familiar with defense technology and really a lot of these types of technologies, and how is Raft redefining what it actually means to be a prime? I mean, like, what does it actually mean?

Shubhi Mishra: 7:45

So Raft is a defense technology company that is focusing heavily in autonomous data fusion, leveraging artificial intelligence, LLMs, limited language models, to make operators super operators. And our approach to solving these mission sets is completely opposite to the way it's been solved before. We are very much focused on solving for user needs by sitting right next to them, rather than sitting where the enterprise is or a PEO is and Solving for buyer needs. And then in addition, rapidly scaling to these bespoke problems. If you, if, so stepping back for a second, right? I have, Raft is very diversified into the services it supports from Air Force to Space Force to Paycom, SOCOM. And what I, and, you know, I visit, you these services on a very frequent basis. I'm always on the plane. And what I've seen is everyone has a very nuanced two problem that they want to solve for. And because it's very nuanced, what it results in, in creating nuanced solutions for it. And what the large primes are focusing on is a one size fit all solution. And that's why they're never able to meet the operator needs, the end user needs. They're able to meet buyer's needs because it solves for writing, you know, one contract document that has all the requirements. But what isn't solved for is like what the guy, you know, in the forward edge in Philippines wants. It doesn't solve for that. And the only way to solve for that is actually going out there, talking to the person, talking to operators and finding a solution that is an extension of what the product is. And so Raft is very much focused on that. And that's how we have differentiated ourselves from all the others out there. And then, you know, in the days of, thank God for Chad GPD, you know, now you don't have to fight the battle. It's like, of course, everybody must use AI in the day of AI, like rapidly scaling and pivoting to find the how AI can make a day in the life of an operational user better has been a game changer. And so we are focusing so much of that and that's how we differentiate ourselves from all the others and regularly participating in these large-scale exercises that define the area of responsibility for a co-com. has been also a differentiating factor.

A'ndre Gonawela: 10:42

Absolutely. And I think you mentioned something very important. Companies need to be sitting with the actual warfighters, the folks who are actually at that forward edge to identify the needs, the requirements, the pain points, really. And I mean, When you're thinking about the DoD acquisitions process, there are so many layers, so many senior officials, commanders, officers who you need to get the approval of. You need to satisfy the various stakeholders. You need to get this action officers involved. You need to get the senior officers approval and so on. And that's such a battle to get through. So I mean, what does it actually take to build something the warfighter actually wants and needs versus filling a request by a military entity that wants something with AI just to have something with AI because it's a sexy new technology, right? Because sometimes I feel like, especially in my past experience, we'll have these entities who want these new technologies, but there won't really be a problem to solve with it, they'll sort of mold the problem around the solution and sort of force fit it in versus the other way around, finding a solution that fits the problem.

Shubhi Mishra: 11:59

In my opinion, DoD and government at large, it's a very consensus-based decision-making process. And there's no, yes, there's a sole decision maker with whoever the authority lies, but the sole decision maker depends on a lot of people to get and understand that decision and make sure it's the right decision. And so I think the answer is and and not or. It's what we have done and been successful at. And this is something I'm often asked of new upcoming companies when they seek advice is, And I think you cannot alienate the buyer community or share with them how wrong sometimes they could be. And while making sure that you are championing for the users because Over a period of time, it catches up. Either your product is being used or it's not being used. Either it's being talked about in the circles or it's not being talked about. And the question just becomes, you know, this large framework of abstract of meet these requirements. How do you really tailor them and be creative such that you can champion the user needs through that? So it ultimately comes down to that. But I think it's an end question and end answer, I should rather say, rather than How do you choose to do one or the other? And the end answer is, you know, learned it the hard way is it's about, it should, unfortunately, and that's what for the vendors, a lot of the cycles are spent on that they rather not be spent on, but it is part of playing the game is you got to make sure it meets everybody's checklist to the maximum level. So

A'ndre Gonawela: 13:44

you've spoken out against innovation theater in defense. What does that term actually mean to you? And how do we get beyond innovation theater?

Shubhi Mishra: 13:52

Yeah, so it's the performance. You and I were talking about it a little bit before, but it's the performance to make everyone around you seem or believe that action is resulting in impact. I think innovation theater is sometimes needed to get the marketing cycles in, but then I think the shift needs to happen right after or sequentially or parallelly about how do you make this, what you're talking about into something a user can use on the farthest edge and have it delivered operational value. And it's easy to say, and everybody has great intent, But it's so hard to do. So I'll give you an example. I just came back from Indo-Pekong, Hawaii, and I was on the island for a couple of days, you know, just meeting with the decision makers. And I some of the time is spent at the AOC and our folks that are working out there, working with, you know, people in uniform. So you have this old, you know, World War era buildings that you can imagine the state, right? There's barely coffee, even a vending machine. There's nothing like that exists. And then to you, that's your skiff. That's where you live out of. And then you come out in the blazing Hawaii sun.

Speaker 01: 15:22

Oh,

A'ndre Gonawela: 15:23

gee, yeah.

Shubhi Mishra: 15:24

you know, without any fans, but it's a ticky bar, which is kind of cool, you know, with like those old-fashioned shades on them. You come out, you know, you catch up on life or you use the unclassified version of a computer to check on any updates or how to fix a problem. And then you go back in and do the same thing. And you do that day in and day out. And that is not easy. But that's necessary to turn that in into operational value. And I think the last part, the doing the do and the hard do is where most of us fall short because it's humanly, it's humanly hard, physically hard.

A'ndre Gonawela: 16:06

No, yeah, exactly. And I mean, like when we're talking about, you know, what do we actually do? work on produce to gain that operational value? I mean, what types of metrics or outcomes are we using to determine if that capability is truly impactful versus being more of that performative innovation? I mean, I've spent a couple of years working in the defense innovation space, and nowadays I sort of cringe when I hear the word innovation being thrown around by so many different people who'll sort of use that term to just latch it onto anything new. So

Shubhi Mishra: 16:40

I think it starts with participating in exercises, these exercises which are replicating how a battle or war may be fought. And it starts with that, and it starts with, can you do with less humans? Can you do with not a whiteboard? How much can you automate end-to-end? And the result of that ends up with more and more operational users, operators using your tool, And then the word of mouth circulating across the board. So now that we have, let's say, a particular AOC tomorrow, we have another one added. And added because they want to and they want to use and they want to make their life better, not because it's coming top down. And I think that is the metric that we keep a close eye on. And I highly recommend, you know, businesses to do that. And that requires a lot of investment. So instead of, you know, this is, again, one of the conversations I'm asked often, instead of investing in maybe a large growth team or, you know, business development team, invest in finding ways to participate in exercises and really demonstrating value because there's a wide gap right now that exists. And if you can make anybody's life easier, they will not let you go.

A'ndre Gonawela: 18:00

Oh, absolutely. So I want to move the conversation into a little bit about the work you do at Raft, because it's fascinating work. I'm still trying to wrap my head around it as I'm not a technologist, so I'll definitely appreciate your help in trying to understand this. But you talk about data fusion, autonomous data fusion, how it's a big critical challenge in today's defense environment. Can you tell us a little bit more about what autonomous data fusion is?

Shubhi Mishra: 18:30

now data fusion is being done by human beings using their gray matter and if we want to get to the level we want to and compete with our adversaries who by the way have not only figured out end-to-end systems and and can where everything talks to everything so it's just faster because of the nature of it but also are continually investing in technology um we must shift from humans gray matter to doing the do to machines doing most of it autonomously and such that a human is observing it and making sure it's doing the right way.

A'ndre Gonawela: 19:11

So this is like the conversion of different types of data into one universal language.

Shubhi Mishra: 19:17

So it extends a little bit beyond that, right? So that is the data fusion process. but autonomously requires machine learning models in an AI to not only read what different formats, standards, schema, whatever you call it, whatever is coming in, and then translate it back to how an operator would want it in how they consume the information. A, you know, a, somebody, a pay comp, somebody's area of responsibility within a pack half may be different from a pack fleet. And they, they consume information different way, but they need similar information. These systems that they're using or consuming information from are, have been built in different decades by different vendors and, and, you know, which are not necessarily talking to each other. So it's always, how do you make sense of all this stuff into something that the operator has been trained on? And the way different services grow and teach their operators very differently, and you have to autonomously make sure the information they're consuming makes sense to them.

A'ndre Gonawela: 20:37

So it's like you have all of these different capabilities, these different platforms, these different types of technologies, computers, whatever, who are all outputting all of these different types of data. Say you have a team of people, one speaking Hindi, one speaking Spanish, one speaking English, one speaking German, and you have all of this great data, but the one person who needs to make a decision on it cannot easily understand it, cannot easily translate that into one universal language like English or something. And we need to do this automatically. So it's that sort of a very rough allegory.

Shubhi Mishra: 21:17

Yeah, that's exactly it. And what you said at the end is super key. It's like it is using their language, whether that is English or something else. And using natural language. So it's not necessarily as a human as you would interact with something. And that's where the autonomous part comes in, the natural language part comes in. So far, the tools that exist and have been deployed are... not natural language tools that are not a human talking to another human tool. So imagine now, go back, imagine when operators are doing their job. When they pick up the phone and call the other guy sitting near the skiff, they're using human language. They don't use machine language. But the tools right now that exist, it's a machine language talking to a human. So if you want to change the behavior and if you want to change AI being the forcing function that enables them, we gotta replicate this phone call to the upper operator and make it frictionless and human talk. So that's where the autonomous part comes in and the data fusion is just around the machine to machine talk.

A'ndre Gonawela: 22:27

Yeah, and I mean, when I'm thinking about why that's so important, I'm thinking about all of the different things that the DoD is procuring, whether it's fighter jets, whether it's sensors, whether it's the new unmanned capabilities, whether it's all of these different types of technologies, folks, that we're thinking about that one may use in a singular operation, you know, when we're bringing one of those capabilities in, we want to integrate that into the broader force to make sure it all sort of fits seamlessly. And, you know, I'm noticing this, you know, not just in a US context, but like a lot of our Asian partners, for example, right? They're like procuring different types of capabilities, right? Like, you know, India is buying fighter jets from France for example, the Rafales. Are those Rafale fighter jets fitting into the broader operational capabilities of the Indian Army? Are they sort of making sure that all the data can sort of talk to each other? And, you know, I'm definitely observing that as we're expanding the aperture of acquisitions beyond the U.S., but into the allies, with the allies, especially with things like AUKUS, with things like, you know, U.S.-India defense cooperation and so on. Is that... Correct.

Shubhi Mishra: 23:41

You're 100% on point there. And it's almost like you're solving for the symptom. symptom of new technology, new technology, but we are not talking about the root cause. And the root cause is, there are only two ways to solve it. One, the way China solved it. It's one thing. It's one company, one subsidiaries of that company, and they must talk to each other. And that's what I call about solving end-to-end. And then in America, where there's a multi-vendor ecosystem and the best may win, we don't focus on solving this root cause. Yes, best may win. Right now, humans are enabling this talk track between all these different systems. What happens in the future when seconds result in life and death? And that's not a conversation yet because we're still warming up to it. And I think that's the most important conversation we need to have.

A'ndre Gonawela: 24:35

No, yeah, absolutely. Because I mean, you know, in the current defense innovation ecosystem, we still have a lot of work to do, but we have so many interesting companies, so many interesting technologies, so many new things that are populating, you know, our capabilities. But how are we connecting that efficiently? Because that's a key issue because, you know.

Shubhi Mishra: 24:52

It's the boring part, but the most important part.

A'ndre Gonawela: 24:55

But it's vitally important, especially when you're in the battlefield, when you have, you know, only seconds to make a decision of life and death, you need processing power, right? to automatically do this. Because I mean, again, like, you know, folks, like going back to the allegory about you have the team of different people who speak different languages. If you have a human doing it, it's going to take so long to actually do that translating by hand. I mean, folks go back to your French classes, right? And think about how hard that was. I mean, if you had a computer doing it, it'd be fantastic. So, I mean, you know, when we're talking about, you know, universal data fusion, what does that actually mean? look like in practice and why is it so hard

Shubhi Mishra: 25:36

yeah i mean see it's hard because technically it's hard right i mean to solve for it's just decades of different vendors decades of different systems and and the way dod has wanted to solve for it to make a standard standardized things and the problem with that is and that's why there's not a lot of buy-in and people who are making these decisions don't understand the ground truth, which is Space Delta, Space Force Delta is solving for their specific area of responsibility. They will create something that helps them get that information faster and quicker. On the other hand, you know, some organization within Air Force or Navy, they will solve for very specific ways they want to solve for. And so could they adopt this standard? Yeah. Would that result in them losing precious time to enable their decisions? Absolutely. And so this one standard, size fit all, has not been adopted. And I think it should be the reverse of it. You do whatever you need to, but let's make sure the data fusion autonomously happens. So I think technically that's one big challenge, just really hard engineering. The second is it is bureaucratically challenged and there are a lot of policies that stand in the way. And those policies were designed for good reason. And however, there are too many policies now and nobody wants to share data with the other entity because, I don't know. To me, those reasons don't make any sense, but they are politically and bureaucratically challenges. And I think a lot of those are also fed by their different vendors wanting to protect the territory and making sure they can protect the territory if they don't share data. That's a huge problem. piece of it. And I also think the third piece is, I don't think Congress has looked at this problem statement super closely. I've spent a lot of time on the Hill, continuously do so. And I'm amazed at the gap they have between what the information they know and gather to what the information is on the field. And that's where, you know, they've appreciated my insight because I'm able to translate and get, they can hear it from the horse's mouth or almost from the horse's mouth of the gap. And I think they haven't asked these questions. They haven't focused on this so much and they just get pitched how new things will solve this problem forever versus we must find a way for the old and new to come together. So more focus from Congress would also help this. But that's what I would say, the three challenges. Technically bureaucratic and not enough oversight, congressional oversight.

A'ndre Gonawela: 28:53

Oh, yeah. No, no, for sure. And I mean, like, how do you... I mean, when we're talking about how you actually do this, like, how do you actually approach integrating these disparate data systems, you know, from these multiple vendors? Like, what's the key to this?

Shubhi Mishra: 29:07

So... Technically, there are things that, at least the way we have approached it, is really developing an abstract layer. And so, you know, that gives you 70, 80% of the way. And then some of these things are... Just similar type formats and so text format, you know, video or pictures and just putting them in bigger buckets and then figuring out how to parse through that. So that's one way technically we have done it. And the next is really a lot of partnership with other industry partners. And what that helps us is, and I would say any vendor helps is, it fastens the getting to the end phase. quicker and we get there faster just because then you don't have the additional bureaucracy of just DoD and government coming in the middle and you can just make B2B connections. And so their system can talk to your system and, you know, you get to the end result faster. So that's how I would say we have approached it.

A'ndre Gonawela: 30:15

No, for sure. Definitely. And, you know, we talked about the information gaps belying our congressional representatives. We talked about, you know, why there are gaps between the forces and sort of the stylification of that data. But do you think the acquisition community itself, I mean, fully understands the implications of fragmented data architectures?

Shubhi Mishra: 30:39

I wish they do. I wish they would. They're not living the pain.

A'ndre Gonawela: 30:44

Why not?

Shubhi Mishra: 30:45

The pain must be felt. And there's only one reason to feel this pain is go out to Guam, go out to Philippines and see and experience a day in life of that operator. I think that will be game changers. And I feel the ones acquisition professionals that I've come across who have in uniform, I specifically say that have rotated out. or have experience towards the far edges are the most, provide exponential results for these communities because they understand. Yeah,

A'ndre Gonawela: 31:22

absolutely. So I mean, When we're thinking about all of these challenges, not just within autonomous data fusion, but sort of some of the larger challenges, I mean, you allude to, I think, what you just said, right, about the acquisition community, those officials not really understanding the pain because they don't feel the actual pain. How do we work towards this? I mean, what does the next generation defense contractor do? look like? How do they navigate this intense, complicated, soulless acquisitions framework with all of these different entities, these different people you need to communicate the pain to, make sure you're not communicated within a silo and so on? How do contractors navigate this?

Shubhi Mishra: 32:14

So I think there is a now what we need to do, and I think there'll be a different future in a few years from now. The now is unfortunately, we got to bring the two communities together and really have the users advocate for what they want. And that's the other big gap I've seen is users don't know or have a blueprint of how to even ask for what they want. And that's where vendors like us can help them because we know how the game is being played. I say game. I have a lot of respect for this game. It's a beautiful game. It's

A'ndre Gonawela: 32:57

a game nonetheless.

Shubhi Mishra: 32:58

Yes, yes. But I do think it is educating and enabling these operators on the edge to go to the acquisition community to get them what they need. And it's continuously a lot of conversations. I also think the... It is the only model we have seen for success for any vendors in this ecosystems are the big prime or the legacy model. And I think the new primes should absolutely, and it's not intuitive, it's against the human intuition, should absolutely fight against that and make sure that they don't end up being bloated. Because bureaucracy burns cash.

A'ndre Gonawela: 34:20

overly bureaucratic organization?

Shubhi Mishra: 34:23

Three letters. ABC, always be cutting. Cut what doesn't work rapidly, invest in what's working. I think that's the simplest way to structure it. And the beauty of now with these AI tools is you don't need that much manpower, for lack of a better word, to do a lot of these things. I think... Invest in the people that want to multiply and are 10x and not invest in things and processes that don't work.

A'ndre Gonawela: 34:59

Yeah. And I mean, you know, I sort of noticed this with like a lot of these companies that have been startups that sort of start off small as they have success, as they grow. And you're in this sort of this weird space where you're a midsize company. Growth is accelerating. And then as a result, you almost feel the need to put in bureaucracy, right, to make sure that you can manage your organization well. I mean, people will often say that being small and agile. is the advantage. However, how do you scale up an organization to fill these needs, to grow the success and so on? Where's the middle ground in terms of that management?

Shubhi Mishra: 35:43

So I'll tell you. So it's one of those things where, look, if a company is selling that their capability and products is all around enabling operators through artificial intelligence, machine learning, and data, they better be doing that on their side of things, which means is they must over-invest in these tools for themselves and make 1x to 10x. And so the same thing applies because that's the premise of everything. And in my opinion, it's always going to be, unintuitive because it's so new, the capabilities these AI is providing you. But I think fight that urge to have a bunch of middle managers. Fight the urge for you need a human to help a human to help a human. Fight that. That just slows everything down. You have too many decision makers. And I approach it very differently where it's who has the veto versus the decision, right? More confusion results stops moving fast and stops agileness. And I understand this idea of middle-sized company versus small company versus large company. It's measured by revenue, but I think a lot of that is changing. I do think in today's world, it's all about what value you're creating and how you're solving the mission. Thanks to not only the recent advances in AI, but also the new government in charge, they're very much focusing on what capability do you provide versus how large your team size is. And given all of that, I really think it should be very much focused on Solving the mission needs, that creates a lot of value versus, I don't know, scale with millions of dollars that are humans that will be replaced any day by AI in any case.

A'ndre Gonawela: 38:12

Yeah. And I mean, when we're talking about AI, I mean, you know, a lot of people have a vision for how AI can integrate into our capabilities, but it's a very vague vision blocked by a lot of fog and a lack of clarity. But, you know, there's also a lot of caution in how AI integrates into our defense capabilities. I mean, it should be... does good AI adoption and defense actually look like? And what should it not look like?

Shubhi Mishra: 38:42

So the way I think about it is just AI in terms of decision-making lens. As a human being, there are two types of decisions you end up making. As reversible, doesn't cause life and death. Irreversible, your action or decision will result in life or death. Majority of the decisions that are being made within the ecosystem are reversible. You can change your decision if it's not the right decision. You can go back. And I think that is absolutely prime for anything artificial intelligence brings in. Where your decision causes life and death, we must proceed with a lot of caution. There's no coming back from there. There we... must test this. There are a lot of exercises. There are a lot of testing that needs to happen. Even after that, there always needs to be an operator on the loop or the human on the loop to make sure the decision is the right decision. And furthermore, if you go into it more, it's just not about AI tools. It's about AI tools that are showing you how they're making the decisions. There are a lot of tools out there right now in the ecosystem. You give them a question, they'll give you an answer. That's not the right way to approach it. For a human and machine to build trust, the machine must show how it's thinking and how it got to the answer. And over time, you will build trust with it. You like it or not like it, or you tweak it. But at the end of the day, showing that thinking is going to be critical for this integration of decisions that can be reversed.

A'ndre Gonawela: 40:25

Absolutely. And I mean, how do we also ensure the ethical, operationally relevant and secure AI integration in national security missions? Because I mean, that's some of the biggest concerns that people will have about AI. I,

Shubhi Mishra: 40:40

again, think of it as the two buckets of, you know, if your decision can be reversed, then Let's weigh it less in terms of these stage gates we have of something being ethical or non-ethical. Of course, nothing should be non-ethical, and that's why we should be testing this out. But over-emphasis on it, massive regulations on it when it is an irreversible decision and a life-or-death decision.

A'ndre Gonawela: 41:09

Gotcha. So, I mean, you know, as we sort of run this interview out, I mean, you've said fear is the greatest enemy of progress. I mean, how does that inform your own leadership style at Raft?

Shubhi Mishra: 41:20

So I've always said run towards fear with a lot of courage. And I think as human beings, we, our monkey brain, our amygdala brain, it's a fight and flight and the minute something hard comes in, you just want to flee. And I think that's the signal to run towards the hard problem, run towards your fear with a lot of courage. And that is something we do every single day. And that is the sole reason why raft is where it is and where it stands. And I, that is the sole reason for the curve of past six years for us has been so exponential that we are sought out by our customers to come help them versus the other way around. And if you're not running towards fear with a lot of courage, you're not having fun, right?

A'ndre Gonawela: 42:23

I mean, how does one have fun amidst all the friction and the inertia of this defense bureaucracy? Because I mean... It sounds like a whole lot of not fun.

Shubhi Mishra: 42:36

It is. Oh, the mundane parts are boring. And yes, those are just things that need to be done. But it's so much fun to forge a new path and to redefine the word prime, to really help these operators who need help. There's so much... Meaning, I mean, I'm going to go a little philosophical. There's so much meaning in life for that. I mean, you know, when you think about all the time you spent and all the nights you stayed up, and if you realize that this is the impact one had on the journey of a country that impacts the world at that scale, it's beautiful. Couldn't be more fun.

A'ndre Gonawela: 43:29

So what changes, I think, technological or institutional, are you most excited about over the next 12 to 18 months? Because I mean, you know, within the span of like one year, we see so many technological advances. I mean, if we're looking at China, we saw deep seek suddenly. come onto the world stage and that set off a firestorm of shock and awe and so many other things. And, you know, we're in a new administration now. There are a lot of institutional changes occurring. What's exciting you the most about these types of changes we're seeing in the short term?

Shubhi Mishra: 44:03

I will say, yes, there's a lot of conversation in the media, in the administration, on the hill around AI, but it is not getting to the edge yet. It is not getting to the people that can use it to make their lives better. And so I'm super excited to see the adoption and the trust that the operators start building with these AI systems. That's one. And the second thing is there's a lot of PowerPoint talk still, a lot of innovation theater. So, you know, that's the other part. Now that the innovation theater can act fast and can result in action more because the time is now, I'm excited to see those PowerPoints being turned into valuable tools that can change lives.

A'ndre Gonawela: 44:59

No, absolutely. Shubhi, thank you for joining me here today. This was a really great conversation. I really appreciate it. I really appreciated connecting. on, I think, artist Dane for innovation theater, because I think that's a huge blocker of progress. But I mean, you know, I really found the conversation on Data Fusion really fascinating. And for our audience members, definitely check out Raft's work. Data fusion is a very important topic if you're interested in defense force modernization. But also, I mean, think about Shubhi's lessons on leadership style and organization and so on. But Shubhi, thanks for joining me here today. I really appreciate it. t

Shubhi Mishra: 45:40

It was fantastic, Andre. Thanks so much. Thank you.