How AI is Disrupting the Consulting Model | Arda Ecevit, Ex-Bain & NexStrat AI Founder

Transcript: How AI is Disrupting the Consulting Model | Arda Ecevit, Ex-Bain & NexStrat AI Founder

Namaan: Today we're going to talk about what AI is doing to the consulting model. And I'd just love to start, Arda, if you don't mind, by just getting your take, because you were on the inside. You were at Deloitte, you were at Strategy&, and you were at Bain, just getting your take on what made you believe that the model just wasn't working anymore. What prompted you to leave what I'm going to call traditional consulting and go start NexStrat?

Arda: Yeah, sure, Namaan. So even before AI came into our lives, I started noticing, together with my other colleagues, of course, some increased pressure from clients and shifting demands towards more agile strategies. Because if you think about it, strategy used to be a long-term process. Maybe most of the work used to be on building multiple year plans for the clients, but increasingly as the world started to move faster and as the increase on certainties, of course, also demanded, clients started looking for becoming more agile in how they plan for the future, how they make decisions.

And so rather than asking for, you know, big strategy decks covering the next five years from consultants, they started demanding help on setting up the process and the operating model to gain that agility. And also quickly figure out the answers and collaborate with consultants and get support on actually implementing those strategies and actually creating value. Increasingly those were being asked by the clients. And so this was a major force that required consultants to adapt.

And a second thing I noticed was, of course, especially in the earlier days, even before Google, one value consultants could bring to the table was the knowledge, basically, right? But, you know, especially with AI nowadays, it's very easy to access knowledge. And even consultants are trying to learn and figure out how things will become going forward with such significant disruptions, right? Affecting every business and every industry. So that's also another disruption or a major change in the space, which I noticed then and is increasing in relevance today.

So making sense of the information, of course, remains to be important and consultants should have their great judgment remain to be a source of value they bring. And yeah, maybe tying to the first point, clients are increasingly also expecting to pay for the results rather than hours. So success-based engagements are becoming more and more prevalent, and that's another thing I noticed.

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Speed as a competitive advantage

Namaan: So Arda, I do not want to put words in your mouth, but I do just want to ensure that I'm understanding what you're saying. So what I hear you saying is that in a world where knowledge is becoming commoditized, speed becomes a huge competitive advantage. And you just felt like you were able to deliver that speed of solutioning to your clients better by leaving traditional consulting. Is that an accurate interpretation of what I'm hearing you say?

Arda: Well, after consulting, I joined the food delivery platform Yemeksepeti, Delivery Hero's Turkey business, to service their chief strategy and transformation office. Partly because the nature of quick commerce is quite fast, but it's true for also other industries nowadays. I noticed that you wouldn't have time to figure out the perfect answer and build the nicest slides for every problem you face. So therefore, we really had that time pressure on us and that was one source of inspiration for NexStrat as well, because AI agents can really help with that agility, and if you give them the right tools and if you set up the right environment and if you make the agents follow a similar process, mirroring how consultants think and operate, then you get this special type of capability, let's say, to make that happen. And that was the inspiration.

Namaan: I love that. My own personal definition of problem solving, which maybe nobody cares about, is just like, can you get to a reasonable answer within time constraints? Not can you get to the best answer. And that oftentimes is good enough.

Arda: Yeah, exactly. Actually, that's one of the principles that consultants follow as well, 80/20. That was a key principle when I was at Bain, because you can't boil the ocean, obviously. And, well, we need to come up with the right answers quickly.

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What NexStrat AI is and who it's for

Namaan: So before we dive into how you're looking to disrupt the consulting model, can you talk to us about NexStrat AI? Is it a platform? Are there services that are laid on top of the platform? Just what's the value proposition? Who is it for?

Arda: Yeah, sure. So it's an agentic AI platform. And in that platform, we have a systematic workflow which starts with problem definition. And then the AI agents are trained to use several different frameworks to structure the problem and rapidly generate hypotheses and then validate and iterate on those hypotheses to arrive at the final detailed answer very quickly using actual data, additional research. And then you can turn those strategies very quickly into detailed action plans, KPI dashboards. So we basically have a unified end-to-end solution for everything from strategy to execution following the consulting process.

So it's great for consultants. They will be very familiar with the process and will find that the AI agents are almost like colleagues speaking the same language. But it's also great for business users as well, especially like strategy teams, transformation teams, executives. Because for the most complex challenges, of course consultants remain valuable and we're not a replacement for consultants, but for day-to-day support, of course it's great to have that same systematic support available.

Namaan: So it sounds like this agentic platform is almost like having a junior analyst or two from MBB always at your fingertips, where you're able to get a lot of the research done, the synthesis done, and then you're given a strategy and you're given an action plan as well. Are you able to talk to me a little bit about the time savings? Like if I wanted to engage a traditional consulting team, maybe I could expect this kind of output in 8 to 12 to 20 weeks. How long does it take me to get a similar output from your platform and how similar is it really?

Arda: Yeah, so it's able to cut the process down to even minutes, of course, but of course depending on how much time you actually have, you can dig deeper, you can run deep dives, you can iterate on your strategies to make them even more robust. But I think it provides at least a 10x acceleration, both for consultants and business teams. One example I can provide is a team of users from a banking client. They started working on a strategic initiative, a marketing initiative, and they spent multiple months basically, you know, running some meetings, doing some research, but not really progressing into what the new marketing program should look like.

But with NexStrat, and we kept that initiative for our initial pilot, they could shape the strategy and also certain details about how to implement it within the first week. So that's quite a lot of time saving and it certainly helps to move faster in the right direction versus your competitors. But of course if the stakes are high and if there is a major investment involved, an irreversible decision involved, of course, you know, taking the time and collaborating with or working with external consultants still makes sense.

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Selling AI-generated insights internally

Namaan: For these kinds of partners that you have, clients that you have who are leveraging your platform, especially consulting teams or internal strategy teams, are you finding that they're having trouble selling the insights further down the chain because they're using an agentic AI platform, or are they really able to focus on the storytelling because the AI is doing the heavy lifting analysis? Talk to me about that because I think clients aren't just paying for speed, they're paying for confidence and trust as well, right? And so how do your partners manage that dynamic?

Arda: Yeah, it's a very good point. And to a certain extent, with the visual frameworks and with the systematic process the platform enables, compared to using just other AI agents, generic, you know, chat-based agents like ChatGPT or Claude, the business users, both consultants and also business users, can arrive at more, you know, confidently designed deliverables because those frameworks and the process enable AI agents to think more effectively, very similar to how they help consultants structure problems effectively and think through them. And also, they provide transparency — you can more easily oversee the process, like what drivers are involved, what's the rationale coming to this answer. And also, the user can correct very easily if AI is missing something or got something wrong. AI will take the feedback, implement it, and keep that in mind for future similar cases too.

And so, with that transparency and with that robust process underlying the whole exercise, then it's much more easy to defend those assets when presenting to a board, let's say. But of course, if you combine that with an actual consultant, so if a consultant is using NexStrat AI and also maybe collaborating with the clients, which, you know, the consultants might choose to also invite into the process to collaborate within the platform even, then, you know, that's the perfect combination.

Namaan: So it really augments the consultant's toolkit instead of replacing it?

Arda: Exactly.

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Has NexStrat commoditized consulting's secret sauce?

Namaan: So, I heard you say here that one of the things that sets the platform apart is that it is trained on proprietary consulting frameworks, or it knows how to think like a consultant. Do you think that those frameworks and that structured way of attacking problem solving is really the secret sauce of consulting firms, and do you feel like that's what you've commoditized?

Arda: Well, yeah, the secret sauce — certainly, you know, part of that secret sauce is the process. These firms use it regardless of the topic of the case, you know, the basic principles of consulting and how you use hypothesis-driven problem solving, you know, those famous principles like 80/20 or, you know, coming up with a MECE analysis, all those things, of course, help. And the instructions on how to use different frameworks, how to approach different types of business problems in various different industries, those are reflected in the prompts that we're developing. We're also providing AI with good examples, really good stress-tested outputs based on our judgment as former experienced consultants. And so all of them would, of course, not commoditize, but still empower consultants that might not have large teams to support them, like independent consultants or smaller firms, to deliver high-quality work leveraging specialized AI like NexStrat in a competitive time frame, with a competitive budget.

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Where traditional firms still have a structural advantage

Namaan: Where do you feel that the traditional firms still have a structural advantage? If you feel like they do at all, right? You've been on both sides of the table. I think you're a unicorn. You can speak very credibly about what it's like to be a challenger in the space and what it's like to be an incumbent. And where do you think the incumbents still have that structural advantage compared to maybe platforms like yours?

Arda: Yeah, so obviously the large firms, they have strong brands and reputational capital in terms of providing that trust factor, the large network of experts and the depth of experience since they've been around for many years. They're all of course very important and that's why we're not claiming that NexStrat is a replacement for working with MBB. So we're kind of expanding the market — we're making this capability and this way of structured thinking more available because, you know, consultants can only support the most complex problems and, you know, this can be an ongoing capability for businesses powered by AI, and also, you know, a turbo boost for independents and smaller firms who might not have very large teams to support them. But yeah, of course, you know, the MBB and other large firms would continue to have certain advantages for sure.

Namaan: I'm sure there are advantages around just risk mitigation as well. You know, there are certain processes they have in place, right? It's someone to blame if things go wrong, right? There are advantages to hiring a McKinsey or a Bain versus maybe leveraging an agentic model that you own from beginning to end.

Arda: That's right. I mean, accountability obviously stays with humans. Of course, both situations demand strong brands by your side. That's what the client is looking for, of course.

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How agentic platforms are reshaping the consulting pyramid

Namaan: So Arda, I want to ask you, how do you think that this kind of agentic platform, whether firms work with you or whether they build their own, is going to change the consulting model moving forward? I know traditionally firms have been organized in this pyramidal way and I'll ask you to explain that if you don't mind, but do you think that this pyramid model is going to shift as a result of these agentic platforms emerging?

Arda: Yeah, of course, of course. So first, to start by explaining what the pyramid model means — consulting firms are mostly organized very similar to military organizations, basically. So at the bottom of the pyramid, you would have junior level resources like analysts, and then on top, you would find consultants, and as you move up the ladder, you would see a shrinking number of members, and at the top, obviously, there are partners.

And the reason for this type of shape and organization was that in terms of man hours, consulting demanded a lot of ground work like analysis, you know, research, building, you know, decks, generating slides. All of that takes a lot of time and a lot of resources, of course, and that called for junior level resources. So that's why, you know, you'd organize like a pyramid.

And with AI now taking over those types of tasks, and consulting regardless of level becoming more about putting judgment and finding out the high value insights, even if you're a, you know, junior consultant, right — then it's becoming more like a straight, maybe rectangular shape, shifting slowly. And we actually see that on the news, materializing already directly with the firms announcing cuts in new hires by 10% or even up to 30%. We see that becoming a reality.

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What the flattening pyramid means for consulting in 2036

Namaan: What do you think the implications are for the industry longer term? So what I hear you saying is the bottom's getting thinner, the middle's getting fatter, because what matters more now is human judgment, business acumen, client management ability, storytelling ability, etc. What do you think that means for what consulting is going to look like in 2036? Are we going to have enough junior consultants to take over those mid-level and senior-level roles? I have a thesis, but I'd love to hear your perspective first.

Arda: Yeah, it's very interesting to see — it will be very interesting to see how the industry will evolve, because it used to be based on an apprenticeship model largely, and many of the partners typically got promoted after many years at the firms. And based on the pyramid disappearing, how are those firms going to raise the next generation of partners is of course a question.

But you know, that pyramid shape also meant a strong up-or-out policy, right? Because in order to sustain the pyramid shape you have to adopt such a policy. And, you know, because the consultants are all ambitious and driven, of course, you know, they would like to rise up the pyramid. So, but now maybe that will be a more sustainable model, maybe with fewer hires, who knows? I mean, there can be less of that up-or-out dynamic and those new hires, they are indeed capable of providing high value insights and demonstrating, you know, maybe that would be a little bit of a stretch, but future partner-level thinking potential and problem solving abilities, and might just, you know, make it to partner with this next generation of partners.

But what's nice is, of course, that there will probably be fewer junior level hires at large firms, but there are more opportunities for whoever would like to step into consulting to do this on their own, basically leveraging AI platforms like NexStrat, or what I'm expecting to see is also an increasing number of boutiques that are being launched. So they can go and join those types of firms. So I'm not sure if the industry as a whole would shrink, but probably the large firms would shrink at the base.

And it's also good in a sense to transfer all those boring and mundane tasks to AI, because consulting especially during the junior years is not always very much fun, right? I mean, it's a very difficult profession and those years are tough, but now it can be more fun. And those high-level judgment and problem solving things — those are the types of things that attract young professionals to this profession anyway. So maybe it's good overall for the industry.

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The case for joining MBB anyway

Namaan: What I'm seeing is the market is continuing to grow. So you're seeing demand for consulting services grow on a year-over-year basis. The more uncertainty there is in the world, the more consultants are in demand. So I'm bullish on the future of the industry, and I am also seeing increased fragmentation. And that increased competition puts downward pressure on prices. And so, you know, what I'm seeing across a lot of the firms is eroding pricing power that's leading to decreasing margins. And so, you know, that's good for the consumer of consulting services, but the partners of these firms are going to want to protect their margins, protect their payday. And so one of the things that I've been wrestling with lately is just, are we going to see a productization of consulting? And I think you're at the forefront of this, right? You have taken the intellectual property, you have taken the approach, you have taken the frameworks and packaged them in a product that reminds me of a SaaS platform. Do you think that the larger firms are going to try and introduce this productization to increase the stickiness of their client relationships and really introduce a new revenue stream? Do you think that's a viable future for some of these firms?

Arda: Yeah, by the way, there's also a SaaS product component to NexStrat. And this trend — I mean, diversifying offerings from pure consulting into SaaS-based products is actually a reality. I also remember certain famous products being launched by Bain and other firms I worked at. And of course, you know, that's going to be probably taking increasing share as a revenue stream going forward. But, you know, offering the core consulting service and, you know, the core value proposition through a client-facing AI platform directly, if that happens, that won't be happening very quickly. That will be a bit too disruptive to rush into for most of the large firms. That's what we expect to see going forward. Eventually, maybe some focused SaaS solutions focused on certain types of problems or domains would of course emerge. There are already those types of services being launched. But we don't expect to see that very soon.

Namaan: To me, the core value proposition of consulting is you have expert advisors who can really dig into your problem in a tailored way. And I think if the human element is removed too much, then the value proposition of consulting goes away, right? And so I certainly would see that productization as an auxiliary revenue stream, not as the main kind of offering that these firms are taking to market.

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What candidates should actually do differently now

Namaan: I wanted to ask you, Arda, about the implications for candidates. We have a lot of folks who listen to the podcast who want to break into consulting. Either they want to go work at McKinsey, Bain, BCG, Deloitte, or they want to do their own independent consulting. And so we've talked about some of the implications for junior talent and how the model is evolving in the market.

My own personal take is that I think what you're going to see more of instead of hiring cuts, I think what you're going to see is headcount growth not keep pace with revenue growth. So what I mean by that is like 10 years ago, if these firms were growing at the clip that they're growing at now, they would have to hire so much more headcount to service that growth. Now, you can keep your hiring consistent from year to year, but continue to service that growth. So in effect, it's a cut, but it doesn't actually look like a cut. And so, like, the competition's getting fiercer for the same number of spots year to year.

And the work is getting different as well. And so let's just assume for the purposes of this conversation that, you know, AI is eroding parts of the traditional model. Why do you think a top candidate should still join Bain, McKinsey, or BCG? Like, you were at MBB, I'm sure you had a great experience. But like, what are they getting in those environments today that they would not be able to replicate independently with the right tools?

Arda: Yeah. So I still believe that, you know, the opportunity to join a reputable consulting firm is worth pursuing. And, you know, especially during the junior years, spending, you know, the first part of their careers would really, you know, equip them with the right experiences and tools, which, you know, they can leverage even if they transition out of consulting and go on to do something else.

And no AI agent can really replicate those actual experiences you would go through in those consulting firms. Because, for instance, most of those firms have active mentorship programs, actually expect you to be proactive about your professional development and engage continuously with all the other senior folks within the firm to get feedback. Every client situation is unique and you go through many challenges. You will need to figure out solutions on your own, but also, you know, see others dealing with tricky situations. You observe the partners. Those are really the not-so-obvious things you learn while you're on the job doing it together with the other more experienced members of the firm. So I think, you know, AI won't be a replacement for that.

But of course, combining that with AI and transferring the analytical problem solving with the increasingly capable AI tools, that would be again the ideal combination. Those firms are also utilizing more and more internal AI tools and agents to complement the work of their consultants. So I think they will coexist together.

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What to focus on before your first day at Bain

Namaan: So let's make it tactical if you don't mind. We have a lot of people listening to this podcast who are starting consulting roles in the next 6 months. And you were at Bain, I'm sure you were a mentor, right? You were a senior manager. Like if someone comes to you and says, I am starting at Bain in 3 months, like what do I do to prepare? I'm sure your answer would be different now than it would have been 5 years ago. So what should that person be doubling down on and what should that person be ignoring as they prepare for their first consulting role?

Arda: Yeah, so, you know, most of the core consultant toolkit — the way of approaching problems, structuring, you know, communication principles — those will continue to be very important. So I think they should still be focused on getting them right in their first year or so, maybe in the following years as well. But, you know, for instance, learning about, you know, advanced Excel formulas or, you know, PowerPoint tricks, probably those aren't that relevant nowadays versus 5 years ago because, you know, AI can increasingly handle that and consultants won't need to worry about that.

So even from day one, I would encourage them to think very actively as if they are the partner leading the case about what the solution to the client problem is. And we actually had a name for that at Bain — we called it "answer first." So we tried to maintain that, of course iterate on it and shape it throughout the case, but we always tried to have an answer. And so they should practice it and they should try to figure out what's the most important insight.

Which the AI agents can provide meaning of course, and, you know, of course do not rely on AI agents too much because they should be the trusted advisor in the room at the end of the day. And as human consultants they will be asked by the managers, the partners, and the clients to defend their work. And there's a very high risk of losing reputation if something goes wrong when utilizing AI agents — if it hallucinates and you don't recognize it and you don't check the output of the agents and it gets presented to the clients. Of course, it's a very significant risk, so they should be very careful about that.

Those would be, I guess, things to focus on. And of course, a significant part of consulting services nowadays are about implementing AI for the clients. So, in terms of capability development, maybe, you know, if they're interested in AI implementation or AI strategy, they might seek opportunities to be tackling such cases and also, you know, try to gain hands-on experience with AI development, building AI use cases.

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Building judgment when AI is doing the reps

Namaan: Amazing. And so I heard you say something interesting, right? Because a lot of people will just say "learn AI," right? And what you're saying is actually get your hands dirty, start to build, to develop and test and iterate on some use cases yourself so that you have some of that personal background and experience when you walk into an engagement. And you can just — you're not just repackaging insights that you've learned from elsewhere, but you're also able to bring your own personal perspective to the table. Accurate?

Arda: Yeah, I think. Yep.

Namaan: On top of that, I heard you mention judgment a couple of times. You know, maybe an AI agent gives you 12 insights, but you're the one who has to determine what the key insight is, because you have to be able to understand the client's business model, the business problem, where they sit inside of the organization, what the internal political pressure is that they're facing, what the most important thing is to solve for first. How does a young professional start to build that judgment? I think one of the concerns that folks have is that AI's starting to take away some of those learn-by-doing reps. And so how else can someone start to build that capability, you know, if they're just not getting as many opportunities to do it?

Arda: So I think, you know, as we go through these shifts of, you know, AI taking over the traditional tasks from the junior level consultants, you know, the junior level consultants would be increasingly expected to actually build up those skills and practice those skills. I think, you know, they would be, you know, put in front of clients. They will be expected to lead the discussion. They will be expected to participate in a problem solving session with unique insights more and more, because otherwise there's not much contribution coming from their side as the AI agents will be doing most of the mundane work.

So I think the industry will be pushing them to practice those things more and more. And actually collaborating with AI agents and utilizing platforms like NexStrat AI to work on any type of business problem — maybe not an exact real client case, but some idea that they might have. They might think of a new idea, a business idea, or see an issue with a process of a company whose product they're using. They might just, you know, cooperate with the AI agents on the platform, see how they use the consulting process, how they approach different problems using different frameworks. And I think, you know, the platform would be very valuable for young professionals that are already inside consulting or looking to get into consulting. So, yeah, the answer might again be working with AI agents to achieve that, actually.

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3 key takeaways

Namaan: So, my key takeaways from this part of the conversation. Please just correct me if you think there are different ones, or add your own. But I think number one is that, look, agentic models are shifting the consulting talent model. So we're going away from a pyramid more towards maybe a flat rectangle, as you mentioned. That changes the nature of junior work and it also changes the hiring calculus for firms. I think that's kind of takeaway number one from this part of the conversation.

Takeaway number two is that when the pyramid flattens, it changes the way that partner economics work. And so the pyramid model is really a leverage model. And so there's a chance that we're going to start to see different types of innovations around revenue generation at consulting firms to drive partner economics in a different way. That's key takeaway number two.

And for me, key takeaway number three — it's just that this changes the way that people who want to go into traditional consulting should prepare for the role, the skills that they should build, and the ways that they should expect to be evaluated in the interview process. Is there anything you'd add to that?

Arda: Mm-hmm, mm-hmm, mm-hmm. Well, I think that's a very good summary of the key takeaways. Yeah, I think we summed it up really well. The client engagement and the interactions with the actual clients, employees, and leadership team — the earlier, the better would be a great part of the onboarding journey for young consultants, I guess, which they should keep in mind. Implementation and execution, PMO-related work will be also more and more demanded, I guess, together with expectations to be based on results and not hours. So any opportunity to work on those types of cases would be valuable for the future as well.

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Why PMO work is rising in importance

Namaan: Can you unpack the PMO work for me for a minute? Because I've often and always thought that the best consultants are the best project managers. And so can you talk to me about just how that skill translates and just why the importance of PMO work is rising in today's consulting environment?

Arda: Yeah, sure. Sure. So, you know, the implementation and execution and, you know, the real value creation is becoming more and more important for the clients. And they would like to see it bundled with the strategy work if not, you know, a standalone service. So therefore, I think it's going to be a great experience for the new joiners to those firms to be placed in such cases, to not only get experience in a growing service area, but also to better understand how things work in real life. Because when it comes to execution, many things go against what was originally planned. There are many constraints which you or the client team might not have noticed. It requires getting buy-in from many humans, many decision-makers, many, you know, different client organizations that need to be executing the work, whether, you know, in the field or, you know, facing the customer. So those take a lot of change management, leadership, effective communication. And PMO projects are basically great to experience all of those and develop your skills in those areas.

And also, many of the large scale projects are getting more complex. Typically, many international teams and resources would be involved. And there might be multiple functions which need to carry out different parts of the implementation program, which you need to get together in the room and agree on something. So all of them are even more complex versus probably 5 to 10 years ago.

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The defensibility of NexStrat AI

Namaan: Arda, we picked your brain as a consultant and we picked your brain as an AI expert. I do want to ask you a little bit about how you approach the job as CEO and founder. And I'd love to just talk to you about the future of NexStrat. And so my number one question honestly, as we've been talking and as I've kind of explored the platform a little bit, is just the defensibility of the platform, right? And we have Claude Code, we have Codex, we have like a million consultants who might like to be doing the same thing that you're doing. So why couldn't a large firm or another consultant just create a competitor and extract overnight? How do you think about your moat? How do you think about protecting the future of your business?

Arda: Yeah, sure. So very similar to traditional consulting where many firms coexist together, of course there will be other players that are launching their own AI-powered consulting applications or similar, but with a little bit different business models, that are aimed at consultants or maybe business users. But what we have at NexStrat is a combination of top-class decades of experience across many of the top firms including Bain, BCG, Strategy&, PwC, Arthur D. Little. So all of those reflect on the way we design the product, every little interaction and feature, hundreds of pages of prompts, the examples that are being fed into our agents. And we're also combining that with experiences we gained as executives, leading strategy functions, transformation programs, being aware of all the realities and typical challenges when it comes to doing strategy and transformation especially.

And we've been around for a while. We've had many users working on the platform on different types of business problems. And we've captured many learnings and we've iterated on the product to make it a really good experience for the users and iterated on our prompts and how the AI agents work. So I think it's quite a robust platform. As of now, it's going to be a great leverage for a consultant or a business user, especially in a strategy function.

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Growth strategy: B2B, B2C, and the marketplace vision

Namaan: How do you think about your future growth? You serve 2 segments. You serve B2B and B2C, right? The individual power user and the strategy function of a business. Do you have one primary focus segment where you really think a lot of your growth is going to come from? Do you treat them both equally? How do you think about that segmentation and the prioritization of your own growth plans?

Arda: Yeah, so actually what we have in mind is a multi-sided business model. So consultants, especially independent consultants, experts, and those in boutique firms, are a very high priority for us. And we would like to actually provide new opportunities for growth to our consultant users by connecting them with the enterprise NexStrat users, business users that might need human experts to validate AI's recommendations. Maybe they'd like an expert to get support on implementing in the real world the recommendations and plans from AI. So I think we have a synergistic business model and what we have in mind is to increasingly create these win-win opportunities for all sides. And yeah, NexStrat is turning 3 this year, and we would like to see both sides of the equation grow.

Namaan: That's interesting. So what I hear you saying is your individual consultant users have the chance to be discovered on the platform and potentially hired by your enterprise users. So you're building like a marketplace, not just a product. Is that what I'm hearing?

Arda: Yeah. Yeah, part of our vision. I mean, there isn't any marketplace in the traditional sense at the moment. But whenever there's an opportunity, we would like to connect an individual expert on NexStrat AI with a business user that is looking for that expertise. Whenever we think that might be adding value to connect both sides, why not? We see this as a community and that's the model of the future.

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How to try NexStrat AI

Namaan: For our listeners who are curious and would like to explore NexStrat, what's the best way for them to do that?

Arda: Yeah, so we actually recently launched a self-serve version. They can just visit our website, it's nextstrat.ai — without a T in the middle, sometimes it's misspelled. And they can just start a 14-day free trial. Actually, we would also like to offer a special coupon for the community. They can check out the description below with the MC50OFF code. They can get 50% off their first month following a 14-day free trial. And I think those who are preparing for case interviews would find that NexStrat will be a great support. They can try solving different types of case interview problems on the platform, get familiar with the process and the frameworks, as an interesting use case. It will be great for us to observe as well how that goes and reach out anytime if you'd like to ask a question or if you think you have a very good idea you'd like to share with us. Looking forward to hearing those, of course.

Namaan: I love that. So just to reiterate folks, 50% off your first month, the coupon code is in the description below this podcast. So go ahead and check it out. nextstrat.ai.

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Personal questions: AI in the kitchen and what Arda's reading

Namaan: Arda, I don't know if you've ever listened to Strategy Simplified before, but one of our traditions here is we always like to end interviews by asking a couple of personal questions. And so before we wrap up today, I just want to hear from you. What's a fun way you're using AI in your personal life that has nothing to do with consulting at all?

Arda: Well, yeah, I mean, I've been using AI recently for cooking. Probably many people are doing that nowadays, but, you know, recently I've been spending more time in the kitchen, partly because we're expecting a kid and I'm trying to help my wife in the kitchen. So I find that it's very helpful to just check ChatGPT or Claude, what I can cook based on what I have available in the fridge, rather than searching for a recipe or watching a video, because they can deal with problems in real time. If the meat gets overcooked, I'm just quickly asking what to do. And it also tries to come up with quick suggestions to save it for me, so I like it overall. And what I found interesting is it also seems to have a good understanding of taste. It's almost like it can figure out what would go well together and I'm not sure where it picked that up. It's got this notion of taste which we have as humans. But that way it's very surprising to me to be able to observe that in practice.

Namaan: I would agree. I've had good luck with ChatGPT recipes. What's the best dish that AI's helped you create?

Arda: Well, it suggested putting a cinnamon stick within rice and it ended up tasting great. So I never really thought of putting it in myself. So that was something nice that we managed to do together.

Namaan: We do that a lot in Pakistani cooking. So that's probably where it got it from.

Arda: Probably, yes. Is that maybe not that original?

Namaan: Arda, I always like to ask people too, what they're reading or listening to or watching. So is there a book you've been reading, another podcast you've been listening to, a movie that you watched recently that you really liked and you'd like to recommend to our audience?

Arda: Yeah, so I came across an article from Sequoia that says "services is the new software." And the article suggested that the new $1 trillion company would actually be a software firm operating as a services firm. So I found that, you know, the insights from that article are quite interesting as the compound effect kicks in. And it suggested that the human judgment in the professional services domains will remain important, and combining that with what AI can do, a specialized solution would be the next opportunity for founders as well. That resonated a lot with me, which I wanted to mention. Other than that, I'm trying to read some parenting books nowadays. I think, you know, there's some time for that, but not for most of the audience of this podcast. So no rush on that front.

Namaan: I love it. Well, Arda, congrats on the new addition. And thank you so much for joining us today on Strategy Simplified. Y'all, please go —

Arda: Thanks for inviting me.

Namaan: Yes, absolutely. Please go check out nextstrat.ai and use the coupon code in the description for 50% off your first month after a 14-day free trial. Arda, thanks again for joining us today.

Arda: Thank you very much.