“At Remarkable Ventures Climate, we’re backing companies driving transition and helping people adapt to the new climate reality,” says Murat Aktihanoglu, sharing his insights in an exclusive interview with The American Bazaar. The seasoned investor and entrepreneur, best known for co-founding Remarkable Ventures and its climate-focused fund, has backed over 375 startups with a combined valuation exceeding $10 billion.
In this conversation, Aktihanoglu discusses the hype surrounding artificial intelligence and climate tech, offering his perspective on what truly defines a startup’s potential in today’s shifting landscape. He also sheds light on the rise of New York City as a global startup hub, the ERA accelerator’s philosophy, and why climate has become central to modern investing.
From his early days building location-based platforms to fostering New York’s entrepreneurial ecosystem through the Entrepreneurs Roundtable, his journey underscores one core belief: good founders matter more than good trends.
This is the second installment of the interview, edited for clarity. You can read the first part here: How Murat Aktihanoglu turns 15,000 startup applications into 15 investments
Kesav Dama: ERA has helped more than 375 startups raise over $1.7 billion. What’s been the biggest surprise or disappointment?
Murat Aktihanoglu: So, either way the surprises are the unicorns. We invested in our unicorns as the first investor, in the pre-seed stage when the company had nothing: just people and an idea. They built a great company and sold it for a lot of money. So, it’s fantastic to see that when it happens because we make many other investments and they may fail. Many of our investments fail because we are pre-seed investors. And I don’t want to promote it, but our fund returns have been so high, much higher than the market returns. So, we’ve been very lucky. And many startups fail for so many different reasons.
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The one thing we get disappointed a lot is when the founders give up very quickly. We thought they would try harder and they are passionate about space but sometimes something happens and they quit very quickly. And that’s the most disappointing thing to me.
What are the top two or three mistakes founders make in fundraising?
The most obvious mistake is when they have done nothing yet. They come to an investor and say, “If you give me a million dollars, I will build this company.” Nobody will give you money if you haven’t done anything. We see that often. They say, “I’m going to quit my job when I raise a million dollars.” It’s not going to happen.
The second is valuation — not having common sense and thinking, “I don’t want to be diluted.” They’ve watched “The Social Network” and worry about being diluted like one of the co-founders in the movie.
But the main mistake is looking like you are not so excited about your company. You’re pitching and you look bored, like you don’t want to be there. Those are three easy mistakes.
What is the right amount of money to raise?
You need to talk to someone who’s done this before. If you try to raise too little for your company, nobody will give you that money because it won’t get you to your next milestone. The money you raise should get you to the next milestone, and you should have a basic plan on how to use it, not exact spending details, but just common sense.
Revenue projections [that] investors ask for aren’t about accuracy. It’s to see how the founder thinks. Are they thinking about salespeople, salaries, and the market the right way? It’s a test. When they ask for five-year projections, they know no one can predict that. They just want to know if the founder understands the space and can execute.
Out of, say your last cohort or last few cohorts, what percentage of the companies were characterized like a SaaS company, consumer company… can you break it down?
We invested in many consumer product companies in the past. Around four years ago, we started investing mostly in B2B. We think there’s a bigger opportunity in the B2B space for our LPs. We no longer invest in consumer products, but we did invest in amazing consumer product companies that are doing great—skin care products, sunscreen for men, and others. These days, we’re focusing more on AI across everything—healthcare, climate, enterprise, SaaS. AI is now a tool applied to every vertical, so we’re focusing more on B2B companies.
Anything you see different from a New York accelerator versus a San Francisco accelerator or say from another location?
Around 10 years ago in New York City, you had to have revenue and real product traction to raise money. But right now, New York is the second-largest startup ecosystem in the world after Silicon Valley, so the amount of funding available in New York is getting closer to Silicon Valley levels. And, in many quarters, New York City is larger in venture capital volume than San Francisco. Depending on what you’re building, if you want to raise large amounts of capital without initial traction based on vision alone, Silicon Valley is your place. In New York, we need to see real business models, traction, products, and prototypes. New York City investors are more practical than visionary.
Does New York City have an advantage because you have so many corporations headquartered around here?
That’s the biggest selling point. If you’re a B2B company, New York City has the largest percentage of Fortune 500 companies in the world.
When your startups are trying to sell B2B products, do you advise them to target big corporations or smaller clients?
Depends on the business. Some of our companies sell to large corporations. They have auditing software for accounting firms, so they have to sell to large companies. Some sell to smaller customers.
We respect everybody and our pattern recognition is different. Like some products need to be sold to large corporations and some to smaller ones, some to medium ones. And then it’s really depending on the business. But we do the analysis very carefully. Go-to-market is very important. You have to pick the right ideal customer profile.
When you select companies for your accelerator, how important is their go-to-market strategy?
About 99%. We ask them about their go-to-market strategy, because we want them to think about it and present to us. But as they go along, when they do customer discovery and market discovery, they usually change what they do completely from their learning. Today I had a board meeting with one of our companies and then they are learning a lot and now they’re changing their go-to-market from like very large e-commerce businesses to smaller e-commerce businesses because that’s how they are seeing the market reaction. So, we want our founders to know everything, prepare for everything and think about everything. We invest in them but we want them to also really use their expertise to make the right decisions and we work with them very closely. They tell us what they’re doing, we tell them our opinions and they make their own decisions.
What would your advice be to a founder?
We ask our founders: what problem are you solving? Customers are the most important people to listen to. Our founders ask their potential customers: what are the problems you are having? They discover the problem first, then come up with a solution. They ask the customer: would this be the right solution? You cannot sit in a room alone and decide. You have to talk to customers. Customer discovery is very important. If you’re too early, do customer discovery without guiding the customers. If you’re later stage, you have to point them in your direction, see their reaction, and try to get a price point. We have many guidelines on pricing. We help our companies with that. There are frameworks where you ask the customer: how much would you pay to solve this problem? How much is too little? How much is too much? We create pricing ranges for a potential solution using the Van Westendorp pricing model. You need to build something your target customer would use and pay for.
Is there any time when the customer is wrong?
When you’re building a solution for an enterprise, you need to listen to them. But yes, sometimes you have to be more visionary for your customer who doesn’t know what they need or what they should use.
Where do you see AI going? Is it going to transform the economy or lead to mass unemployment?
This is the question everyone’s trying to answer. I think AI is just like cloud computing, mobile phones, or typewriters. When typewriters came out, people said calligraphers would lose their jobs, and that it would be miserable. But people moved on to use these tools.
As a computer science person, I believe those who can use AI tools in the best way will advance to better jobs and do better in life. People not using AI tools will be left behind. Just like the printing press, typewriters, or computers like when they came out, people moved on to new roles created by the opportunity.
That’s why we invest in a lot of AI companies. These days, full-stack AI companies are very exciting—companies with no humans, only AI agents doing all the work. People will adjust accordingly. I don’t see 80% of people losing their jobs and starving. Some founders and investors are exaggerating to gain an advantage, raise money or to impress others.
Artificial general intelligence is not even close. Two months ago, Apple released a report where they tested existing LLMs for reasoning. There are now reasoning models, and when a model isn’t trained on a domain, it scores 0% on reasoning, according to the Apple report. If you ask the LLM: what’s the best way to mine on Mars? They scored zero. So, AGI is way far away. And people who are raising a lot of money claim AGI will be achieved soon to achieve their goals. AGI will not come from generative AI only because that is just statistical pattern matching from training data. It’s going to come through other ways. And the IBM CEO agrees with me. But this is not a popular opinion.
Do you agree with the view that there’s going to be a huge AI bust?
I agree. There are some companies in the AI application world doing prompt engineering, prompting ChatGPT, Claude, or Gemini in a way that gives you the right answer. We don’t invest in those companies obviously but the AI hype is actually being used to raise money when the company has actually no AI layer on their own. They are using an existing API which anyone can use.
You’ve been the co-author of “Location Aware Applications.” How do you break down complex tech into frameworks?
I wrote that book because my last company was about location-based services. This was 2009, and at the time there were no GPS chips in mobile phones. The first GPS chip in a phone was the iPhone 4S in 2011. We were pinging cell towers around the user and triangulating to find where they are. Our accuracy was around 20 meters, which was pretty good for that time. Technology is a tool. We were trying to tell people what’s around them: who they know nearby, what services are nearby. We were the first location-based ad network; we worked with Nokia. We took a simple idea, triangulating cell tower locations to find the location of a person more accurately than other services, and then use it to provide them value.
Do you see any emerging tech that’s as transformative as GPS once was?
Apple is about to give access to the GPU on the iPhone to any application. You don’t need to go to the cloud. You can run a small LLM on the iPhone itself. This is the future. You’ll be able to generate text, audio, video content, images locally on your machine.
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As I mentioned, we have a climate fund now, and now we are looking at very specialized hardware chip companies doing interesting things. Nvidia is a $4 trillion company, and they are doing great. They invented the GPU model almost 20 years ago and built a full software stack, CUDA, around their parallel processing GPU units.
We are now seeing chips that process voice, and do AI inference on a chip locally without going to the Internet. They can transcribe conversations into text locally without any Internet connection. Specialized chips for different AI use cases will be commonplace. Video used to be encoded on CPUs and eventually now there are chips, they do video encoding. So, I think as we get more specialized use cases for AI, there are going to be chips doing very specific tasks and it’s going to be a very interesting thing to watch what people build with that.
Do you worry about the digital divide?
Of course, I’m from Turkey. I grew up with not many resources, but digital divide already exists today without AI. Like people without Internet access. Many households in poor areas of the U.S. don’t have access to the Internet, which is a huge disadvantage and a major problem.
If you had to go back and give advice to young Murat, what would you say?
I got lucky in my life multiple times. That’s why I’m sitting in New York City at an office as a co-founder of multiple VC funds. My advice to young people is “Work as hard as you can, put yourself in a position to get lucky, be nice to everyone and then luck will kick in and you’ll be successful.”