AI founders flocked to Inside's Meet Our Fund 5 event in October 2023 to hear from today's top VC's investing in AI. Our team spoke with VC's behind the scenes to ask them what advice they'd give to AI entrepreneurs pitching to VCs. Here's what they shared:
Lucas Swisher, Coatue
I think what we're most excited about right now are people that are tackling new workflows or new problems. If you've looked at the last generation of companies that have come up in the mobile era and the cloud computing era, a lot of the biggest businesses were built around new workflows and people solving really new challenges.
I think it's really tempting to go after existing workflows and existing ideas, but what we're most excited about are those explosive new ideas that we know that you all are building.
Emerson Kirk, Gradient Ventures
I'd say really focus on the go to market. At the end of the day, AI is a technology that enables and unlocks a lot of new opportunities, but you still have to get it in front of customers. You still have to get people to buy it.
Every product that's ever existed over history, you eventually have to get people to want to use it, and you have to reach them. So, if you can really focus on go to market, and talk about how you're going to win in go to market, that, to me, is what gets me really excited, and I think a lot of other investors think about that, too.
Jessica Kaing TechStars
My biggest piece of advice is to be authentic. I think that part of the reason why we love seeing different teams and value teams is because when we see authenticity and we know who you are and we feel like we can connect with you.
We'll want to get to know the rest. We'll want to know what you're working on, and also know what you've accomplished as well. But to start it off comes with authenticity, and if we can connect with you or not
Eric Zhu & Christian Elam, Bachmanity Capital
Christian: Don’t follow a hype cycle like we had with Web3. Entreprenuers should really make sure that their product and their company is solving a real world problem and not super focusing on like AI, we're an AI company, we're AI product, but like making it around like the actual problem, the product and like how we use AI naturally.
Eric: I feel like instead of focusing on fundraising, just focusing on hardcore metrics, right? Revenue growth, etc. With an AI company, it's gonna be a lot easier to launch, because you already have the pre existing infrastructure. If you're building an AI company unless you're building a foundation model, which is a lot of theoretical stuff, right?
So if you're building something that's like, oh, you know, building a chatbot, or building something that is built on top of and, yeah, wrapper, right? Definitely focus on more of the metrics like growth and revenue versus the amount of money you raise. Yeah. And, you know, focus on building sustainable companies, right?
Don't build in hype. And focus on revenue, and doesn't really matter how much you raise, just like Yeah, yeah. Yeah, well, like, part of the business is to, Like, have traction. Yeah. Traction's more impressive than raising. Yeah, like, part of the business is just to hit as much you know, make as much money as you can.
Right. You know, Make as much of an impact, right? Not focus on like how much money you make, so. And also, a brownie points if you show up in the high school bathroom to pitch. That always works. Make yourself unique. Stand out.
Bola Adegbulu, AI Fund
Really focus on the business value of what you're trying to do with AI. I think that's really the main thing. Start with the business value and then work backwards to the AI. Versus going from the AI and trying to find the business value.
Molly Welch, Radical VC
So I think for AI entrepreneurs pitching VCs a couple of piece of advice I offer. The first is perhaps obvious, but still very important. And that is to come prepared. So of course that means a pitch deck but that also means some thought that thought kind of put in advance into things like market size.
competitive landscape, incredibly important, especially for application layer AI, but in AI generally, where there's such a boom in startups. And anticipate some of the questions that venture folks are going to ask you and have good answers to them. On the preparation point, ensure you are ready to pitch.
So, deck, of course but if someone offers you a term sheet the following day, are you actually ready to take it? So, come prepared and make sure you're, you're come ready, you come ready to pitch.
Jason McBride, M12
Make sure that the value proposition is clear when you're pitching to VCs, especially as it pertains to generative AI. And look for that differentiator, right? So when you're really trying to focus on generative AI, find a differentiator that's much more than just a wrapper.
So what you probably heard in the industry right now is that there's a distinction between The products that are really leveraging true generative AI, and those are just wrapping around it. Try to make sure that you're building something that is sustainable, that is differentiated, and that can really stand apart from the product.
So make sure that it's more than a wrapper. It's a solution that drives value and drives product market fit.
Noah Yago, Cisco
Think not just about today's problems, but tomorrow's problems. A lot of immediate problems that we can solve, that we could build a great business. But the truly amazing, groundbreaking businesses that are going to change the future of the industry are focused on what's happening and the problems that are being created three years ahead.
Ali Tamaseb, DCVC
I think the main thing is just working on your company, the traction and the numbers of the company, the deep understanding of the space and the problem space that you're in is very important than the deck or how you pitch, work on the company, make the company better, have deep understanding of the problem space and the company and the industry that you're going after, and VCs will be chasing you.
Vivan Cheng, CRV
Make sure that you're able to authentically convey why there is Founder problem fit, meaning why are you sort of the best person in the world to be working on this problem? And last thing is just making sure that the problem space you're working in is a venture scale problem one common mistake I make is there are a lot of great ideas Not all of them should be venture scale.
And so thinking those through through those two things will really help make the pitch successful.
Abie Cohen, Centre Street
AI entrepreneurs these days have to be really proficient with what sets their product or service apart from a technical perspective. So, as much as you can speak to the expertise that you have with why your AI product is technically proficient, please represent that to investors.
I think that's going to be very important. They want to see proprietary info, they want to see defensibility, and investors want to see differentiation relative to some of the competition sprouting in the AI field.
Kanu Gulati, Khosla Ventures
I think Khosla Ventures specifically focuses on two key things when we're considering an investment.
One is, how big can this opportunity be? If everything goes well is there a path to getting a really impactful, large billion in revenue opportunity? That's number one. How big, if everything works well, how exciting and big can it be? And then, equally important for us is to understand how should we think about the risk retirement order, given the category, given the space, given the state of the company.
By which I mean, which risks have already been retired, what are we focused on retiring in the next one to two years with this current phase, and in the future, what do we need to believe towards that vision? And we think if I rely on both of those things, the big pot of gold that can be had, and the risk of time and order we can be good partners.
Sheel Mohnot, Better Tomorrow Ventures
Make sure that the solution you're selling is really like, really needs AI and will solve a problem better using AI. I think a lot of folks think that simply adding AI onto something will help solve a distribution problem when that isn't really the case.
And probably the company that already has distribution is going to win. So I think it's better if you are selling an AI solution to somebody that might already have distribution, rather than thinking your solution is going to solve everything
Andrea Wang, General Catalyst
I think always be problem centric, not solution centric. I think we want to see that you're driven by a first hand experience with the problem, a lot of research and customer discovery and that you are actually having great conviction behind the problem.
And we care less about, especially in the early precedency stages, you knowing exactly what the solution might entail.
Clayton Bryan, 500 Global
I think what we're seeing is we're seeing a lot of really gifted builders. And I, I like to use the analogy, a lot of hammers looking for nails. And so I think right now you want to really understand the psychology of your end users. Who's willing to pay for this? And you have to display that you have that such a strong understanding of what they need and be able to articulate that very clearly and then start to build prototypes that are showing that you're able to get the buy in from those folks that you want because there's a lot of projects out there right now. And so you're going to really have to stand out by one showing strong customer understanding of the psychology of your customers and then being able to ship something quickly. So that, you know, as an investor, I can, I can evaluate whether or not that's a staying power.
Key takeaways, organized by category:
1. Focus:
- Focus on new problems: Address fresh challenges instead of existing ones. (Lucas Swisher, Coatue)
- Future-oriented: Consider emerging problems and long-term impact. (Noah Yago, Cisco)
- Go-to-market strategy: Show a clear plan for acquiring customers. (Emerson Kirk, Gradient Ventures)
- Authenticity: Be genuine and emphasize your strengths. (Jessica Kaing, TechStars)
- Differentiation: Stand out with a unique and sustainable solution. (Jason McBride, M12 & Abie Cohen, Centre Street)
2. Company readiness:
- Preparation: Be ready to pitch and accept potential term sheets. (Molly Welch, Radical VC)
- Metrics and traction: Focus on growth and revenue, not just fundraising. (Eric Zhu & Christian Elam, Bachmanity Capital)
- Founding team fit: Demonstrate your expertise and passion for the problem. (Vivan Cheng, CRV)
3. Market and opportunity:
- Scalability: Aim for large-scale impact and billion-dollar revenue potential. (Kanu Gulati, Khosla Ventures)
- Problem validation: Ensure that your use of AI is the best solution and solves a critical problem. (Sheel Mohnot, Better Tomorrow Ventures)
- Customer understanding: Clearly define your target audience and their needs. (Clayton Bryan, 500 Global)
