On Thursday, March 28, 2024, Ravix Group had the pleasure of hosting “Women in AI: How to Fundraise and Scale in 2024.” The panel featured Courtney Chew of SSM Legal as the moderator, and panelists included Danielle D’Agostaro of WVV Capital, Abby A. of SNØCAP, Melissa Widner of Lighter Capital, and Ashley Pantuliano of OpenAI.
Sponsors included: Lindsey Mignano of SSM, Jacquelynne Suguitan and Kate Kozak of TriNet.
Some highlights:
- 🚀 AI Investment Landscape: The discussion acknowledged a significant increase in VC funding towards AI, particularly generative AI. It’s becoming more challenging for non-AI startups to raise funds due to this trend.
- 🗣 Importance of Storytelling: There was an emphasis on the ability of startups to tell compelling stories. It’s crucial for startups, especially in AI, to narrate their value proposition and anticipated market position compellingly.
- 💸 Investment Focus: Currently, investment seems to be heavily focused on the model layer of AI startups, but there’s anticipation for more investment in the application layer.
- 📈 Startups and Revenue: Founders need to demonstrate traction or demand for their product. Even if it’s not paid initially, showing revenue potential is vital.
- 📚 Diligence and Data: Due diligence becomes critical when raising subsequent funding rounds, with legal aspects like IP ownership and data usage being scrutinized.
- ⚖️ Legal Risks: The legal risks associated with AI, such as IP, data privacy, safety, and misuse for disinformation, were discussed, highlighting the importance of early legal engagement for startups.
- 🌱 Sustainable Growth: In the current funding climate, startups must focus on creating sustainable growth and be conservative in their scaling plans.
- 👥 Team Importance: The importance of having the right team, especially in the early stages, was stressed. A strong team can often be the deciding factor for investors.
- 🤖 AI’s Impact on Labor: There was a prediction that AI would not replace jobs entirely but rather create more specialized roles requiring longer training or education.
- 🌈 Diversity and Inclusion: The event also highlighted the importance of diversity and inclusivity, addressing biases and the unique challenges faced by women in the industry.
- 👩👧 Motherhood and Career: The discussion touched on women’s challenges in the workforce, especially after becoming mothers, and the lack of established maternity policies in some VC firms.
- 🔝 Changing Dynamics for Women in Tech: There’s progress being made with more women taking on significant roles in tech and VC, but the distribution of venture dollars to women-led companies is still not proportional.
You can access a video recording of the panel here.
Transcription of the Panel
Bree Hanson 01:56
I’m Bree with Ravix Group. We are one of the sponsors. Today we are an outsourced accounting and CFO firm for startups anywhere from preseed all the way up to seed stage. We’re here to celebrate, Women’s History Month, women’s history month but also international history which I also learned in Russia which we have a Russian here today. The men write poems and bring flowers to women at the office. We haven’t yet during Women’s International month they do this so Mark where’s my poem? Thank you. It was also started in Murrin which is another amazing thing. So we are here to celebrate today and I pass on to try net or other sponsor.
Jacquelynne Sugitan 02:55
I’m Jackie & This is Kate from trinet.
Kate Kozak 03:01
Hey, everybody, thanks for being here. I’m Kate with TriNet. For those of you guys that aren’t aware TriNet is a PEO a professional employers organization. We work with VC backed companies to help them scale efficiently. Typically from pre seed to Series B stage where that an inflection point where they’re looking to have that next amazing candidate to their team. We have a single sign on technology platform that encompasses hire to retire. So everything from applicant tracking all the way through to the 401 K piece including fortune 100 caliber benefits, but we were thrilled to have you guys here today and thanks to our amazing speakers. And then, lo and behold we have SSM who is leading the panel.
Courtney Chew 03:43
Good afternoon, everyone. It’s such an honor and privilege to be here to welcome you to our panel discussion today. My name is Courtney Chew. I’m a counsel at system law of WeBank certified full service law firm serving early stage founders and tech companies. My practice primarily focuses on providing legal services to early stage startups, tech companies and small business founders, primarily within commercial contracts technology transaction, a little bit of data protection and privacy, some information and venture financing and a bunch of other general corporate work. And if you didn’t know SSM law, it provides a comprehensive suite of legal services, including the practice areas that I’ve mentioned, we also have expertise in corporate law, intellectual property in house litigation management, patent law, also data protection and cybersecurity and so much more. We’re proud to be a weaving certified law firm demonstrating our commitment to fostering diversity and inclusion in the legal industry. So for today’s panel discussion, we’ll be exploring three key themes shaping the startup landscape through a lens of AI, first from securing funding in today’s environment, and then second building and scaling a trustworthy AI unsustainable business. And then finally, as the ladies mentioned earlier, honoring the significance of International Women’s Day or Women’s History Month. So I’m thrilled to be joining this amazing panel, this amazing lineup of panelists and excited to guide a conversation that’s hopefully informative and insightful for all of you. So let’s dive into it. I’m going to kindly ask that everyone please hold their questions until the end of the panel. We’ll aim to maybe do about 1015 minutes if we can, and then I’ll have each panelist introduce themselves and provide a brief background. Go ahead.
Danielle D’Agostaro 05:37
Thanks, Courtney. Hi, everyone. I’m Danielle from web capital. I’m a partner there were $100 million fund backed by corporates like Northwestern Mutual Foxconn, Johnson Bowles and advocate health grievious. Prior to that, I built and ran the alchemist accelerator which is a venture backed accelerator funded by corporates and have a portfolio of over 400 companies. From there
Abby Albright 06:04
I am Andy Albright I’m with snowcap Ventures we are a new credit stage or climate seed stage fund. Prior to that, I was a co founder of another fund called WX. Our fund which invested in women led spatial computing companies at the intersection of AI and AR and VR. And I’m currently also account for Outlander, which is a generalist fund at the seed stage.
Melissa Widner 06:31
Hi, everyone. I’m Melissa Weiner, and I am currently the CEO of Leia capital letter capital is the pioneer in revenue based financing. So that’s an undiluted funding, we’ll probably get into that a little bit later, I spent the better part of two decades as a VC before I went back on the operating side. Before that, I ran two companies that both had successful exits. I’ve been an entrepreneur and angel investor, VC. And now I’m in the non deleted side to keep companies away from those evil VCs.
06:59
It’s great to know that no,
Ashley Pantuliano 07:03
I’m actually currently I know, I am Deputy General Counsel at open AI. So I’m a lawyer, I’m a legal team. And like me and my team are responsible for advising open AI and our business on development and commercialization and provision of our AI model services. Keep adding fun
Melissa Widner 07:23
here. So
Bree Hanson 07:25
it’s totally boring.
Ashley Pantuliano 07:29
And before that, I was, I was in house at Dropbox, I was also in house, that sort of company called Blue. I’ve been in tech for.
Courtney Chew 07:38
Great, thank you, ladies so much for sharing your background. So let’s kick off the discussion with our first topic or theme of conversation, raising capital and securing funding. So we’ve all we’re all here for the buzz of AI. Right. But what does that really mean for investors and founders? So this first question is for Danielle and Abby, can you share insights on how AI has changed the investment landscape? And where’s the funding flowing in the AI stack today? And also, are there any specific areas that are attracting more interest than others? Yeah,
Melissa Widner 08:11
sure, um, so we have had aI as part of our thesis from the onset of the fund. And we’ve seen kind of, you know, because we’re backed by corporates, we see that automation could help with a lot of pieces, different pieces of the corporate landscape. So it’s been important to us. And, you know, it’s nice that it’s trendy, it just makes things a little more expensive. But with this new Rise of Gen AI, and how it applies, you know, it’s definitely changed, at least from our point of view, the investment landscape for AI startups in terms of, you know, what is going to be the next, the next big thing, I’m often looking at startups that become features of companies the next day, and then for everybody else, that isn’t an AI startup. You know, it has made things a bit harder. But that just means you have to really get back to basics and understanding what your business is and where you can add value.
Abby Albright 09:18
Yeah, and so the point about the where’s the funding going in the stack, I think we’re still seeing it in the model layer. And we saw that Amazon just completed their commitment to anthropic which adds a few billion in a second. Yeah. And I think that ideally, we’re gonna see more in the app layer, is the model layer becomes I don’t, we don’t know where that will pan out, right. We still don’t know where that value will accrue in this deck. And I think that’s the real opportunity for startups is to, to just be really good at storytelling, and you’re only going to be good at storytelling if you can actually tell a compelling story. going on with how your startup can actually capture value or even anticipates going to capture value, but you have to be able to demonstrate some level of traction or demand. Before you go on, fundraise at this point, like, yes, some of these models, models had multi billion dollar valuations before they went public. out to the public, excuse me, that’s just not the case. For applications, you have to demonstrate some form of demand or attraction, even if it’s not paid revenue right away. And I think that if you can tell a compelling story that the fact is that nobody knows where the value is really going to agree here, at any layer of the stack, there’s meets every layer. So, so just get really good at being able to convince someone and lean into the fact that no one really knows. So if you can show, you know, a realistic pathway, then that’s all you got to
Melissa Widner 10:57
do right away. Yeah, make sure your name ends with AI. funding in general, I was looking at some stats. So in 2020 20, to 2% of all VC dollars went into generative ai i and then 2023 was 17%. So I can’t think I’ve been in venture for, like I said, a couple of decades, I can’t think of a time maybe in the.com, where, where it was that big of an increase. And I think we’re on track for 2024 to be even larger, a larger percentage of dollars going into AI. Awesome. Thank
Courtney Chew 11:30
you guys so much for painting that picture of the landscape for us, I think it’ll be very beneficial for our listeners today. I guess kind of shifting gears a little bit to what investors, our investors obviously want to see a strong return on their investment. So this question is for Danielle, how can founders demonstrate that long term dependability of their business model to ensure that strong return on investment? And in other words, like how can founders or new startups convince investors that their model is unique and won’t be easily replicated in this?
Melissa Widner 12:02
Yeah, I mean, to Abby’s point, you know, it’s, it takes I mean, for us, we look at the team, and we invest in early stage. And that’s kind of all we can go on at this point, just because there’s not a lot of other data points. You know, it hasn’t, there’s not enough adoption, unless you’re a consumer play, which we’ve all seen kind of how that played out already. But from a long term kind of corporate enterprise play, it’s yet to be seen. And so we’ve seen, I think, a little bit more six, I feel like a lot of startups that I’ve spoken to, they’ve all come out kind of on a on a horizontal Play platform where everyone’s learning, figuring out where the real use cases are. And now, you know, for those that were able to raise, they’ve spent that money trying to figure out a couple of verticals. And so really becoming good at your storytelling. Where’s that value? In which industries? Who were who’s you know, hair on fire need? are you solving to me? That is where the defensibility lies? Of course, on the technical side, you need a lot of smart people to build these models in the right way. It I don’t think it was, it was too early a year ago to know how expensive that was going to be. So for some of these companies that are raising billions of dollars, that’s going to hardware costs, that’s going to compute costs, that’s going to stop right and operational costs. How much of that is coming to actually running the business? I don’t know.
Courtney Chew 13:36
Yeah, yeah, that’s great. And I guess kind of to tag off on that, you know, we hear a lot about building a strong moat around your business and how that’s really key. So I’d like to kind of unpack this concept of moat a little bit more. So what exactly does it mean to build a strong moat around your business? What are the specific aspects that a company’s defensible moat? Do you? Do you and your practice find the most compelling? And how can founder solidify their position in the market? So let’s hop into this?
Abby Albright 14:06
Yeah, I think, I think one. So one thing we do probably know, at this point is that it’s probably not a as compelling to go as a business and try to create the foundational model layer, right? Like that’s sort of being hashed out by the big the big guys. And including open AI and, and others that have already sort of come into that. That makes sense, because no one really knows where the value will grow. Perhaps there’s someone else that will come in, but but I would say that outside of that we’re looking to have more specific models, right, and so very, very targeted to a targeted audience with like specialty and multimodal, and I think that that’s one element, I think like data. Labeling and training is also potentially one vote but I think you just go back to it. traditional business models. So partnerships like client partnerships that may take, because it’s still really hard to establish like these often complex partnerships, that could take many years. If that is that alone is a mode, a competitive mode, if you are able to establish those, and that’s just a, that has nothing to do with AI, it has everything to do with how hard it is to get things over the line with with large corporation, there’s a company that I was just, it’s a startup, I don’t know if I can say their name, but it’s a startup in the maternal tear space. And they have huge partnerships that they’ve been working on for years with Amazon, Target, you name it, and that is a huge one, because it will just take other people years to catch up. And they have some exclusivity windows. And so I think you just go back to those types of things. Like you don’t necessarily know how the model aspect will work out. But but those types of things, I think, are pretty clear.
Courtney Chew 16:01
Well, I didn’t say anything else, the lady sort of night? Well,
Melissa Widner 16:07
I think it depends on who the audiences. So when I was an adventurer I was looking at, you know, is this product that’s easy to sell, quick to scale. And then of course, you want it to be sticky, and will this be can be a billion dollar business. But at lighter capital, we’re we’re looking at revenue based financing, and we don’t take any equity. So it’s a form of debt. We are looking at stickiness, and I think of stickiness as a moat. So I know when I was a venture capitalist, I didn’t like companies where the sales cycle was two years. And the implementation was, you know, six to 12 months later capital, we love that because the revenues really predictable. If you you know, for the company, a corporation takes takes, you know, years to make a decision and months to implement something, they’re probably going to be with them for a long time. And I think we will see that with AI companies, the more sticky that almost the harder is to sell your product. And the harder it is to implement your product that creates a moat.
Courtney Chew 17:06
Yeah, thank you so much for sharing. I think that’s very insightful, you know, partnerships and stickiness, right. And so I guess, to kind of tag off what you had just said about, you know, raising capital. And we all know that it can be pretty tough. So for this last question, under our first theme of raising capital, what are the key challenges that companies face in raising capital and some success, successful strategies that you’ve seen that are effective for communicating with investors? And I’ll open this up to everyone. All right. Well, one of the so
Melissa Widner 17:42
this is a very tough environment. It’s a tough this environment, probably since 2009, or 10. And we’re in a really tough environment right now for capital raising, unless you’re generative AI company, and even that 29 billion that I spoke about earlier, most of that accrue to a handful of companies. So when you have to be scrappier than you had to be in 2021, where I saw companies who raised raised on a $100 million pre with an idea. So that just isn’t going to happen. It might, it might actually happen with some technologists who have the new generative AI, that’s still gonna happen there. But but one thing I’ve seen that works really well, it’s just communications with future investors. So you know, you have your meeting with investors, treat everybody that’s a potential investor, as a potential future investor, and communicate with them to the extent that you can as if they are an investor. So one of the best things I saw as a VC was I used to get from a company that I actually invested in as an angel that ended up getting acquired by Uber, I used to get what they called their future investor report. And I got that report for like a year and a half before I ever invested. And it’s just a great way to, you know, build your, your, your potential investor base, and keep them updated with what you’re doing. And it’s surprising to me how few companies hardly anyone does that. And it’s a pretty easy thing to do. I actually spent a lot of time working with startups in my accelerator portfolio in helping them get connected. And you’d be surprised at how hard it is for them to create affordable email that actually communicates relevance. And so we I spent a lot of time you know, and I think it’s super important, because when you think of an investor as a person, that gets a ton of emails from multiple different communication channels. There’s a lot of noise and so how do you stand out from the noise? You you have to you have to do your homework, you know, and you have to honestly treat in fundraising like sales, you know, and knowing who your customer is, what perspective they care about, you know, speaking to them in their language, usually around growth, right? Like Teen tech, all of those things are great. But you really need to highlight like, why you’re winning, right? Or why you’re going to win if you’re super early, and figuring out like, what is it about that person and that fund that, you know, why why do I? Why would they want to connect with me? And so I make I make a lot of founders go through this exercise. And honestly, the hit rate is much higher. When I send an email that has looked like they put some love into a, you know, versus like, the generic emails I get, where it’s like, I never invest in consumer, why are you sending me a dating? Platform? Yeah. So it’s a, it’s something I think we don’t speak enough about to early stage founders that maybe we just assume, is obvious. But yeah, do your homework.
Abby Albright 20:56
I think I will add one thing that has worked, I think, for me, or I’ve seen this work for founders, with me, not to promote spamming, but they actively update me on they have real movement. They’re not like just sending the same email over and over, but they actually have real movement. And they’re demonstrating to me what other people have said about that movement, as well as some experts in their field. But they’re constantly updating me because I think, for those of us who’ve done sales before, I’m kills all deals. And so generating a sense of speed to close and that there’s real momentum, especially in a market which right hard to raise. You can do it by continuing to show like, hey, it’s we’re growing really fast. Now’s the time to act.
Melissa Widner 21:42
But yeah, investor updates are fantastic. Yeah, I
Abby Albright 21:45
think those are better than actually some people will send like a notion page where they’re they’re constantly updating the page. Yeah, but I can’t tell what you updated. I don’t know when I know. Yeah,
Melissa Widner 21:55
we all live in our inbox. Yeah.
Courtney Chew 21:56
So emails. I mean,
Melissa Widner 22:00
until they figure it out. Yeah, no, no, please. No.
Courtney Chew 22:06
Okay, thank you. So much. So so we can’t use chat TPT to draft that email for us. You can Yeah. Well, thank you so much. I think that kind of rounds out our first topic on raising capital. So transitioning now to our second topic of conversation, building a trustworthy AI and scaling for the future. So as someone in my practice, who’s worked with AI startups, I’ve seen firsthand, you know, the importance of navigating legal risks as it relates to AI, because it is exciting, but it’s also uncertain. So now you can get Ashley to chime in a little bit. Given your expertise, what are the top legal risks in AI for scaling companies in this year 2024, especially regarding IP ownership? And then also as companies scale, how can they best manage that risk within their AI integrated service?
Ashley Pantuliano 22:59
Yeah, I would say terms of legal risk management. So I think companies should think about a couple of things. When I think about legal risk. There’s all kinds of legal risks with AI, like, copyrights, privacy, safety, there’s worries about misinformation, disinformation, about abuse of AI, and how it can be used for all these terrible thing. And so I think companies should really think about what stage they’re in, and what their risk profile is, before they sort of like spin up all these huge, like legal resources to assess their legal risk. So if you’re a super early stage, AI companies think about, like, you know, what is what your exposure is, Are you like just trying to get your company off the ground? Like maybe, like, try to have a viable product first. And then like, think through, you know, sort of like what you’re going to need in order to manage the risk? Or are you You know, like, a company like opening eyes have this huge sheet of like foundation model, and has to be the reason they’re like, you know, getting sued by everyone’s. So I think it’s definitely spectrums. The other thing to think about, I think, is where you are on the value chain. So like, we’ve talked about people building their own models that probably not very many people building these like large, large foundational model, or people who are building on open source people who are using API’s to have an AI service, right. So like, I think thinking through sort of where you fall on that spectrum will also be helpful because the foundational model providers are the ones that are gonna think through, you know, legal safety, all the risks that come with pre training, a large model versus like a service that is building on an API service, for example, then they have to think about what they’re doing with that technology, the data they’re putting into sort of fine tune the model and things like that. So I think definitely, like breaking it up and going a level deeper in terms of of what your risk profile is, would be would be helpful. But I’m happy to talk about the details on any major legal risks that come with AI. And then in terms of IP ownership, I think, again, like breaking it up into what what kind of IP ownership we’re talking about, are you talking about, you build a technology and you want to get IP protection on it? I think that is actually not that different from like, just standard technology. AI is a technology, there’s frameworks for IP protection for it, right patents, copyrights, you can get patents on whatever the software methods you are using different ways of how you, you know, deploy the technology, there’s all kinds of like protection you can get for that. In terms of using AI, just like lots of companies are now just using AI in their in their jobs. They’re using it to create content, they’re using it for data analysis. But it’s definitely IP issues there. Right. So you have us in different countries have come out and said that I think protection is for human invention for human creation, right. So anything that has been created solely by AIS is probably not going to be it’s not going to be very easy to protect it. So when whenever people ask me, like, Oh, I’m using chapters against me to like, create marketing, copy or create this kind of like, work of authorship, like how should I think about IP protection there, I always tell people, well, you should make sure that you obviously first review the work and make sure that you know, you find it, it’s an original work, it’s not taking content from somewhere else. It’s not citing to other like not like sources that are maybe made up or hallucinated or whatever. But then also make sure you add your own sort of human creation element to it so that you can get protection and then document what you’ve added and make sure that you keep track of that, because that can be important when you’re filing for IP protection. Oh, yeah, that’s a lot. Yeah.
Courtney Chew 27:03
Thank you so much. Yeah, that’s like a, like a whole hour and a half condensed into five minutes. But yeah, thank you so much for to think about, you know, the stage of where you’re at as a company and where you fall within the value chain. And also, considering these legal aspects, there’s a lot to think about. So I kind of wanted to build on that when you mentioned, you know, you should look at the stage of the company. So, like, at what stage should companies think about establishing these frameworks for accountability, fairness, or data privacy? And then who should be involved? Who should they think about evolving, whether that’s on the technical side with data scientists, or legal side with privacy counsel, or whoever, and so,
Ashley Pantuliano 27:44
yeah, so again, like thinking through, I think, definitely like a huge data AI governance framework, is probably more better suited for like later stage companies. But you do have to think about, I would encourage companies to think about, like the type of service that they’re providing. So if you are a child directed service, and you’re collecting audio and video samples of children, and you’re training on that data to create a model for service, that’s going to be a way more, you know, have way more legal ramifications, right. And then if you’re like, a b2b collaboration software, and you’re using AI to power your search, like probably don’t need as much on like the data governance, data governance, side of things. So I think it definitely depends on the type of service. And then whatever your resources are, and what your risk, like what your risk tolerance and profile is, and what you think your exposure is. And so you can, I would encourage companies to just talk to talk to your favorite lawyer and talk to so you can, you can get a lot out of a one hour conversation with a lawyer that is pragmatic and is very familiar with that field and knows sort of like what, what your company could need, and can give you like a really, really quick overview, and then you can go from there. And you can go and build out how much ever you want to build out. So you can really, really get a good sense of just spending like an hour with a lawyer. So yeah,
Courtney Chew 29:11
yeah, those are great points. Yeah, we do have a lot of earlier stage clients that we represent, who may be working in, you know, the health data area where they’re collecting information from, you know, patients or nurses or doctors. And so it’s important to get legal advice earlier on, so that you can make sure you’re managing that risk. Well. Um, so yeah, thank you so much. I guess we can shift gears now a little bit to scaling and growth. So how can companies achieve a sustainable and scalable growth while navigating a potentially tighter funding environment as we’ve mentioned, and I’ll open this up to any of our panelists.
Melissa Widner 29:52
Well, I, it’s I I’m talking with a VC hat, but you know, now I’m live Being in another world at lighter capital, where a lot of our companies, we’ve done close to 1200 rounds of financing at about 22% Go on and get venture capital. But a lot don’t. And there’s a lot of great companies out there, they never get talked about rarely get talked about, be weren’t venture backed in the technology sector. It’s like 98 to 99% of technology companies don’t get venture backed, but we don’t hear about them. So what’s interesting is looking at growth, with venture backed companies versus non venture backed companies, when I was a venture capitalists, when we put that fuel in the fuel was the money, we wanted them to grow. And you’re putting a lot of risk on the companies because they have to grow, you have to get a uniform, you have to get a big exit to pay for, you know, the nine companies that didn’t return anything. So So I think, when we’re talking about growth, we have to understand, you know, what is the goal of the shareholders. So the goal of the shareholders, if you have venture ship, venture capital shareholders, you’re going to have to grow quickly, although last year, they were telling companies to slow down. But eventually, they’ll be looking for those returns. But as the market recovers and be pushing companies to grow, again, which puts a lot of risk on a company. So I think my advice for a company for people starting out and thinking about how they’re going to capitalize their businesses is really, you know, understand what you want to do, and what growth path you want to have, and what control you want to have along the ways. And that that will help determine, you know, who you take on as investors. And I think there’s a big part of this, which we saw over the last couple of years about getting back to basics, and really understanding what are you building? What value are you providing who is necessary within the team to provide that value versus over hiring? Right, we all saw what that inflation period look like, in terms of people and capital. And the unfortunate results of that, and within the last year with with a bunch of tech firings, as people will kind of recalibrate what their actual needs are, what products they’re building, what, what value they’re bringing to the table. And so if you start with that conservative, not conservative, but you know, just mindfulness when you’re building a company, in terms of what, who do you really need and the founders are critical at this stage, especially in the early stages, the founders are super critical. Do you have the right founding team to build a basic version of this vision to start testing, and, and finding, you know, customers along the way, and then once you do that, then you start scaling, right, then you start adding fuel to the fire and growing that out, but I often, you know, I, it was, it was at a startup detriment to take in so much capital, so early on in a process, you know, thinking like, a resources of plenty, but, you know, then you start operating a business in a very different way, when you have what you think are endless resources. But you know, I think like, you know, we always talk about like, well, you figure it out when you get there, but we all, you know, everyone had a hard time figuring it out when they got there. And it resulted in a lot of flattened down rounds, a lot of, you know, a lot of downsizing, or just businesses shutting down, you know, and so if you keep that in mind, keep it mindful at the beginning. venture money will be there. You know, it doesn’t it’ll, it’ll be there for when you’re ready. But don’t try to grab it too early. I mean, not to mention, so many liquidation preferences that off the probability of options being worth anything, it’s very small. So, but it’s hard to sorry, just to add, I mean, in an environment we’re in for a very long time, you know, really until about mid 22. You know, the goal was to raise as much money and that became the goal, not delighting your customers and creating a profitable business, it was to raise as much money at its high valuation as you get that was the goal. Yeah. So we were off track for a pretty long time. We’re getting back on track.
Abby Albright 34:12
And I think I just reiterating the testing point you made. I mean, there’s just so many ways now to to test if there’s demand, what is the willingness to pay? Right, like just very basic things that I think really, people either bury their heads in the sand a little bit because they don’t want to know, they spent, you know, there’s some cost bias a little bit or like they’re just so committed to some area. And not to say that you can always validate things, especially if it’s an entirely new behavior, but at some point you have, you have to be able to demonstrate that and so I think that that’s just just to keep hitting on that fact. And then I think what I’ve noticed and I don’t have any data other than completely my own experience so far, but I’m curious if you guys have seen that. I’ve seen more customers investing in products before because as things get so specific, sometimes VCs, especially generalist VCs, we don’t always know the true value of something. And it when it speaks so highly to what you’re doing, if your customers are paying you for the service, or maybe they’re not even paying you yet, or they’re on a trap, are now investing in your company, that that gives much more confidence to Dylan’s generalists. But I also think like, it should give you more confidence in the product you’re building. So I think there’s just continual ways to do
Courtney Chew 35:30
this. Yeah, that’s great information. I think it’s like when founders can prove the value through, you know, the product or customer base, and it gets them to the next step. So kind of tying onto that, you know, as companies do navigate these challenges have a tighter funding environment, securing the next round, once they’ve proven themselves can be even more crucial. So this is where due diligence come becomes particularly important. And so for Ashley, given your legal expertise and understanding of I guess, AI companies in general, what specific areas of due diligence? Should companies like open AI or just like companies in general focus on to prepare for that next step, or the next round of funding?
Ashley Pantuliano 36:13
In terms of like legal diligence? I would say, just being prepared to answer questions around any of the major legal risks that companies these companies would face? So again, like on the open AI side, there’s a lot of questions around training data and how we use data, how we use user data to improve our models are kind of locked out of how do we come up with privacy laws? I think those are, there’s like basic questions that any lawyer that’s doing diligence on the company will will want to look into in terms of companies that are maybe not doing so much of the training, I think there’s still sort of a focus probably on I’d love to hear I don’t know if the investors focus on like, what people are doing with data, because there’s like a lot of fear and uncertainty doubt around that. How are we How are people using their research data? How are they protecting it? Are there any copyright issues, because copyrights huge with AI. And so I think those are like the big big Johnson, legal areas as far as product. And then also, just general diligence applies, like, again, as just a technology. So don’t forget about all the other standard things that you have to do when you’re doing anything with that matter. So
Melissa Widner 37:39
I mean, we’re, you know, because there’s so much, so much noise in the AI space right now, early on, I think there was so much hype, and you know, if it if it said AI, you know, there there, the buzz kind of created the momentum. But now that we’re we’ve gotten a little bit smarter about what that means? Are they using chat govt to back their business? Where are they getting their data? You know, is it just a wrapper isn’t a real proprietary models at real data, we’re able to ask better questions during our diligence. And this is helping us kind of sort through the noise, not that we have the answers by any means, you know, but it helps us get a little bit more comfortable when making investments. And that’s why we play such a high value on on the team, you know, we can often look at a company and say, do they have the technical chops or the capabilities internally to actually do what they say they’re doing? And then when you look under the hood, sometimes you realize like, oh, maybe it’s just maybe it’s just another rapper, you know, things like that. So w rhp.
Courtney Chew 39:01
That’s actually a great segue. Last, last topic under this conversation. So if we kind of, kind of turn towards the future of AI, and like this evolving world of AI, and we have advancements like chat, GPT, those GPT, four coming out large language models like Google’s Gemini that are really changing the boundaries of what AI can really achieve. So this has led to some concerns of people thinking that AI could really entirely replace their business. So like with this in mind, how realistic is that concern that AI could potentially erase? Replace entire businesses, and what types of businesses are most vulnerable? And I guess for companies who are seeking investment, what advice can you offer on how they can best prepare for the future with increasingly sophisticated AI? And we can start with Melissa and anyone else can chime in Have
Melissa Widner 40:04
one of our investors basically said he’s just sell everything now and go buy a bunker in New Zealand that you know, that you point to oh, you know, this is kind of overhyped, and it’ll, it’ll bring some great efficiencies, but and everything in between. And I’m definitely not skilled to talk about it or predict the future. And I’m not sure if anyone is at this point, have a way to your earlier point. But I’m sure you would have some good ideas. There are some are some opinions there. Yeah, I
Ashley Pantuliano 40:34
think I hear a lot we hear a lot about, like, is AI going to replace entire industries? Yes, like that. There’s certainly a lot of that in the legal field as well. And my personal view of it right now is that the technology is just very useful, it’ll just bring a bunch of efficiency, well, it’ll eliminate low level work that it can sort of replace, yes, but it’s not really different from like other big technological shifts that we’ve seen in the past. And it just brings greater efficiency. And then those, those people that were doing network can do other work. And really, like it kind of helps up level everyone’s productivity, at least that’s what it is right now. As for what it can do in the future. I mean, there’s, there’s a lot that, you know, we don’t know. And so I think one thing, companies that what one thing that can do is make sure that they follow up with the technology, actually use it, figure out how it can really help you because I think it can be very, very useful. And I definitely understand its risks and limitations, but at the same time, it is something that people can really, really benefit from. And we’ve seen a lot of benefits, customers stories, you know, obviously things in the news about how Chachi Beatty has helped a lot of people in a lot of different areas. And so I do think like JetNet, right now, it’s a pretty, pretty good benefit I
Melissa Widner 42:03
think in software development, I mean, most CTOs that we’ve spoken with, have said that, you know, their job will become increasingly important. But the number of people that they will require to create new products will decrease significantly. So you know, that that probably, you know, if you go back 25 years ago, in the US, anybody who could code was high in demand, and then a lot of that a lot of sort of the basic coding went offshore. And it was a great way to provide wealth to, you know, a lot of skilled people. And so what will happen there, I think, is pretty interesting. I mean, there’s, there’s something to be said, I mean, with the rise of mobile, right, there was a fear there at the beginning, having a computer in your pocket being tracked all of this stuff, you know, AI is the same thing. There’s, there’s a fear that always starts. But once people start using it, and integrating it as part of their lives, they realize how it can complement and make them even more efficient. So what we may see, you know, in my in my crystal ball, is that we may see this world in which yes, there is maybe a decrease in certain in certain types of labor, but we will probably see an increased in and I don’t want to call it specialized labor, but there will be you know, and those people are going to be expected probably to do more, you know, with with the time they have, because technology is going to be complementing and supplementing a lot of their work. So if if it used to be well, we need five engineers, well, now we can do with two, but those two, using technology should be like 50% 100% more efficient with their time because there’s kind of no excuse, right? It’s going to take time, of course to get there. But I think that just shifts us into a different type of labor market where maybe people have to go to school a little bit longer, or get training in certain industries in order to, you know, to prepare for this. But that’s not necessarily something to be fearful of. It’s just some I see it as kind of an opportunity for people to, you know, figure out what that specialty looks like for them, and maybe start making inroads to getting there.
Courtney Chew 44:27
Yeah, that’s great. So it sounds like you know, with AI being so integrated in our lives now, it’s nothing to be afraid of by just learning how to adapt and use it to be more efficient, even though that might come back at us and requiring us to work a little harder. So yes, thank you guys. Thank you ladies so much. And we’re getting ready to kind of wrap up this super insightful and informative discussion that we’ve been having. But I think it’s fitting to recognize, you know, the importance of this month as the ladies mentioned earlier at the beginning, as this panel was really brought together In part to honor and also bring light to women’s history month, or International Women’s Day. So I’ll spare the details of you know, the history of how it came about, as that was briefly mentioned that, you know, since since International Women’s Day has become kind of a month of celebrating women’s achievements, throughout history, and even to today, and also inspiring, continuous progress. So I guess for the last question to round everything out, for our panelists School of like, female rockstars. They’re, they’re really killing it. So reflecting on the history and significance of International Women’s Day or Women’s History Month in general, what are some of the biggest challenges you faced, as a woman or even face other woman you’ve witnessed other women facing? And what strategies do you employ within your respective fields to champion inclusivity and empower other women? So we go down the line, Oh,
Melissa Widner 45:56
baby was kicking, I was like, she’s letting me know something. You know, actually, personally, this this has been, because I’ve become a mother recently, that has shifted my perspective, in terms of how women are kind of viewed in the workforce, once you’ve changed into that role. You know, because basically, you can keep up for her when, you know, when you don’t have anything kind of safe holding you back. But it’s definitely changing your priorities and things and a lot of other, you know, women that I’ve talked to within VC and just other industries. You know, maternity leave is not something that’s either guaranteed or even like known. There’s so many women recently that I’ve talked to even at my own fund, where there was no maternity policy, you know, we had we have to create a me there’s, yeah, right. Right. Exactly. And so, you know, it is definitely a challenge, when you have to, you know, people have to, like, bring communities together, talk to legal, like, you know, I’ve heard somewhere, I’m like, that sounds like blackmail, like, you know, like, talk to a lawyer. Because, you know, it’s, it’s kind of the wild west out there. In that perspective for women. You know, when you make that transition, especially since BC, we’re just starting to get women to certain ranks and stuff. But if you’re lower level, you know, we’re still I’m still having friends, where they’re like, Yeah, I’m the only woman on my team, you know, I’m the only woman on well, we just hired a new EA, so I am. But I, I, you know, most of the times you are the only woman or small group of you, and you don’t have that strength and numbers. And so, you know, it’s a challenge. It’s an, it’s a challenge. And all I can say is, you know, all we can do is try to share what’s worked, what hasn’t be supportive, you know, and tell women, you know, help help women kind of navigate through it, because otherwise you’re flying blind.
Abby Albright 48:07
So I kind of two wins. But I think the first is the women being judged on their past and accomplishments. And the men being judged on their potential. I mean, we saw this actually in emerging tech is, it’s especially challenging or rears its head in emerging tech, because it’s emerging technology. And so you can’t demonstrate that you’ve done things in this field yet, because it is all potential. So that’s actually what we saw. My co founders and I, for WX, Czar was this AR and VR and AI applied to that. women that were very technical were were just overloaded. And so what have they done lately in this field, we’re like, well, they’re doing it now. You know, anyway. And so we really not to say you have to start a fund to back women. But that is what we actually started doing everything but funding, and we were able to raise up on and give them actual cash, which was helpful as well. But I think that that’s one thing I continue to see. And then I think what do I also try to do in my day to day life is just challenging, like unsubstantiated claims, like in hiring, where maybe the description of the woman is that she and I’ve heard this, she doesn’t seem up for it. And I’m like, I don’t even know what and then literally applying and we were interviewing her and then also, the man seems to get it. And I was like, but he has way less experience. And so just really challenging it like not in a condescending way, but just but what does that mean? And like, what is what are the facts say and that kind of thing. So I think those are two. Yeah,
Melissa Widner 49:43
I don’t know where to start here. I will start on you know, there’s the stats are still terrible in terms of percentage of venture dollars that goes goes to women founded companies, but there’s been so much progress made. And I mean, the fact that most of you VC firms now do have some women on the investment team, even though not necessarily at the partner level. Yet, if you went back even more than a decade, just a decade ago, that was not the case. And it wasn’t even talked about. So I became a venture capitalist in 2000. And in Seattle, and I host an event at my house now, every year in Seattle, I started three years ago for women and VC. And we have like 60, or 70 people on the mailing list. I always joke that if we had done it in 2000, there would have been three. And that’s it. I’m not kidding. Like that was that was all there was, and you, it wasn’t even talked about. So there were a lot of things that happened in the early part of the last decade, with lawsuits or like how I’m thinking, but I mean, it actually did lead to some good discussions, and it led to companies. You know, Andreessen Horowitz can’t say, hey, we have 52% of our staff is women. So we’re there when they didn’t have a single woman on the investment team. But you know, that has changed so So things are changing. And also what’s changing is the dollars that are not dollars that are going to women, but the number of women run or co founded, female, co founded companies that are getting funded, the dollar still look really dismal. Because a lot of the really big rounds, you know, you could have two rounds happen. One is billion dollars, and one is $10 million. And if a billion goes to the bailout Committee, which is usually further along, it’s going to look skewed. But I can tell you that things have really changed in terms of everybody I spend most of my time in Australia is measuring what’s going on. VCs are putting out there how many women founded or co founded companies they’re investing in. And that wasn’t happening while ago. And also in Australia with the best the biggest unicorn we have Canvas funded and run by a woman, Melanie Perkins. At lighter capital, what’s really interesting, okay, I’ll pull back a little bit and ask the VCs and other any VCs in the room, what’s the most important thing that you look for when you’re making an investment decision? Like what what is what what what are you looking at? Primarily when you make an investment decision? Early stage and film? Yeah, sounds good. Sounds good. Okay. Yeah. So it’s founders. And that’s totally subjective, right? Yeah, if you’re saying we’re looking at revenue, we’re looking at technology, but founders is totally subjective. And I had the bias, you know, towards, you know, white and Asian men aged 25 to 40, when I was when I was a VC, because that’s what I saw as that’s who was successful. So what’s interesting at lighter capital, you know, we are funding, the application takes 10 minutes, that sounds like a plug. But I mean, it could be any revenue based financing company, but the application takes 10 minutes, and we pull in the data from bank accounts and accounting to your accounting platform. And we make a decision based on the data. So what’s happened is, we’ve funded a lot of female led companies, because we’re not looking at the team at all. So it’s really interesting when you take that out, and it’s not just men that have that bias. It’s anyone who’s out in the world, because you’re looking for pattern recognition. And, but But it’s changing, because when you’ve got companies like Canva, and Melanie Perkins, you know, creating billions of dollars for her shareholders, then people are starting to think, oh, actually, you can make money back in women. And I don’t know how this is going to change other than you have to continue. Yeah, you gotta. You can’t see it. You can’t be a writer. You can’t be what you can’t see.
Ashley Pantuliano 53:26
Um, yeah, I echo everything, everything everyone else has said. I’ve been pretty lucky in my career in that I’ve worked in tech. And I think tech is like, they’re pretty sometimes hard to work, but they’re like, we definitely pay attention, I think, to these types of in the left, that’s
Melissa Widner 53:43
a recent phenomenon. Yeah.
Ashley Pantuliano 53:46
Definitely pay attention, I think to diversity, inclusion, gender differences, unconscious bias, and things like that, at least the companies I’ve been at, but even still, there are definitely times where it’s noticeable. Like, when it comes time to give feedback for women. Like, like Abby was saying, like, the feedback is like, Oh, she five, like, she’s not assertive enough. Yeah. And I’m like, will you say that if he was if it was a man like, I don’t think or only show me about the woman if they were assertive? Yeah, exactly. Yeah. Right, right. Yeah. So I found it helpful to just like, call that out. Like if my lead ever said something like that. I’m like, sure, sure. Like,
54:29
let’s unpack that a little bit.
Ashley Pantuliano 54:32
The other thing that sort of, I’ve seen, especially like Mom, mom troubles. So I’ve been pregnant a few times, several different companies and more than once, I would say like, three at least three or four times I would hear things like oh, it’s a it’s a break like you’re taking a break. Break from work, work, work, vacation when I get to relax I can check my email
Melissa Widner 55:02
20 different things.
Ashley Pantuliano 55:05
Or I’ve even heard multiple times this person is pregnant. And so they will not be eligible for a bonus, and they will not be able to they’re taking leave, and they will not be eligible for promotion. And I’m like, that is illegal. So I think spreading the word when you see it, like saying something because again, yeah, like, it’s not just like we just, you know, people have their own biases. I think it’s like bringing it to light.
Abby Albright 55:31
Yeah. One thing I don’t know if I should even say the ballot, but the, I’ve actually recommended to people to change their environment. Because I think that I’ve read, I’ve worked long enough now. And I’ve had so many amazing bosses and so many amazing colleagues. And it’s the actually the odd I would say the exception anymore for me to have something that is completely not getting it and making it very challenging for me, and I don’t know if it were the, my training and the female to like, try to convince them and to try to see them and make them change their ways. And now I’m like, oh, not your problem. Yeah, move change environments, because there are enough people that are going to support you that you just find them. It’s way better. And really just like not worth your effort. Yeah. Yeah.
Courtney Chew 56:19
Thank you, ladies so much. That was awesome. We started 10 minutes late. So I’m, I’m sorry? No, no, we’re gonna go in until 110. I think we could take maybe one or two questions, either from the zoom or from our in person, audience, if anyone has any.
Kate Kozak 56:34
I do. And I think we should go on the wrapper with the W question. Our clients, a lot of our clients are AI as of like, last year. That’s, that’s popular now. And I think one of the questions, you know, for funding purposes, you’ve talked about the wrapper, like, Can you unpack that a little bit for the people online who may not understand what that is? And what you’re kind of looking for in AI companies? What is a wrapper versus what is proprietary? Go ahead. Yeah,
Melissa Widner 57:04
so whether you’re using a third party source, like an open AI, or are you building the model from, you know, from scratch and house with your own data sources, right. And so, basically, and we’ve seen this happen in before the AI boom, too, you know, with LinkedIn, right? They shut it off, your business is screwed. So, right. So if it’s more of a question around who owns the data? Is your business model completely grounded in that? If it is, then you need to find ways to have a base, right, have your own strong base, that isn’t going to be determined by by an open AI or anthropic or one of these other ones? Um, yeah.
Abby Albright 57:50
I do think we’re seeing more startups that are using multiple models, and they’re not tied to one. So I think that that that risk is getting Yes, but I do think people have always they said this for a while, like, I remember there was sort of like a condescending comment on like, superhuman being a rapper or like Gmail or something. You know, and I think so I think it’s turned around to in a way, that’s certainly helpful. But yeah. If you can you risk that. Yeah. But using multiple models is probably a good thing. Yeah.
Courtney Chew 58:22
Maybe one more question, if that’s
58:25
people. I mean, yeah, go ahead.
58:29
Yes, I have one quick question. I know, there’s always a lot of misconceptions out there. And it’s good to be thorough. All four of you out there is that what is probably a common misconception you’ve heard where you want to dispel here today? Oh,
Melissa Widner 58:46
women AI beasts. Yeah, sorry. Just
58:51
in general on the topic for today, you know, women in AI and investing? Oh.
Abby Albright 59:06
I don’t even know if you can really even define what maybe this will say something. What like an AI company is because we actually have this with like AR to at some point. It’s just a horizontal layer. And it can be used as a feature or it can be aI first, but even then, like, it isn’t an AI company, at some point in the future words, expanded and offers other things. So I, I actually think it’s, um, don’t, don’t try so hard to actually be an AI company, because I don’t even know that we know what that actually is. And then it doesn’t help you. So it reminds
Melissa Widner 59:44
me of, you know, a company calling themselves a tech company because they have had a website, sort of analogous to Yeah, where, you know, there’s something you’re doing that AI is empowering your product and therefore you’re an AI company, and there’s look, there’s a lot of pressure to become an To be in that category now, because like we talked about, that’s where 17% of the funding went one.
Abby Albright 1:00:04
One thing that I do think that has come up with was I’ve talked to founders and some of you my angel portfolio company, where they, they use machine learning, and they do some AI here and there. The biggest thing that they’ve had to face in fundraising is just to answer the question of, well, isn’t AI going to do that thing that you’re doing? And as long as they can answer why they’re either going to be there with it, or why it won’t, you know, make what they’re doing. Yeah. irrelevant, is like the only thing they don’t have to go. Oh, but we’re also AI. Yeah. And because I actually think that muddied the water for them. Yeah.
1:00:44
So actually, I have a great
1:00:55
so many different company, but when it comes to storytelling, and so we sat in for recess to play my hands down something No, my scientist training tells me is that we just the woman raises scientists screencasting, yeah, we learn the language, and I look at only then you can print. And then what my vision tells me. So I am thinking is up until becoming the CEO, I had to really be nice. My co founder chairman told me that torture, so I didn’t get any of that. But these are all muscle units for storytelling. And I mean, really, you know, assertive, like, you know, and the amount of assertiveness I’ve seen man is so cute. Like no other way. Most of us actually he was flipping through a deck. He told me, he’s saying that bullshit. I know, he doesn’t do that. But he’s screaming. And then he said, He’s cleaning this, he doesn’t do that. I know that he doesn’t do it, but he got my attention. And then when you look at like me, I’m like, you have to be really careful. What your own co founder level with the sales experience, because only the sales me can tell you I’m selling this and I have to paint the vision for the future, only then people will come on. So how is a woman or is that just a woman? Handicapped? So scientists and together so I think all the types of technical co founders have that problem? Have you seen people who have overcome this without like p90x or snorting? Because I’m like, no, because I’m really always surprised maybe to just work out. So So have you seen anybody who has been delusional themselves? So evolving themselves into a Senate? Well,
Melissa Widner 1:03:02
I so Larry Ellison, one of his biographies I read a long time ago, you know, they said he didn’t lie, he just use different tenses. And this versus we will happen, or, you know, we might have it a future. But it is, it’s not just that women are less likely to do it, they aren’t, which is why it’s they’re less likely to paint a vision. I mean, we’re helping with any V bolt effort for women led companies and lighter capitalism, 1100 rounds of financing we’ve done I should check that, but I don’t think there’s any, but when we’re just really punished when they do that. And they don’t, I mean, Elizabeth Holmes is in jail, not that what she did wasn’t wrong, but she’s in jail. You know, there aren’t others men in jail who were selling something they didn’t have. So, so it’s hard and we’re not there yet where it’s okay to do what you need to do to raise the millions of dollars and not succeed and be female and not get like horribly punished for it. Just
1:04:03
for the sake of like being that even though you just can’t do this
1:04:17
we just need more examples. Like
Abby Albright 1:04:19
they’re, they’re like real resources. And there’s a guy, Robbie Crabtree, I don’t have anyone else follows him. But his whole thing is we’re gonna start at some storytelling, but then it’s full and he has found I think he’s a lawyer. Actually, I don’t I hope he sees this. I’m trying to do good here. But yeah, it’s a whole thing and storytelling and actually my friend Jason gate, like his whole business is storytelling for startups. Because it is it is a skill. I think there’s also that like, terrible idea, or at least I feel like I faced it and sales were like, We’re the non technical or it’s like a somewhat derogatory term, but basically sales was a very real skill and not everyone I think everyone could be taught to do eventually but you don’t have time to do that right necessarily maybe you have like an affinity towards it and you can learn it quickly but but if you have to move fast like bring in a salesperson like and you said you did right and I think that that’s critical or work with someone who is that’s what they do they teach you how to present yourself what to say what not to say how to tell a story, and I think it’s well worth the money potentially. Yeah,
Courtney Chew 1:05:28
I think that’s pretty much all the time we have today.
Kate Kozak 1:05:35
Lots of energy production some other people online if they want to reach out to you how they do that support me I’ll start with you. Oh, yeah,
Courtney Chew 1:05:41
um, you can find me on LinkedIn or email just Courtney Theo your T Nui SFM dot legal and also LinkedIn. Yes,
Abby Albright 1:05:49
LinkedIn for me to LinkedIn works for me But Abby, it snowcap SN C AP WCS
Melissa Widner 1:05:55
Melissa at lighter capital.com and also LinkedIn, Melissa Whitson,
Ashley Pantuliano 1:06:00
LinkedIn for me to actually potentially be a anti Uli.
Courtney Chew 1:06:08
Match and thank you to our sponsors as well.
Kate Kozak 1:06:12
Thanks, everyone. We’ll pass out the Zoom link shortly. Thanks. Bye
