Investing In Tomorrow: AI, Innovation, And Growth With Mike Ryan, Co-Founder, Bullet Point Network, Part 1

 

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Download “The 10 Best Things To Know About Venture Debt” from 7in7show.com.

Mike Ryan, CEO of Bullet Point Network, shares his wealth of experience in finance and reveals key investment strategies for the current market environment. Dive into trends, risk management, and timeless investment principles that can make a difference in your portfolio.

In this episode Zack Ellison and Mike Ryan discuss:

1. From Hype to Hustle: Startups Adapt to Pragmatic Capital Raising
2. Post-Bubble Capital Raising: Crafting a Credible Business Plan
3. The AI Gold Rush: Separating Hype from Prudent Investment
4. Unlocking the Power of AI: Strategies to Avoid Deception
5. Capitalizing on Scarcity for Downside Protection and Upside Returns
6. The Venture Debt Landscape: Opportunities and Risks for Investors
7. Betting on Growth: Unveiling the Formula for Investment Success

Investing In Tomorrow: AI, Innovation, And Growth With Mike Ryan, Co-Founder, Bullet Point Network, Part 1

Introduction To Season 2

Welcome to Season 2 of the 7in7 Show with Zack Ellison. This season, we’re focused on investing in innovation. We’ve got one of the best investors out there, Mike Ryan. Mike is the Founder of Bullet Point Network, known as BPN. He’s done many things in his career that are noteworthy. Mike, I want to turn it over to you to talk about how you got here and what is BPN.

Thanks, Zack. It’s great to be with you again. Quick background on me, I grew up in Staten Island. I went to Yale and then went to Wall Street. I went directly to Goldman Sachs. I spent about two decades there. I was a partner at the time of the Goldman Sachs IPO for about eight years afterward. I eventually became the global co-head of equities.

I left Wall Street and started my own family office and then maybe five years or so into that, Harvard University asked me to manage some money for the school’s endowment. I ended up managing about $6 billion of direct investment, plus another $12 billion that we allocated as an LP to co-investors in other people’s funds.

I left Harvard and started Bullet Point Network or BPN. It’s a software platform and an analyst team that we make available to venture capitalists, growth equity investors, credit investors, and some buyout funds, and sometimes, to the portfolio companies of those funds. That’s what Bullet Point Network is. That’s my background.

I’ve tried out BPN and your platform. it’s awesome. I want to talk about what goes into that in terms of the scenario analysis. A big part of that will be what you’re doing with artificial intelligence and that’s a big theme in the market nowadays. Before we dig into the specifics of BPN and AI, let’s start with the bigger picture of what you see in terms of themes when it comes to investing in innovation, specifically in the US and maybe in the venture ecosystem.

 

 

The current reality is a theme. Companies are essentially looking to raise capital. They usually are and they are once again. There was a period of time where there was so much change, so much reduction in valuation, and so much limitation on capital availability. There had been a period preceding that where there was so much abundance of capital that companies were a little bit in disbelief for a while and maybe were hoping that things would rebound.

I don’t think they’re hoping for that rebound anymore. The number one theme is pragmatism. They’re back to raising money. They’re accepting the terms that it takes to raise capital in equity or traditional preferred rounds, as well as in debt. In your neck of the woods and elsewhere, that’s the number one theme. Maybe it’s back to work, back to raising the money because you can’t be a growth company that’s not growing, so you’re going to have to invest. That’s theme number one.

Theme number two is related to that, but there’s no longer a free pass. You can’t just have a great idea, a powerful credential founder and raise money. You’re going to have to have a much more disciplined, well-communicated, and well-thought-out business plan. Some of these very innovative things require quite a bit of capital because you’re inventing something. You might be building factories, creating new technologies, or pursuing patents. Think about some of the most innovative things in the world. Many times, they require a lot of capital and a long timeframe to develop them and bring them to fruition. Not always, but many times.

It’s not enough to have a great idea or a powerful founder. You need a well-thought-out business plan and discipline to succeed. Share on X

That is an interesting intersection where you have companies wanting to raise capital, needing to raise capital to pursue the very innovation that we’re talking about here, and investors being more disciplined, requiring more from the business plan, and maybe being a little less willing to invest in the vision with perhaps the exception of AI, which we’ll come back to. It does appear to have bubble-like characteristics in the funding markets now. In most other areas, whether it’s different flavors of EVs, their components, traditional biotech, which is one of the most innovative things in the world, MedTech, biotech, a lot of long cycles, a lot of regulatory risks, a lot of scientific risks.

Even in defense tech, consumer tech, or FinTech, when you have long cycle times, real R&D budgets, and real factory and capacity building that you need to do, you need a lot of capital. The second theme is you have to communicate your plan with enough specificity and credibility that they will give you the capital. I’ve touched there in passing on a handful of industries. Those came to me off the top of my head because those are industries that we’ve worked on with different VC partners.

Investing In Industries And Companies

Mike, when you’re thinking about investing in industries or companies in particular, what are you looking for? What are the factors that signal that an investment could be good and more substance than hype?

We start and finish with the old-fashioned fundamentals. How good is the team? Is the founder and the management team proven, outstanding, and strong? We also focus on the market. Is the market there for the taking? A lot of people get confused about thinking broadly in terms of a giant single TAM. We try to subdivide it into truly accessible TAM number one. How may you expand into a second, third, and fourth TAM over time?

You then get to what is perhaps the most important third point, even more important than team and TAM, which is differentiation. Do you have a real winning edge? Do you have a competitive advantage, a moat that will form around your product or service? Are you definitively better than the alternatives? What’s the proof for that? Do you have traction? Do you have customers? Are you producing revenues? Do you have science? Do you have patents that are issued? Do you have defensible moats that will surround your business so that your cashflows are effectively growing and protected?

That’s where I’ll come back to the beginning and say, for us, it’s about profitability. It’s about growth and profitability. We try to separate hype from reality. We try to quantify the story in a way that translates the story into numbers. How many units will they sell? What margins will they get? How sustainable and defensible is that sales plan, and how scalable is it? How efficiently can they grow their operations and produce bigger profits?

It probably sounds pretty similar to old-fashioned investing in non-innovation sectors. That’s intentional. You shouldn’t be completely wowed by the people and the vision. They are ultimately essential. If you don’t have a great founder and if he or she doesn’t have the right vision, you’re not going to end up with a successful company in an innovative play.

That couldn’t be more important, but it can’t stop there. That’s the difference that we’re trying to take at Bullet Point Network. We’re trying to translate that vision, that excitement, or what you call hype, into cashflows. Those cashflows may happen over time. We can use simple, well-proven things like a discounted cashflow model or think about what multiple to put on revenues that will capture the long-term decade-plus of growth and profitability that you’re paying for now. We do think you’re supposed to do that second step. Don’t just listen to the story. Quantify the cashflows and think about whether what you’re paying for that makes sense.

We’ve talked previously about the importance of integrity as well. As you’ve said previously, it all starts with the integrity of the founders and the management team, and then it flows into everything that you said.

The integrity of the team and the people. People come first, though the governance or the corporate integrity of the business is another important factor. You want to make sure you don’t have complex related party issues or bad governance. You want there to be some integrity around the business, but fundamentally, you do need to have that personal integrity. Great people driving great businesses is what you want to invest in.

Is there a way to quantify integrity and the probability that the founders are going to do what they say they’re going to do?

There are a couple of things in there. One is straight-up integrity, honesty, and delivering what they say they’re going to do. The other is execution capability. Will they have the skill and the ability to, first and foremost, recruit talented people to their team, and then lead and organize or manage the work streams to deliver the execution results? They’re both important. For us, they are two different things. Even though we’re enormous fans of quantifying everything and quantifying stories, there is no way to quantify integrity. I do believe that someone’s integrity and execution track record, the second thing, leaves a footprint. That’s what I often say. I say someone’s life’s work leaves a footprint behind them.

 

The footprint is either a footprint of high integrity or strong execution results in success or otherwise. It’s a little bit like the Supreme Court’s definition of pornography. You’ll know it when you see it. When you see a footprint, when you see a track record of someone who’s been operating with high integrity or someone who’s been operating with great execution results, it’s very clear because people that they’ve worked with or competed against or collaborated with, speak in a certain way about them.

People who have worked with them want to rejoin them and are working with them in their second or third venture. Customers and others in their supply chain or their ecosystem speak very clearly of them. When you’re doing your primary research about customer suppliers and competitors, you’re doing some serious and important work on the integrity and the execution capability of that team.

I like the way you termed it footprint because the word track record gets overused and misinterpreted, especially in the investment world where people say, “What’s your track record?” They’re oftentimes referring to portable numbers in terms of performance results. To me, when you’re investing in innovation, you’re not going to have that track record in many cases. I always say innovation doesn’t come with a track record. That’s why it’s innovative. By definition, if it’s new, it can’t have a track record.

What you described makes a lot of sense because what you can look at as an investor is the footprint. It doesn’t need to be numbers that they generated at a firm. It can be their entire history of development. I tend to overweight folks who have come from humble beginnings and who have had to overcome obstacles because when you ask them, “What’s the hardest thing you ever did?” It wasn’t landing at the deal or getting a job or anything like that. It was, “I had to fight to survive.” To me, if you can do that, the other stuff is easy.

Especially when you’re investing in early-stage companies, there aren’t the numbers there to demonstrate if this person’s been a winner necessarily. There’s still evidence. It’s not just hard numbers. That’s where a lot of folks go wrong. It’s also why a lot of emerging funds have trouble raising capital because institutional investors, as you know very well, want to see a longer-term track record of numbers. They often will look beyond that to say, “What’s this person’s or this team’s footprint of success?”

The word footprint is an intentional choice. If you do your homework on someone, you’ll see they may have run a business unit or they may have run a whole division of a large company. They may have started a prior company or startup that failed. They may have participated in a startup where they were employee number ten that succeeded. Now, this is their opportunity with you to be leading their own business here as this fifth thing that they’ve done in their life.

There will be footprints in each of the prior four things that speak to their integrity, their creativity, and their execution capabilities. If you don’t find out some of the bad things about what happened in those four prior at-bats, you probably haven’t done your homework. In seeking to find out some of those bad things, you will undoubtedly see a clear footprint of someone who’s got high integrity, someone who’s a great execution leader, and also someone who can attract and retain talented people around them.

I tend to look for signals because sometimes, there’s not enough hard evidence. I like veterans, athletes, non-traditional founders, and anybody who’s overcome big challenges. I start with that because those folks are usually incredibly persistent. They’re hardworking. They’re resilient. Resilience, persistence, and coachability are other things. The ability to take feedback and apply it applies to those groups of people.

It’s interesting for me because there’s a huge edge that can be gained as an investor by somehow quantifying or measuring the likelihood of a person or a team being good at what they do, even if you never see any numbers. When I started ARI a couple of years ago, one of the first things I was thinking about was, “How do we quantify a person’s personality and how do those factors relate to the probability of success?”

I haven’t built that machine yet. We’re pretty far along with some aspects of it, but it goes back to the factors that I mentioned. How do you screen for integrity, persistence, work ethic, humility, and coachability? That, to me, is going to be one of the next layers of investing that we haven’t reached yet. It’s like the next frontier. We’ve gotten to the point now with the numbers that anybody can crunch. Some machines are much more powerful than you and I combined, but the machines still don’t know how to measure the intangibles. Ultimately, that’s what will be a big differentiator.

I like your scorecard and your approach. Those people with the characteristics that you summarized as being important signals for you are generally people who sound like I’d love to spend time with. They seem like good people that I’d like to be with, working in the proverbial foxhole or collaborating on a project for all those reasons. There is one thing that I’ll offer you and your audience to consider, and that I’ve learned somewhat the hard way. I’ll use a quick analogy and a quick story.

When I was working in Japan and I was hiring people, I ended up looking back on my record of hiring people. One thing that became clear is I was generally hiring people that spoke very good English. While that’s not a bad thing, that is far from the most important thing when you’re doing business in Japan. I had to course-correct and say, “I’m hiring people because they make me feel good when I’m meeting with them. I need to get to a deeper layer and figure out the key success factors that they need to have in their jobs to be great in Japan.”

Hiring the best people isn’t about who makes you feel good—it’s about who will deliver the results in the long run. Share on X

Back to the question of all those great characteristics you summarized, I love to be with people who share them, there is something about innovators. Innovators often are not the nicest people. They’re not always the most collaborative. Oftentimes, their minds are very closed and they are disruptors in their space, in part, because they’re looking at unobvious things. They are seeing things that are other than obvious to many of us around the system.

It’s that level or that razor’s edge of their solving unobvious problems. They’re doing it with high confidence. They’re not always taking feedback. A lot of times, the feedback that they’re getting is about the status quo and is fully conditioned on a lifetime of living within the status quo. They’re going to change something with a disruptive solution to maybe an unobvious problem.

I learned I couldn’t hire all the good English speakers in Japan. I sometimes don’t want to always hire, partner, or fund people who are completely collaborative, easy to work with, and coachable. Sometimes, you want to hire people who are brilliant, disruptive, and right. That third part is very important because if they’re brilliant, disruptive, and other than right, there are problems. That’s what you have to think through.

Independent Thinking And Innovation

You nailed it with this idea of independent thinking or contrarian thinking in many respects. If you want to do better than average, you can’t think like the average. Sometimes, that’s going to put you at great risk because if you’re wrong and you’re going against the crowd, that’s when you typically put your career at risk at a bigger firm. To be great as a founder, you have to be an independent thinker.

You almost have to be, by definition, what the academics would term overconfident. I don’t mean it in the sense of being cocky. Somebody who looks at the numbers and says, “I just went by the numbers. I would never launch this startup because the probability of success is very low, and it’d probably be better served to go and clip a nice coupon for the next 40 years at a tier-one mature firm.”

You have to be nuts because you have to say, “I’m going to be the one that’s the outlier and I’m going to go solve a problem that no one else has yet solved or hasn’t solved as effectively as I can.” You’re right. I should have put that at the top of my list. It’s critical to have at least the person leading the firm or somebody in that top C-suite, you have to have somebody thinking like that because if you’re thinking like everybody else, you’re going to get results like everybody else.

I added that one particular thing to your excellent list because in the innovation sphere, it’s critical. The other thing that I keep emphasizing is the ability to recruit, retain, and motivate good teams because not everyone on the team should have or will have the same strengths or dispositions. If everybody on the team is an independent disruptor, you may not end up with much success either. You do need some people who are great at the process, some who are great at relationships, some who are great at creativity, and some who are great at diligent execution.

You need a diverse portfolio of people with skills. Getting them to buy into the same goal and objective and then deliver it is a real skill that many investors underestimate when evaluating a founder or a team. How good is the person at recruiting and motivating and getting this diverse skillset group to work together?

To your point, it’s often not the same person who will have those skills. The independent thinker who’s the visionary probably isn’t going to be the best manager of people, generally. It’s funny because we both worked in the capital markets for a long time. At Deutsche Bank, where I was a bond trader, the people who got promoted to lead business units were usually the top producers. The top-producing trader does not make a good manager 95% of the time in my view.

I always thought that was interesting because folks who were producing a lot of revenue, rightfully so, would become promoted, but they were getting promoted into the wrong types of seats because they were a good producer. Being a good trader has nothing to do with managing people or leading at all. That was always something that always stood out to me as a way that most banks are fundamentally mismanaged in my view. When I applied it to the startup world, oftentimes, the person who’s the visionary is not going to be the person who’s the good team builder, the good project manager, or the good day-to-day operator. Sometimes they can be, but it’s rare.

They might also be brilliant when it comes to something on the technology side like AI, which we’ll talk to but they might not have the soft skills. They might not be a good marketer. They might not be somebody who’s able to brand the business and build this visibility. To your point, you have to have a core team that’s got all these key skills around vision, strategy, operations, marketing, finance, and leadership. It’s oftentimes going to be 5 or 7 people. It’s not going to be that one person.

It takes a village to make success, usually.

Let’s shift gears a little bit. I want to talk about AI because you’re doing a lot in the space and it’s incredibly relevant right now. Where do we start? Let’s start at the top. When you hear the word AI or when investors hear AI, what are they thinking, and what’s going on beneath the surface?

The Hype And Reality Of AI

It’s a fascinating time to be talking about AI. I can’t get through a day without having serious conversations about it in most rooms that I’m in. The quick answer to your question is that when investors hear about AI, right now they’re thinking, “I want to buy some. How do I get that?” That’s fueling somewhat of a bubble-like behavior in and around the space of companies that are involved with AI in various ways. That said, it’s a profound, fundamental, long-term change dynamic in the world. Those who use AI effectively and commercially are going to have a major competitive advantage over others.

It’s very worthwhile to understand AI and to embrace and think about it. It’s easy right now. It’s like the same story, different day. It’s easy to be seduced by the excitement, the hype, and the potential of AI. It’s important to try to drill it down to, “What’s the use case? Who’s the user? What’s the ideal customer profile here? What’s the process that’s being 10X improved or materially better because we’re incorporating AI?”

 

It’s also important to actually start using it. As you mentioned, at Bullet Point Network, we have software that does two things. It’s research management and scenario modeling. We’re taking evidence, mapping it to specific assumptions, and putting center points and ranges around those assumptions. We’re building sets, regimes, or combinations of assumptions to build logical sets of cashflows and understand the odds of different financial outcomes for the business and valuation outcomes, looking at both the cashflows and the capital market conditions. That’s what we’re doing.

On the research management port, most research is done by human beings over the course of our lifetimes. They’ve become very focused on trying to make “data-driven decisions.” Those human beings are trying to get their hands on data and analyze it. That’s a good thing. As you pointed out about innovation, founders, and future disruptive technologies, it’s also true generally about the future of most businesses.

The historical data from the past is not going to give you a clear answer for what the future will hold. That’s going to take judgment. It’s often going to take the judgment of a human being. The way I am defining our use case at Bullet Point Network for how to use AI best is let’s try to automate and improve the way in which we quickly source and filter relevant information. Let’s try to create as many summaries of relevant information as we can and put them in an organized, methodical way in front of a human decision-maker. She can make a good decision based on information captured by more than the minutes, hours, or days that she herself could have put into the project.

That process of using AI in a very focused way, writing specific prompts, using very specific vectors to subdivide the information, and focusing on the sources or the knowledge pile you’re using for the AI prompts is very critical. We’re focused on building workflow automation so that you can improve that human research process in a 10X fashion by having AI-sourced information, as well as human-sourced information.

One of the big challenges is that most people who are enormously excited about AI aren’t doing anything with it other than maybe a casual thing on their phone with their friends that’s cool and fun. I’ve enjoyed doing it too. We’ve got to get below that superficial level of a cool toy, doing cool tricks to what are the real commercial use cases. As we do more and more of that in all of our businesses, in all businesses around the world, you’re going to see 2 or 3 common things happen. First, people are going to be amazed that it’s possible to do something, and then they’re going to be disappointed that it’s not possible to do everything. They’re going to be focused on, “How can I do the most with it practically and pragmatically?”

Finally, they’re going to get to the point that we always start and finish with, “How is this going to translate into cashflows? What are the cases? What are the use cases? Who’s going to pay for them? What are the units? P times Q, how many of each unit are you going to get? Why is that going to be materially better in terms of either improving revenues or reducing costs that will lead to bottom-line profitability expansion?”

I’m almost like Jekyll and Hyde on the topic. I couldn’t be more excited about the long-term potential to use it properly, but I also couldn’t be more concerned about the fact that most people are not using it and they, therefore, haven’t gone through those phases of learning and they’re excited beyond belief. As an investor, that’s a great way to separate yourself from your money because you’re not being careful and thorough about how’s this going to translate into cashflows. What am I paying for here? Am I paying for two decades of success that looks exactly, like Microsoft or Tesla or am I paying for something that I have reasonable odds of making money off of reasonable commercial milestones that this investment could produce in the next 3 to 5 years?

It’s a fascinating time. Anything that’s got an AI orientation is flying off the shelves or investors want to buy with both hands. Most people are not using it much. The arms producers, the people selling the hardware, the chips, and the picks and shovels to the gold miners of AI are the first wave of winners. That’s well understood.

The commercial practices of using generative AI are what we’re talking about now. We’re not talking about the older versions of AI that have been well used for pattern recognition marketing for years, but generative AI, the use cases are still early days. People are quite susceptible to the story right now and they are going to need to quantify the numbers to make sure that they make good decisions here.

You nailed it on many fronts and I agree with you on the Jekyll and Hyde situation. In the longer term, it’s hard to not be incredibly excited about AI. It’s going to fundamentally change the way we live. That’s why I named my company ARI. When I first started thinking of names, I thought, “In the future, we’re going to have to differentiate what’s not AI because everything’s going to be AI.” Years ago, you might have had 5% or 10% of interactions commercially, touching machine learning AI. People didn’t realize that. I remember as early as 2015 or 2016, I was meeting with senior folks at Bloomberg. They had a meeting at Fenway Park and they invited all the top traders to come out and give their feedback, which was cool.

We got to hit some baseballs and whatnot in Fenway. What was interesting to me, the big takeaway, was I asked them what percentage or they had mentioned that up to 10% of the articles that were on Bloomberg were being generated by machines. I thought, “That’s pretty interesting.” It turned out that it was 10% of the articles related to equities and stocks. I said, “What are you guys doing on the fixed-income side?” They said, “We haven’t done that yet. That’s like coming up next.” I thought, “This is a huge opportunity.”

I went back and built my own newsletter. I sent out a newsletter back in the day that thousands of traders would read, but I built it so that it was automated. It would take in all the data via API and then the text would be generated based on the numbers. If S&P 500 futures were up, it would automatically pull in the text saying, “Futures are up today and this is how they’re trading over the last five days and in the last month.” I automated all this stuff. It took a while because there was a lot of trial and error and I got to the point where I had a 5 or 10-page newsletter that was predominantly generated by machine. I didn’t have to do anything.

Unlocking AI’s Potential For Business Growth

That’s a great story and I’m sure you were ahead of your time and successful in that realm at that time. It is applicable now to what I’m looking for in all these AI businesses and AI-enabled businesses. Much like other forms of technology, AI is in every business. It’s going to be in every sector, every segment. The winning users of AI in their respective sectors are likely to have a big competitive advantage over those who don’t play well or succeed in embracing it. To your point about your newsletter, what is critical, go back to basics. Who is the customer? What is the process that’s being massively improved here? How much does that improvement of that process generate in terms of economic potential? What cost does it save? It might be time, a lot of human time.

If it’s done by Bullet Point Network with tons of effort around building the prompts, focusing the knowledge piles, using the vectors, and mapping the evidence, AI can be an enormous productivity enhancer. It’s almost as if you’re having many extra people because the work that used to take a week can now take an hour.

Success in AI means translating productivity gains into real cash flows. That’s how you win. Share on X

If you think about that, if you were pretty productive with your other hours and you saved yourself a lot of time and synthesized it and you didn’t imagine things that were not realistic, if you didn’t imagine that it was going to “give” you the answer, but it was going to help your productivity improve so that what used to take a week now takes an hour. Now you have the rest of the week to think critically about what you learned and to maybe go and explore that issue from a different perspective and then try to quantify it in a useful way. If you make good use of the extra time you’ve saved from that productivity, it can be very valuable.

In other businesses, we’re looking at defense tech businesses. We’re looking at consumer tech businesses right now. We’re looking at some businesses that make components in the electronic vehicle space. We’re obviously looking at a lot of medical devices and biotech, all of which are using AI in very focused ways. We like to understand how this AI is being developed, implemented, tested, and used. Ultimately, is there a buyer for the products you’re producing and coming out with? We like to translate everything into cashflows. That’s what is ultimately going to be the trick.

There’s so much to dig into. One thing I wanted to say is this idea of necessity being the mother of invention. In other words, when I look for companies to fund, I’m looking for companies that are solving a problem. The reason I automated my newsletter was not because I was trying to do something slick. I was sick of writing a newsletter every morning by hand. I thought, “How can I save myself two hours in the morning so I don’t have to wake up at 4:00 AM?”

From being at Goldman for almost two decades, you know how it is. You get in the morning as a salesperson and you’re updating all your clients on what happened overnight, what they missed, what happened in Asia, how you think the market’s going to open, what your best trades are for the day, what axes you have to pitch them, etc.

I thought, “Every single salesperson was getting on the desk writing these things. That is incredibly inefficient because they’re all writing something, wasting an hour of their morning when they could be doing a higher-level activity. I’ll build this newsletter and then I’ll give it to my sales force, too.” I’ll tell you, Mike, I had the entire sales force sending it out to every single one of their clients. That’s how I went from being like a junior schmuck to being relevant almost overnight.

All of a sudden, people were like, “Zack is saving us hours each day.” The clients were going, “If I want the best insight and I want it fast, I know where to go.” It goes back to this idea of what AI can do. What I had to do manually and took me months to build with that newsletter, now, somebody could probably do it in less than a week or maybe even faster if they know how to harness AI. It’ll probably be better than what I was doing back then. Mine was like the Model T and now you can have a Mustang in terms of how much things have evolved in the last few years.

The last thing I’ll say, and I know you want to transition to a final topic, is that the thing about the analogy that I used earlier is that it’s almost as if we can all have more people working for us instantly. Instead of doing it yourself, you now have almost a handful of people working for you. They’re all AIs. The thing you might want to ask yourself, which we ask ourselves a lot in terms of building these props, focusing on the right knowledge piles or sources.

Ultimately, utilizing the output of the AI in a hybrid human process is how happy would you be if you hired 5 people, and 2 of them lied to you most of the time or lied to you a third of the time. They gave you false information, confusing information, or hallucinations, as it’s called in the AI world. That is something that people have to be very mindful of. You’re getting credible information, sounds very articulate but sometimes is wrong. You need processes to protect yourself against, “I’ve hired five people and 40% of the information they’re giving me is lies.” You have to be careful about that. You wouldn’t probably want to be with those five people for very long.

I have a good friend who I’ve known since I was a kid. He’s a great guy, but he’s a pathological liar about little things. It’s the same thing. It’s like AI in the sense that you have to know what’s true and what’s not and also verify everything, especially before you act on it. That’s where we’re headed with AI. There’s going to be a real opportunity for companies to figure out how to validate and verify what various AI processes are producing. I don’t know if you’ve seen companies like that already. I’m sure there’s some out there, but I haven’t found a clear winner yet.

 

Important Links

• Zack Ellison on LinkedIn
• Applied Real Intelligence (A.R.I.)
• 7 in 7 Show with Zack Ellison on Apple
• 7 in 7 Show with Zack Ellison on Spotify
• 7 in 7 Show with Zack Ellison on YouTube
• 7 in 7 Show with Zack Ellison on Amazon Music
• Mike Ryan on LinkedIn
• Bullet Point Network
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About Mike Ryan

Mike Ryan is the Co-Founder and CEO of Bullet Point Network. An active private investor, entrepreneur, and board member, Mike has almost 30 years of investment, capital markets, and management experience.

In addition to founding and overseeing BPN, Mike served as Board Chair of the Alpha Partners Technology Merger Corp and has been the CIO of MDR Capital, his family office, since 2009. Before founding Bullet Point Network, Mike served as Head of Public Equity and Absolute Return at the Harvard endowment, Head of Global Securities (overseeing equities, fixed income, currencies & commodities) at Credit Suisse, and Partner and Head of Global Equity Products at Goldman Sachs, where he spent the first 18 years of his career.

Mike has served as a director, committee chair, and board chair on numerous corporate and non-profit boards and is a venture partner or advisor to several growth equity and credit funds. He graduated summa cum laude from Yale University with a B.A. in economics and was an Academic All-American in basketball.