What Horses, Watches, And Bookstores Can Teach Us About Why Automation Won’t Kill Jobs

A few months ago I spoke on a panel, and I was asked a question that I am always asked about AI and automation – will it kill jobs? And if so, what do we do? The answer I gave surprised many people who said they had never heard an answer like this before so I thought I would write about it here.

Here’s a heuristic that will guide the way – things we no longer need don’t always go away. Sometimes they die briefly, but then are resurrected as status symbols.

Bookstores

When I was working on my MBA in 1998, my business school professors were freaking out because they had no idea what business was going to look like when the Internet really took hold. I had a professor tell us that in 5 years all brick and mortar retail would be dead, and that we would only shop online. Obviously they were very wrong. If you take bookstores as an example, you might be surprised that while Amazon initially put a big dent in the bookstore industry, there are now more bookstores in the U.S. than there were before Amazon. The algorithms of Amazon are super efficient but, they don’t provide the serendipity, the community, or the curation we sometimes desire.

Watches

I remember playing golf with a friend in 2007 who said “wow, you still wear a watch?” He told me he had no need for one because he had a cellphone and it always had the time. The cellphone was, for a while, definitely killing the wristwatch, but much like independent bookstores, it appears that watches are starting to come back as more of a status symbol than ever before.

Horses

Two hundred fifty years ago, everyone owned a horse. That’s how you got somewhere. When cars came around, it didn’t kill off the horse industry altogether. Instead, horses became expensive status symbols. To own a racehorse, or to participate in equestrian events, it it’s own culture and community filled with mostly wealthy people.

So what does all of this tell us about AI, automation, and jobs?

I believe that as jobs get automated away, employing people to do a thing, instead of robots, will become a status symbol. Humans are always competing with each other for status, and that won’t stop. Bookstores, watches, and horses didn’t go away, although they did change in different ways.

But, some things do go away forever. For example, no one washes clothes by hand now that washing machines were invented. How do you explain that?

My theory is that there are two kinds of jobs. There are jobs machines are better at, and will always be better at. And then there are jobs that really can’t be done much better, but could be done faster or more efficiently. by a machine. The latter category jobs will emerge as a status symbol if you have a human still do it. Those jobs will pay well because they now become “luxury services.”

If I think forward and see some new jobs emerging as a result of AI automation (data curator, data annotator, model trainer, AI designer, etc), and see some jobs becoming status symbols as mentioned above, and also factor in that hybrid human-AI partnerships will upskill some low skilled workers and enable them to keep working, I’m actually pretty bullish that at least for the next few decades, we don’t have a problem with automating jobs away. There will be economic upheaval, and some industries will be like the clothes washing industry and suffer pretty greatly, but, at the macro level I believe the story will actually be all right.

The Half Court Ventures Story: What I’ve Learned From 4 Years of Angel Investing

Backupify was acquired in December of 2014. In June of 2015 I made my first angel investment. Along the way, I started a fund with my friend Todd Earwood, and learned a lot about investing. This post chronicles that path.

Deciding To Angel Invest

The first thing I did post exit was talk to lots of smart people about angel investing. If you do this in Boston, where I am based, most people say this… “don’t do it, you will lose all your money.” Time and time again I heard a story where, someone made a bit of cash, then they spent a year studying angel investing, looking at deals, figuring out their strategy, and then pulled the trigger, doing 4 deals in their first year of investing. Then they waited and watched while 2 went out of business, 1 became the walking dead, and they got squashed out in a recap of the other one. Almost everyone tried to talk me out of it. “You’ve worked too hard for this money, don’t lose it” was a refrain I heard many times.

But. I was 38 years old. My theory was that I could lose all of it, and that would be entirely ok. I don’t have a lavish lifestyle, and I don’t really want one. (People are always surprised I drive a 2009 toyota tacoma stick shift). My strategy was to work and invest as aggressively as if I had never made any money at all, figuring that even if I lost everything, I would learn a lot, increasing my ability to hopefully make it back.

I was lucky that 3 of the best angel investors in the world were investors in Backupify: Jason Calacanis, Chris Sacca, and Dharmesh Shah. I talked with all 3 of them about angel investing, and they all gave me advice that was very different than what other people advised. All 3 said that to be successful, you have to do a lot of deals. 20 was the number they threw out. I was told that if the first 15 bombed, still do the last 5. Do 20 deals.

The second major piece of advice was to brand myself in a way that I would get good deal flow. One reason many angel investors fail is that they don’t see the best deal flow, so all they see is second and third tier investment opportunities. This piece of advice was part of what inspired me to start my AI newsletter. It has been, and continues to be, a very good source of deal flow.

The third piece of advice was to focus on size of possible outcome over likelihood of possible outcome. This kind of ties back into Nassim Taleb’s idea of playing games that favor convexity. If you do it right, your hit rate can be worse than average but your hits payout disproportionately, so you end up fine. More on this later.

Setting Up Half Court Ventures

The idea to setup a venture fund wasn’t mine. Some of my original angel investors in Backupify were based in Louisville, KY, where I am from, and they reached out to ask if I was going to angel invest. When I said yes, they said “you will see deals in Boston, NYC, and San Fran that we will never see here, please throw some of our money into them along with yours.” This was easier to do with a fund structure, so, we created Half Court Ventures. It turned out to be a $3M fund, but I was the largest LP. As the fund was getting setup, I realized I wasn’t going to do this full time and may need some help, so I asked my friend Todd Earwood if he would be a general partner in the fund as well. Todd and I have done a bunch of business things together over the years, are close personal friends, and have made and lost money together on various things, so there is a lot of mutual trust. Plus, our skill sets are very complementary. (You can see Todd’s presentation here on telling AI stories.)

We chose the name Half Court Ventures because we both love basketball, and Full Court Ventures was taken. But over time, we evolved the story to say that it references a half court shot, which is difficult to make, but still possible, and more likely with practice – similar to startups. When we tell you that story though, you will know now that it’s a myth. The original naming story is that we were just not that thoughtful about it.

Half Court Fund 1 made 48 investments in 3.5 years, in mostly AI companies. It did so well (on paper) that the LPs all wanted to come back and do a second fund, so we just did the first close on Half Court 2.

Deal Flow, Evaluation, And Investing

All in all, I’ve made 68 early stage investments as of the day I’m writing this post. 55 of them are through Half Court, via fund 1, fund 2, and our Angel List syndicate. The other 13 were personal, either in friends, companies founded by people who worked for me, or weird non-venture style stuff. Half Court stayed focused on AI.

Angel and Seed stage investing is nerve wracking. Companies are a rocket ship one year and flat the next. They are dying, then suddenly raise massive rounds. We’ve seen companies get large markups, then crash, and we’ve seen entrepreneurs pull magic out of a company on the verge of death. The only thing that is consistent is that whatever the entrepreneur tells you will happen, will most definitely not happen.

At these stages, there aren’t many metrics to use to judge the company, and even if they have some metrics, they are usually meaningless. I don’t do much competitive diligence, because I’m not sure it matters at this stage. Smart entrepreneurs will navigate those dynamics. Mostly I look at teams and markets. Is the market big? Will the team figure it out? If what they are telling me doesn’t work out (because it often won’t) are there tangential spaces for them to move?

We tend to evaluate deals based on what I’ve learned from reading Nassim Taleb’s work on convexity. I know all the things that can go wrong in an early stage company. I’m not trying to mitigate those risks. I’m trying to figure out that in the unlikely scenario that everything goes right, how big can this be?

At the angel/seed stage, pretty much every idea looks kinda brilliant and kinda dumb. I could craft a story for why it will succeed or fail. So, I try not to waste time figuring out what could go wrong. That said, I also tend to stick to things that I already know a bit about, which helps.

Our deals come from a bunch of places, but the best sources tend to be my newsletter, and existing portfolio CEOs. One of the things I’ve been focused on, and am very passionate about (and will write about more on this blog) is AI hardware. Half Court has already invested in Mythic, Rain, and Koniku. I think investing is a lot about finding the trend everyone else is missing, and AI hardware is one of those trends.

Lessons Learned

It’s really hard to know, 4 years in, how much we’ve been lucky and how much we’ve been good. Ask me in a decade and maybe I will have a better idea. At the moment though, Half Court 1 is doing really well, despite the fact that we made a ton of mistakes.

  • We were easily taken in by charismatic entrepreneurs who had no grit, and easily gave up when things got tough.
  • We took on (and continue to take on) syndicate risk, meaning we’ve done deals when the company has no lead. We’ve been the very first check into 9 deals (usually just $50K) and almost every deal we have done has been pre-revenue, many pre-product. The results have been mixed. Some entrepreneurs don’t close their rounds. But others we get into because we’ve already committed, and the lead shuts out new angels.
  • We’ve done deals that would have been good but the valuation was bad.
  • We didn’t reserve much capital for pro ratas, and we missed chances to invest more in some of our best deals.
  • We’ve been burned by SAFEs (still hate them) when entrepreneurs have a walking dead company and the investors have no way to even force a conversation about what’s next, or when someone doesn’t honor the original spirit of the SAFE. It’s just this no man’s land of legal rights. Convertible notes or equity make a deal waaaay more attractive to us.
  • Your handful of big winners really do drive returns more than anything. Everyone says this and my experience is the same.
  • Some entrepreneurs just make things work. I was the very first angel into Bulletin.co, and it was entirely based on the gumption and grit of Alana and Ali. They have been through multiple ideas and business models to get to their current success. Finding these entrepreneurs is hard. Always invest in them when you can.
  • Sometimes I invest in someone I really like even when I hate their idea. I think of it as getting to know them so that even if this company fails, I’ll get a shot at their next one.

A side note about big exits – it seems like their really should be a different way. There are tons of good tech ideas that aren’t venture scale, and could be nice businesses sold for $25M. But when you do a $10M cap SAFE on a slide deck, there isn’t an opportunity for an investor to make much money on that $25M exit. I don’t understand why so many companies get funded on roughly the same terms despite being vastly different businesses. Why aren’t there more $1M on $3Ms? Or $2M on $2M pre? If you did a 2 on 2 and got to cash flow breakeven on that, sold for $25M in 5 years, the founders would each make $6M (assuming 2 co-founders), and investors could get a 6x. Everybody wins. No one is financing that model.

How Do You Have Time To Do This?

The biggest question I get is how I have time to do this. I run Talla full time, and I have two school aged kids, and I write posts like this. It’s actually not that hard because I don’t have many other hobbies. I watch zero television except for college basketball season, and I don’t even have a Netflix account. So instead of “netflix and chill” I do the “read decks and chill” on a friday night. And I try to involve my kids in it a bit. They’ve met a lot of the entrepreneurs I’ve invested in, been to dinners with some of them, and I hold a quarterly AI poker night at my house that 15-20 of them will usually attend. I let my kids hang out at those because I think entrepreneurs are good role models for them.

Also, I believe it helps me at Talla. We are in an early market, so seeing the insides of so many other AI companies gives me ideas, and makes me smarter about the market. I will say my investors are split on it. About half would tell you it’s made me a smarter CEO, and about half would say it sucks time away from Talla and is a distraction. Boston is more of a do-one-thing-only tech community so, my Boston investors tend to be a little more on the “this is a distraction” side than my Silicon Valley investors.

And finally, when you get a process down, and stick to areas you know, it can become more efficient than you think.

In Closing

I think early stage investing is incredibly fun and rewarding. I actually think growth stage investing would be too, but, I can’t really play at that level yet.

If you are an AI entrepreneur, I hope you will reach out and send me a deck. If you are an investor and want to collaborate on deals, please reach out as well.

If you are new to angel investing, and want to chat, I’m always happy to share my experiences.

Welcome To Coconut Headsets

I’ve been blogging since 2003, when I wrote the Businesspundit blog, which I sold in 2008. Then I moved to coconutheadsets.com, but in 2014 moved to Medium, feeling like it provided better distribution for my thoughts. I don’t really like it anymore so I’m moving back here as my primary source of writings. I’m also the same Rob May that writes the Inside AI newsletter. I run Talla as CEO, and am a partner at Half Court Ventures, the fund I started with Todd Earwood. We are the most active AI seed investors on the East Coast.

If you want to know what Coconut Headsets means, read up on cargo cults. I chose the name because in startups and investing, there are many erroneous ideas out there that follow a similar vein. I try to break those mindsets. I hope you can find something on this blog you disagree with, that challenges your thinking. Otherwise, I haven’t done my job.