Things I wish someone had told me before I started angel investing

The company I was an early employee of (that ended up being a "unicorn") was not a cool kid, and we certainly were begging people to invest both at the angel stage and (especially) the series A stage. And those people got a really really good return on their money.

This isn't to say there aren't valuable signals perhaps involving "cool kids" status, but there are a lot of diamonds in the rough.

> I figured it would be more fun to be the beggee than the beggor for a change, and I was right about that.

As a much smaller time angel investor myself than the author, I'm still the beggor. You are only the beggee if you are writing 25k+ checks (and more like 50k-100k to really be the beggee). If you are writing 5k or 10k checks, you are going to be begging people to take your money, cool kids or not cool kids. So if you are looking to get into angel investing today without allocating 6-figure amounts to your hobby, I wouldn't advise doing it for ego reasons :)

I really do question this. The "problem of induction"[1] comes into play when you start talking about pattern matching and learning from "experience". That is, there's no guarantee that the future will look like the past.

Before Zuckerberg was Zuckerberg, I wonder how many people would have said "Hey, I recognize in this kid the innate capacity to be an NBT"? Of course they got funded, but I believe most of it was after they already had demonstrable traction.

On that note, one of the things that makes fund-raising such a drag, is that so many angels (at least in this area) want to see "traction" before investing. Even though, typically, you would thing that angels are investing at such an early stage that nobody would really have traction yet. Maybe it's just that the angels here on the East Coast are more risk averse.

[1]: https://plato.stanford.edu/entries/induction-problem/

However, something that I think the essay modestly overlooks is the non-financial elements. The investors made a huge difference in my life & that of the others that worked for FathomDB. I like to think that we moved the industry forward a little bit in terms of thinking about modular services (vs a monolithic platform-as-a-service) although it turned out that the spoils went mostly to the cloud vendors. Many of the ideas developed live on in open-source today.

Of course, this all serves Ron's point in that it doesn't make for a good investment. But that doesn't mean that no good came of it - and it makes me want to work harder next time so that it is both a good outcome and a good investment.

So: thank you to Ron and all our investors. It is no accident that you are called angels.

If you want to get into the angel game in 2017, and you want to do it to make money, then I'd sincerely advise you to go take out $5-10k for a weekend in Vegas, and try to get really good at a game of complete chance, like roulette.

"Good" at roulette, you're thinking? What can that possibly mean?

It means having a large bankroll and knowing your tolerance for burning through it. It means understanding how to pace yourself, so that you're not blowing through your bankroll in the span of a few minutes. It means getting the itch out of your system, if, indeed, this is merely an itch.

Can't afford to fly to Vegas and blow 10 grand in a weekend? Don't get into angel investing. You can't afford it. I say this not as a snobby rich asshole, but rather, as the sort of nouveau-riche asshole who lost quite a bit of money many years back, doing exactly what the author did, and losing money I learned in retrospect I didn't really want to lose.

I still make the occasional investment, but as part of a group. By and large, those investments go to founders we've worked with before, or who come highly regarded. We invest super early, we eat a fuckton of risk, and we expect to lose 99.999% of the time. We're too small-time to play the game any other way at the moment.

Angel investing is about bankroll and access, and if you're wondering whether you've got the right access, you don't. So you're left with bankroll. Have fun, and try to get lucky if you can help it. :)

The #1 thing a startup can do to survive is to be as stingy as possible with their capital.

"And this is how I made 42 investments in my first 3 years. All are now bust, and I am out 1.4 million dollars"

Obviously not fun to tell the world how much money you lost, but it would help to add color to the people behind the VCs, that developers love to see as the frenemy (terrible people out to screw you, but man their money is nice sometimes).

A VC once told me that there were "good angels and bad angels" Too many bad ones and he wouldn't invest. A couple specific bad ones and he wouldn't invest. To that, there are also good angels that will make introductions, spend time coaching, and really help beyond what I'd call a "hobby." It seems like there are good people out there with money and knowledge and they really want to help out others in an angelic sort of way knowing full well they will likely lose their investment.

And it is the same for stocks, many people think they will make money by investing in a specific company because their logic says it is good idea.

Investment is a job, and to win you need experience

Is he implying some sort of unethical behavior as the second way?

That's a pretty specious statement. I don't know how he came up with that; it certainly doesn't match with a lot of reality.

Any guesses on the second way?

The best I could think of was: find dumb investors to pump it full of money and hype it. Then rely on all the hype to get it sold.

I'm hoping for a less cynical answer!

I'm somewhat biased when it comes to angels because most of the experiences I heard (http://etl.stanford.edu/) were almost always homeruns. Sure there's the down in the gutter claims every investor tries to sob about where they lose money but let's be honest wouldn't it be great if someone gave a talk and said how much they lost (and how much they're continuing to lose) by attempting to get rich quick.

So far bootstrapping appears to best way of weeding out the shitty angels who haven't been in the game for a minute.....it's a pleasure to not deal with someone wanting to give you a check while telling you what their expectations are for YOUR business not their 10k+ check.

Anyone figured this out?

Inversion essentially means think hard about: "What factors can cause my venture to fail?, How to avoid those factors?"

This sounds simple but it could be a very powerful idea. https://www.farnamstreetblog.com/2013/10/inversion/

  It's 222-2222
  I gotta answering machine that can talk to you

I'd love to hear from other angel investors with (perhaps) different experiences and opinions.

Can anyone give me such examples?? I am curious.

Much better news: I do believe that it's fairly obvious that there are good solutions to the most important problem mentioned in the OP.

First a remark on scope: I'm talking about information technology (IT) startups based heavily on Moore's law, the Internet, other related hardware, available infrastructure software, etc., and I'm not talking about bio-medical technology which I suspect is quite different.

Second, a remark on methodology: When the OP says "almost certainly" and similar statements about probability, sure, (A) in practice he might be quite correct but (B), still the statement is nearly always just irrelevant.

Why irrelevant? Because what matters is not the probability, say, estimated across all or nearly all the population, or all of business, or all of startups, or even all of IT startups. Instead, what is important, really crucial, really close to sufficient for accurate investment decision making, is the conditional probability given what else we know. When the probability is quite low, still the conditional probability -- of success or failure -- given suitable additional events, can be quite high, thus, giving accurate decision making. So, net, what's key is not the probability but what else is known so that the conditional probability of the event we are trying to evaluate, project success or failure, given what else we know is quite high.

So, back to the OP. We can start with the statement:

> The absolute minimum to play the game even once is about $5-10k, and if that's all you have then you will almost certainly lose it.

Here for the "almost certainly" to be true needs to depend on what else is known. Sure, if not much more is known, then "almost certainly lose it" is correct. But with enough more known, the first investment can still likely be a big success.

The big, huge point, first investment or 101, is what else is known.

> There is a small cadre of people who actually have what it takes to successfully build an NBT, and experienced investors are pretty good at recognizing them.

I agree with the first but not with the second. From all I can see, there is hardly a single IT investor in the US who knows more than even dip squat about how to evaluate an IT investment. E.g., commonly the investors were history or economics majors and got MBA degrees. Since I've been a prof in an MBA program, I have to conclude that a history or economics major with an MBA has no start at all evaluating IT projects.

Here is huge point:

We can outline a simple recipe in just three steps for success as an IT startup:

(1) Find a problem where the first good or a much better solution will be enough nearly to guarantee a great business, e.g., the next big thing.

(2) For the first good or much better solution, exploit IT. Also exploit original research in high quality, at least partly original, pure/applied mathematics. Why math? Because the IT solution will be manipulating data; all data manipulations are necessarily mathematically something; for more powerful manipulations for more valuable results, by far the best approach is to proceed mathematically, right, typically with original work based on some advanced pure/applied math prerequisites.

(3) Write the corresponding software, get publicity, go live, get users/customers, get revenue, and grow the revenue to a significant business.

So, right: Step (2) is a bottleneck: The fraction of IT entrepreneurs who can do the math research is tiny. The fraction of startup investors who could do an evaluation of that research or even competently direct such an evaluation is so small as to be essentially zero.

So, net, the investors in IT are condemned to miss the power of step (2) and, thus, flounder around in nearly hopeless mud wrestling in a swamp of disasters. And, net, that's much of why angel investors lose money.

So, the main problem in the OP was losing money on IT projects. The main solution, as both an investor and an entrepreneur, is to proceed as in steps (1)-(3).

For IT venture capitalists (VCs), they can't use step (2) either, e.g., can't do such work, can't evaluate such work, and can't even competently direct evaluations of such work, but they have a partial solution: Likely enforced by their LPs, in evaluating projects they concentrate on cases of traction and want it to be significantly high and growing rapidly.

So, with this traction criterion, and some additional judgment and luck, some of the VCs get good return on investment (RoI), but they are condemned to miss out on step (2).

So, what is the power of step (2)? As we will see right away, clearly it's fantastic: Clearly with step (2) we can do world changing projects relatively quickly with relatively low risk.

The easiest examples to see of the power of step (2) are from the US DoD for US national security. Some of the best examples are the Manhattan Project, the SR-71, GPS, the M1A1 tank, and laser guided rockets and bombs, all relatively low risk projects with world changing results. Each of these projects, and many more, was heavily dependent on step (2) and met a military version of steps (1) and (3).

More generally, lots of people and parts of our society are quite good at evaluating work such as in step (2) and proposals for such work, just on paper. We can commonly find such people as professors in our best research universities and editors of leading journals of original research in the more mathematical fields.

I started some risky projects, e.g., an applied math Ph.D. from one of the world's best research universities. From some good history, only about one in 15 entering students successfully completes such a program. The completion rate of applied math Ph.D. programs makes the Navy Seals and the Army Rangers look like fuzzy, bunny play time. With much of my Ph.D. program at risk, I took on a research project. Two weeks later I had a good solution, with some surprising results, quite publishable. Later I did publish in a good journal. I could have used that for my Ph.D. research, but I had another project I'd pursued independently in my first summer -- did the original research then, in six weeks. The rest of that work was routine and my dissertation. While working part time, the Navy wanted an evaluation of the survivability of the US SSBN fleet under a special scenario of global nuclear war limited to sea, all in two weeks. I did the original applied math and computing, passed a severe technical review, and was done in the two weeks. Later I took on a project to improve on some of our work in AI for detection of problems never seen before in server farms and networks. In two days I had the main ideas, and a few weeks later I had prototype software, nice results on both real and simulated data, and a paper that was publishable -- and was published. My work made the AI work look silly; it was. Once in a software house, we were in a competitive bidding situation. I looked at what the engineers wanted and saw some flaws. Mostly on my own, I took out a week, got good on the J. Tukey work in power spectral estimation, wrote some software, and showed the engineers how to measure power spectra and how to generate stochastic process sample paths with that power spectrum. As a result, my company won sole source on the contract. So, before I did these projects, they all were risky, but I completed all of them without difficulty.

Lesson: Under some circumstances, it's possible to complete such risky projects, given the circumstances, with low risk.

But IT VCs can't evaluate the risk before the projects are attacked or even evaluate the results after the projects are successfully done. So IT VCs fall back on traction.

I confess: It appears that the IT VCs are not missing out on a lot of really successful projects. Well, there aren't many IT startups following steps (1)-(3).

So, for IT success, just borrow from what the US military has done with steps (1)-(3).

The problem and the opportunity is that nearly no IT entrepreneurs and nearly no IT investors are able to work effectively with steps (1)-(3), especially with step (2).

The IT VCs have another problem: The know that for the next big thing -- Microsoft, Apple, Cisco, Google, Facebook -- they are looking for something exceptional. And they know that those for examples have very little significant in common. Still the IT VCs look for patterns for hot topics at the present or recent past. That's no way to find the desired exceptional projects. E.g., when the US DoD wanted the Manhattan Project, they didn't go to the best bomb designers of the previous 20 years; doing so would not have resulted in the two atomic bombs that ended WWII. Instead, the US DoD listened to Einstein, Szilard, Wigner, Fermi, Teller, etc., none of whom had any experience in bomb design.

For me, the most important thing that Ron conveys is that being an entrepreneur is an incredibly foolish thing to do. Silicon Valley created myths of passionate geeks who worked in their mom's garages and went on to make billions. Who doesn't want that?

But the reality of Silicon Valley today is that because of these myths, most people work their twenties away for a chance to buy a lottery ticket...

Unless it's in your background and in your DNA, it seems that angel investing will end in tears.

What I take from this is that this person doesn't have a grasp if high school math or is not being honest.

Also if you listen closely to a lot of investors they'll basically tell you their metric is "can I sell this to a greater fool?". This is why there is so much investment in 'hot' areas when, in reality, those are the areas to stay away from as the unicorn shares are likely already over-priced.

plenty of good entrepreneurs have great angel investing track records doing it part time (Elad Gil, David Sacks, Aaron Levie)

>To make a product that fills a heretofore unmet market need, and to do it better, faster, and cheaper than the competition.

This is an insane sentence. Let's make it only slightly more insane to throw it into starker relief:

>To make a product that fills a heretofore unmet market need that nobody has expressed or even thought about until the company announces it, and to do it absolutely perfectly, instantly without any development time, and make it free for the consumer, while getting money from a sustainable high-margin source and having a proprietary moat that makes it impossible for any other market players to enter even a similar market. Also I'll add that the company must have such strong network effect that the utility of any competitor's product is negative (people would regret getting it even for free) unless the competitor is able to get at least 98% market share.

That's pretty insane, and if you re-read what I quoted you will see it's the same kind of insanity.

Why do people even write stuff like this.

-

EDIT:

Downvoters don't understand my objection. I'm not going to edit this comment. If you don't get it, you don't get it. This investor literally named "good, fast, cheap" (except as: better, faster, cheaper) as three of four requirements that must be met. (The fourth named requirement being "heretofore unmet".) You cannot get more insane than this except in magical la-la land where there are no trade-offs of any kind. It's absurd.