On Founding & Investing

CVIII

[Infinite Regress, Beating the Benchmark, Generating Alpha, Estimating Truth, Wax in Your Ears, Investing in Investing]

Thesis: Being a good founder requires a lot of the same things as being a good investor.

[Infinite Regress]

I started investing in the stock market in high school and enjoyed it enough to start a hedge fund in college.

I still consider myself to be an investor; asides from a personal portfolio that has done quite well over the last five years, founding a software company is more or less the act of building the company I would like to invest in—financially prudent, customer centric, premium product, aggressive reinvestment in valuable technology.

And, funny enough, I also like investing in companies where leadership views themselves as investors (a fun bit of Sunday morning recursion).

But what is a a good investor? A good investor is more or less someone who can make decisions that get better results than expected.

It should go without saying that I want BirdDog to get better results than should be expected given the relevant variables:

• No funding

• No experience building a software company

• Ultra Competitive space

• Neither founder is an "educated" engineers

• No prior experience working in the roles we are selling to

When you put it like that, we really are already doing better than could be reasonably expected.

The question, though, is what tools from the investing world will help us do significantly better than expected?

The answer is really not so complicated - I think it’s as simple as a little bit of good analysis & overcoming psychological biases.

[Beating The Benchmark]

Two of my favorite investors of all time are Nick Sleep & Qais Zakaria. They ran Nomad Investment Partnership and returned 921% over 13 years that included the Great Recession. They wrote a collection of very good letters that I would highly recommend reading if you want to understand more about investing in companies.

How good is a 921% return over 13 years?

Well, in financial markets, you don't actually care about just the return, you care about how much more you returned than another investment that had a similar risk profile. In that context, their results were just as impressive, if not more - they beat the MSCI World Index, their 'benchmark', by about 5x.

$1 in their fund from inception to close would have yielded $10.21, while $1 in the MSCI World Index would have 'only' become $2.17. (I say 'only', because for a lot of people, doubling your investment in 13 years is still very healthy.)

Broadly, you refer to your excess over what you were "supposed" to get as Alpha. By our definition of a good investor being one who can make decisions that get better results than expected, if you can consistently generate Alpha, you are a good investor.

[Generating Alpha]

Sounds simple enough, right? If all we do is generate alpha, then by our functional definition, we're good investors!

But, how does one actually go about generating alpha? In the speech starting on page 81 of their letters, our investing role models, Sleep & Zakaria, agree with Bill Miller's claim that alpha can come from one of three sources:

1. Information - Find & incorporate information that someone else does not have access to

2. Analysis - Analyze & draw conclusions from public information better than everyone else

3. Psychological - Behave in a way that is more disciplied than any one else

Both in public markets & financial markets, I think these three sources of alpha are actually ranked as I have them written out - Information is the least interesting, and Psychological is the most interesting.

In public markets, it's pretty hard to get information that no one else has. If it is truly "secret" and widely accepted valuable information, you typically can't trade on (it unless you are a politician).

When founding a company, this category is slightly more interesting, because the relevant information often comes from interrogating people in the space you are serving. While this can take a lot of effort and requires discipline to get right, to experienced founders, it is sort of table stakes. And, to industry insiders who found a company, they can oftentimes invest less in this area, because they already have an intuitive understanding of the relevant information in the space.

The other two, though, are a lot more interesting

[Estimating Truth]

Analysis is an exciting source of alpha. It gives you a chance to test your model of cause and effect against everyone else's—you're more or less trying to draw more right (or less wrong) conclusions from the available information than everyone else.

As a brief example from financial markets, I invested in a steel company that built out a new business line that produces pre fabricated steel structures. This was very unconventional, because most steel companies sell steel at commodity prices & let everyone else process it.

A lot of investors thought their new business line was a distraction. However, when steel prices took a turn for the worse, the margins across their business stayed up because the pre fabricated steel structures did not go down in value as much as steel, as they claimed would happen (and as I agreed with).

Now, I am still invested, because they have been extending that pattern by diversifying to aluminum. This is a risk, but my analysis (now admittedly dated) says that their founder (still ceo) is taking the risk prudently by largely funding the investment with free cash flow while still returning a healthy amount of capital to investors.

This is somewhat a trivial example, but the core of analysis is there—based on the information that is available, what do you think will happen?

In BirdDog, we’ve recently had an example of some more complex analysis. We have a lot of conflicting information:

• Some users ask us for 'sequencing' tools and workflow automations

• Some users want us to integrate data with crm

• Some users who tell us the data is great, but they don't actually use it!

I'm simplifying the matter, but here are some possible conclusions we can draw from these claims:

• We should build sequencing tools

• We should integrate with CRMs & other tools that are already frequently used

• The data is actually not valuable

The conclusion we draw will have a massive impact on the business we build. If we think it is the first option, we will invest a lot of time into building out and maintaining features. The same is also true for 2, but to a lesser extent (a sequencing tool would require more ui/ux & just as much integration with other platforms as the other tools). And the third would conclusion would call our business model into question!

We want to make a decision that will give us the best roi; what, in the long term, will give us “the best” business?

To come to an answer, we have to use all of the other information we've already learned about our space:

• A major sequencing tool may go bankrupt soon

• Credible sales leaders are calling the usefulness of sequencing tools into questions

• Some firms already spend as much as $25M / yr on CRMS,

• An industry of consultants are invested in keeping teams in their crms

• Our data has created value time and time again

With our analysis on this info and more, we've decided to integrate with CRMs and other existing systems. Since we're just rolling this out now, it's too early to adjust the scoreboard, but I have enough confidence to call the shot in writing here.

Regardless of whether or not we are right, analysis of the information in question is absolutely critical and has a massive impact on how much alpha you generate.

[Wax in Your Ears]

The last edge, and by far the most interesting, comes from overcoming the slew of psychological biases that plague us as humans.

This is the most interesting because it is so hard to do and so few people do it! After all, you are literally fighting against human nature.

These biases are too enumerate to comprehensively articulate here, but a recurrent theme is having the wisdom to separate what you should ignore from what you should focus on. So, I’ve shared three things you should ignore.

Ignore Sales People

In both finance & founding, there are a lot of people trying to sell you something by leveraging marketing that makes you feel like you need their thing.

This sort of person is not just limited to gurus selling investment courses or startup courses, but also to a lot of others who you might otherwise be inclined to believe—some financial advisors, some VCs, and some firms selling software products fall into this category, too.

You will hear that if you don’t do this one thing that they can help you do, then you will fail. And while their offerings can be genuinely helpful, it is really important to not get convinced that you will fail if you don’t buy from them or work with them.

Ignore Hype Cycles

Another major trap is following into hype cycles.

Recently, I spoke with someone who pivoted from {last_popular_idea} to agents. Why? Probably because agents are popular now!

There is a collective euphoria around agents that almost has a life of it's own. It's not one person trying to sell you on the idea that you should use agents; rather, it is a herd mindset that you see in both startups and financial markets quite often... there is a massive convergence on one hot thing.

Whether it be tulips, the internet, real estate, crypto, or ai, whenever most people agree on one thing with a fervor, they are typically more wrong than right. And that doesn't meant they're strictly wrong, it just means that they're likely missing a lot of important details and caveats and trade offs.

Yes, AI will fundamentally alter the fabric of society over the next 10 years. That does not, however, mean that you should drop everything and invest in AI! BirdDog uses AI, but we don’t use agents; if we think it makes sense at some point for our business model, then we will use them. We certainly won’t just use them because everyone says we need to…

Ignore Short Term Thinking

This one might encapsulate the other two - if you can get passed very short term thinking, you will be well off indeed.

Optimizing for small time scales, like how you feel in the next 30 seconds, does not generally get you as good of results in the long run, as say optimizing for how you will feel on your death bed.

The same is true for investing or building a business. "Making a quick buck" is usually a trap.

In the context of BirdDog, we have to resist the temptation to say yes to everything at the expense of saying yes to the things that we believe will make a unicorn.

[Investing in Investing]

There’s a lot more to investing than I could share in so few words, particularly when we get into psychological biases.

But, if generating alpha defines a good investor, then you can be a good investor by getting just about as much information as everyone else, processing it with thoughtful analysis, and being emotionally disciplined in a noisy world where everything wants your attention.

Starting a company requires massive effort, and you can really actually succeed without generating alpha. But, if you want to get outsized returns (part of the draw of starting a company), I do think behaving like a good investor is a powerful strategy—I think it has and will help Jack & I make a very valuable company.

And, if we hone in on the psychological part, simply putting wax in your ears can get you really far.

Live Deeply,