tl;dr
8 principles that guide me through the labyrinth of going -1 to 0 with a startup:
- Everything is equally hard, modulo your inherent advantages.
- Any idea can lead to a huge business.
- Intuition drives testing, data drives decision-making.
- Action produces information.
- Discomfort is the way.
- Your customer is all that matters.
- High-quality reps > high-quantity reps.
- Play loose. Have fun.
Intro
In the quest to build a startup, I’ve already wrote about a systematic method to generate ideas and a user manual for vetting them (coming soon, I promise). These are resources to help you go -1 to 0 – From the commotion of everything you could do, to the convicted thing you will do. But together, they only give you a blueprint. Concepts that are simple in the abstract, but missing nuance that make them hard to put to practice. Day-to-day, you’re burdened with tremendous ambiguity. Where should I start? Should I abandon this idea? This person says this is a shit market, what should I do?
And once you start down a path, the market will tell you lots of things: some right, and some wrong. It’s your job to separate the signal from noise, but how?
“Being a good entrepreneur requires having a hundred conflicting data points in your head and being able to still make a decision.” – Nat Turner
I don’t have the silver bullet, but I have guiding principles. 8 heuristics that help me navigate through the uncertainty and conflicting feedback. What I’m about to share is not necessarily true (and arguably controversial), but its useful to me.
Principles
1. Everything is equally hard, modulo your inherent advantages.
Assuming everything, from healthcare to AR/VR, is equally hard is a reasonably good approximation. Doesn’t mean it’s the same genre of hard. In healthcare SaaS, the market opportunity is vast and assembling a product is easy (usually), but establishing scalable distribution is painstakingly difficult (not to mention differentiating from the competition). In AR/VR, it’s sort of the opposite: The market is disappointly small (but it could grow) and if there’s a hardware component to what you’re doing, there’s technical risk. Distribution is still hard but not as punishing as healthcare. The cliche in startups is that B2C is way harder than B2B. Sure, consumer preferences are fickle and funding for these startups is scarce, but if you can dodge these obstacles, you have room to grow because chances are your competitors will get impaled by one of those obstacles. But with a B2B SaaS play, customers are saner and funding is readily available but competition is fierce because those realities are true for others. One more example: Writing software is easier than producing hardware. But with software, you take on a lot of market risk (do people actually want the thing you’re building) at the expense of execution risk. With hardware, the balance is typically tipped the other way. You can debate differences at the margins, but taking the limit of this train of thought, I argue the different risk profiles across industries pretty much cancel out.
I don’t want to go too far down this line of thinking, but the mechanisms behind allocation of resources in markets are pretty efficient, so if something was “easier”, capital would quickly rush in to arbitrage the difficulty away. So on balance, net difficulty is equal.
When you factor in your inherent advantages (talent, trained skills, subject matter expertise, personal capital, etc.), the distribution of difficulty is no longer uniform. This rule helps me counteract the “grass is greener” bias, where we allow little knowledge of a foreign domain to trick us into believing there’s a chance of greater success elsewhere.
There’s a well-told story in YC lore about the Brex founders. After successfully exiting their first fintech company, they wanted to escape the industry. They looked outward to what was in vogue at the time (2017): AR/VR. They joined YC and dabbled in AR/VR for a while, but quickly realized it wasn’t their forte. The market was nascent, the technology was complex, and the path to profitability was unclear. Recognizing that their strengths lay in fintech, they pivoted (back), and eventually created Brex.
2. Any idea can lead to a huge business.
In this post, I make an attempt at proving this assertion, but its based on a lot of questionable assumptions and hand-waving. But I find this rule has real practical value, even if its not quite true. Anytime I find myself tormented about whether an idea will scale or is situated in a big market (which is nearly impossible to judge), this principle gives me comfort to make local progress, without being paralyzed by global factors.
3. Intuition drives testing, data drives decision-making.
When it comes to where to start, I don’t rely on market research or playbooks to chart a path. Instead, I lean on my intuition to make the first move. What’s your gut feeling on the first problem I should explore? Who do I think is the target customer? What’s the best way to reach them? These initial intuitions are what guide experiments.
As I gather data from these initial tests, that becomes the primary input for my decision-making process. I don’t cling to my original intuitions if the data points in a different direction.
This interplay between intuition and data is crucial. Intuition without data leads to unsupported assumptions. Data without intuition leads to aimless empiricism. The two work in tandem - intuition sparks the initial direction, data confirms or refutes it, and the cycle continues.
4. Action produces information.
This is one of my favorite pieces of advice from Coinbase founder, Brian Armstrong. Even if you’re not sure what to do (your intuitions could be weak), just try something different. Because any action is better than inaction.
“Startups are like sharks. If they stop swimming they die.” – Paul Graham
When you try a product or GTM experiment, it will produce information and help you come up with better ideas of what to try next. This is true even when you try the wrong thing. Trying the wrong thing should still help you identify which hypotheses about users, value proposition, go-to-market strategy, etc. are wrong.
Don’t get stuck in analysis paralysis and remember,
“You can’t connect the dots looking forward; you can only connect them looking backwards.” – Steve Jobs
5. Discomfort is the way.
Lets face it, a lot of this journey is uncomfortable (even when you transition into 0->1, it doesn’t get any better). And you need to recognize that your mind has a knack for protecting you from discomfort, even when you’re not conciously aware of it. If you’re smart, this tendency is especially acute. You’re mind is better at pulling out all sorts of gymnastics to rationalize decisions that avoid confronting fear. It’ll steer you away from rejection from potential customers, sticking with a problem that seems temporarily hard, networking with strangers, etc.
So when faced with a decision with seemingly two equally good options, I choose the one that’s more uncomfortable. That’s because my mind is likely subconciously minimizing the potential out of uneasiness.
6. Your customer is all that matters.
At this stage, your ego is in a fragile state. Your vulnerable to the bad advice of others, like investors, fellow founders, retired experts, etc. They’ll tell you that something is not possible for XYZ reasons, or this market is going to explode in the next 10 years, or that you can’t succeed without londstanding industry relationships–don’t let any of that dissuade you from finding out the truth. The only opinion that matters is your customer’s. Your job, as a customer-first founder, is to listen to the problem your customers want solved, create a solution to it, and validate that they’ll pay for it. That’s it. It doesn’t mean you shouldn’t pay some attention to those other voices, I’m saying that you shouldn’t let them make decisions for you.
7. High-quality reps > high-quantity reps.
If you haven’t guessed already, you’re going to be running a lot of experiments. Experiments to discover what is the product, who are the customers, how will you reach them, who are the competitors, etc. The list goes on. You’re going to be learning a lot and the velocity of learning is going to determine how fast you get to conviction.
With any idea for an experiment, make sure that there’s a well-defined distinction between success and failure. Don’t fall in the messy middle. If the hypothesis fails, make sure it fails clearly and unambiguously. If it succeeds, make sure it succeeds equally clearly and unambiguously. A hypothesis failing means the experiment succeeded; you learned something. That’s what it’s all about. The worst outcome is mediocre success.
So prioritize high-quality reps in favor of a higher quantity of them.
8. Play loose. Have fun.
This isn’t a heuristic so much as it is a reminder. When I look back at my time playing competitive sports, I played my best when I played loose, when I wasn’t obsessed about my performance or the outcome.
I suspect that this process from nothing to conviction is one influenced by the backwards law: Where too much effort actually harms your progress. Unlike diminishing returns where incremental progress attenuates the more effort you put in, the backward’s law states that in certain activities, after a certain point, more effort reverses progress. The backwards law is prevalent in human psychology: If you feel anxious, the harder you try not to feel anxious, the more anxious you will feel. If you have low confidence, then trying really hard to imrpove your confidence will actually further destroy your confidence.
Maybe its false intuition, but I think that way-finding suffers from the backwards law. So when I find myself taking things too seriously, I remind myself with the simple words: play loose, have fun.
Conclusion
These are my personal principles. They help offset my biases when searching. Your biases may vary. You may need a different set of guiding principles. Regardless of what they are, the key takeaway is having them is better than not.