Y Combinator Startup School: Week 1 Takeaways
I started my business (formally) in February 2016, and while revenue and inventory growth have been beating expectations year-on-year, I know I could be doing more. There are companies out there that were built, grown, and acquired in less time!
I coincidentally came across Y Combinator's Startup School in July, on their original deadline for accepting sign-ups. Knowing their reputation and how much the curriculum would be influenced by the likes of Paul Graham and Peter Thiel, I signed up. To hold myself accountable and to benefit my fellow lifelong learners, I’ll be sharing my notes and key lessons here.
My first two takeaways immediately sold me on the program (in addition to it being free!):
1.) There is no "right" company for Startup School
When you imagine the companies that get mentored and funded by Y Combinator, you picture a group of genius hackers working 80-hour weeks to build the next great tech startup. It's easy for anyone who didn't fit the mold, like myself, to feel like they don't belong.
But they addressed the elephant in the room right away, explaining that no matter what your industry, your stage of progress, how big your team - you're in the right place. This lesson applies beyond startup school, i.e. just because you're not building the next Facebook doesn't mean your new business has any less merit.
2.) Startup School is, at the very least, "an excuse to work on your startup"
By having regular check ins, you want to show up with some kind of progress to report. Accountability at it's finest. Who couldn't use some extra motivation to work on their side hustle?
Lecture 1: How to Evaluate Startup Ideas Pt. 1
The first lecture, "How to Evaluate Startup Ideas Pt. 1" is a primer on Y Combinator's philosophy of entrepreneurship. The themes discussed by Kevin Hale, a partner at YC, set the stage for the rest of the program.
Here's what I learned:
3.) Many people never go full-time with their startup not just because they don’t have resources, but because of conviction. They never set out the conditions under which they are willing to quit their job.
I think most people with a side hustle dream of growing and running it full-time. But you can't expect the magic startup fairy to come knocking on your door, telling you when the time is right to dive in.
You need to lay out in advance the KPIs you need to hit, or what the company needs to look like to be comfortable going full-time. It seems like common sense, but how many people actually do it?
4.) "A startup is a company designed to grow very quickly."
This was an interesting way for YC to define a startup, but being investors, it makes sense. It draws a line in the sand between a small business, where the goal might be to grow more gradually, provide some side income, learn, work for yourself full-time, or benefit your community, and a startup, where the goal is for growth chart to hockey stick (usually ending in an IPO and/or acquisition).
5.) Think of a startup as a hypothesis about why a company should grow quickly - this also provides the structure of your business' narrative.
Hale describes a startup hypothesis as having 3 key points:
Problem - the setting or conditions that allow this company to grow very quickly
Solution - your startup, aka the experiment you're running within those conditions
Insight - the explanation of why the experiment will be successful
The copywriter in me also recognizes how this also provides a great structure for explaining your startup - especially to investors, the press, and anyone else outside of your target market.
6.) There are 6 characteristics of "good" problems. You need at least one of these conditions - ideally multiple - but it's not necessary to have all.
Good problems (i.e. problems that present viable business opportunities) are:
Popular - a lot of people have the problem
Growing - ideally at a rate faster than other problems
Urgent
Expensive to solve
Mandatory
Frequent - people will encounter them over and over (thus giving you multiple opportunities to convert)
7.) NEVER start with a solution and work backward
This is probably the golden rule of startups - never start with your product, solution, or idea and then try to find (or create) a market or problem for it. At YC, they have an acronym for this: SISP or "Solution in Search of a Problem."
The best startup ideas originate with the potential users or customers. Start with what problems they have and do whatever is necessary to solve them. This could mean starting with yourself, but to have a viable business you’ll definitely still need to validate that others have the same problem AND are willing to pay for a solution. This, of course, means you need to stay closely engaged with customers, talking to and interviewing them frequently (more on this later).
8.) Your insight is your “unfair advantage” in the marketplace
You can consider “unfair advantages” like competitive advantages or unique selling propositions within the startup world. There are 5 possible advantages, and while you don’t need them all, it’s good to have multiple. They are:
Founders - are you 1 of 10 people in the world who can solve this problem?
Market - is it growing rapidly (i.e. at least 20% a year)? If so, your solution will automatically grow. However, this isn't a viable long-term advantage.
Product - is it 10x better than the competition?
Acquisition - do you grow by word of mouth/without spending money? Take advantage of your early lack of resources and acquire customers by doing things that don't scale. If you rely completely on marketing that others can replicate (e.g. paid advertising), then your venture has a short runway.
Monopoly - as your company grows, do you get stronger? This relates to the monopoly effect explored in-depth by Peter Thiel in Zero to One (one of the greatest books on startups in recent history).
Lecture 2: How to Talk to Users
The second lecture builds on point 7 above - finding actual problems to solve by talking to actual customers.
It's led by Eric Migicovsky, another partner at YC, and he sets expectations from the first minute, explaining that the best companies are ones where the founders themselves maintain a direct connection to users/customers. He goes on to explore the idea in depth - here are my big takeaways:
9.) To start a company you need to build a product, and talk to customers
It's that simple. Imagine 50 people in a room complaining to you about the same problem, and building them a solution they're willing to pay for.
10.) There are 3 goals to user interviews, and 3 mistakes that most founders make:
Goal 1: Extract as much information and data from them as possible to improve your product, marketing, positioning, etc.
DON'T talk about or try to sell them on your idea.
Goal 2: Talk about the concrete path that led them to encounter the problem, including their motivations and the broader context.
DON'T talk about hypotheticals (e.g. what a product could be, features you want to build, etc.)
Goal 3: Take copious notes and listen - this way you’ll bring to the table hard data and real facts about users’ lives. Plus, you rarely know until later which key facts of user interviews will be useful.
DON'T talk too much.
11.) Migicovsky helpfully gives the exact questions we should be asking:
What is the hardest part about this problem?
When was the last time you encountered it?
Why was it difficult?
Customers don’t buy the what, they buy the why (i.e. features vs benefits – it will inform your marketing or sales copy... my copywriting friends and readers will know this concept well!)
What, if anything, have you done to try to solve the problem?
If potential customers aren’t already exploring potential solutions, it might not be a viable opportunity. If they are, then you'll learn about potential competition.
What don’t you love about the solutions you’ve already tried?
Users aren’t good at identifying possible features, so it's no use asking what they'd like to see (remember, try not to talk about hypotheticals). But the problems they have with current offering or solution suggest what you can do differently, and thus build a feature set.
12.) Be prepared to discard "bad data"
Bad data would include anything:
Non-specific
Non-tactical
Hypothetical
Generic
Fluffy or overly positive
Those are my key takeaways from an enlightening Week 1! I hope you enjoyed, and it would mean the world if you would help hold me accountable for graduating Startup School - please be the hokey, inspiring teacher to my wayward inner city kid! Feel free to pester me via DM, email, Insta comments, etc.!
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