The thing we care most about in interviews (at least of things one can change) is how engaged the founders are with users. How do they know people actually want what they're building? Have they talked to real, live users? What have they learned from them?
We don't care super much how big the initial market is, so long as the startup is making something that (a) some subset of people want a lot, and (b) if that market is not itself huge, there is an easy path into bigger neighboring ones. Basically, we're looking for startups building Altair Basic.
If founders respond that there aren't really any current solutions, then it usually means that either a) They aren't making something that people really want, or b) They haven't talked to enough users.
If it's a problem people actually have, then they must be coming up with crazy hacks or solutions that are much more tedious/inaccurate/expensive/generally more painful than the one you're coming up with. Very rarely is there simply not some kind of existing solution.
What I found really interesting was that the reason successful disruptions are "more convenient, simpler and/or cheaper" is not because that's an improvement, but because it enables the disruption to be used by non-consumers... (who lack the skills for a complex product; or the money for an expensive one; or access to an inconvenient one.) They are delighted to have a solution better than what they have now, so it doesn't need to be as good as the incumbents'. Secondly, if it's not good enough to appeal to incumbents' customers, it won't provoke a competitive response.
For example, before the automobile, horse and carriage was a 'solution' to the problem of getting around. In the early days, was a car a much better solution than a horse? Horses were readily available, didn't need a gasoline infrastructure, they even self-replicated so you could get a new one every few years.
I understand I'm playing a bit of devils advocate here, but I often gut stuck in the mode of thinking existing solutions are good enough, then somebody comes along and evolutionizes an industry with what at the early stages might seem to be minor improvements.
Another example would be the early days of sunglasses. If the question was asked 'how are people solving this problem now', the overly simple answer would have been 'they squint a bit'. With that as the answer, would you go and develop sunglasses?
Take your example of sunglasses. A quick search on wikipedia shows that the precursor were glasses with a thin slit in them. It was never squinting, and then BOOM, Oakleys.
There was always a gradual change that is only missed in retrospect because of how standardized and popular the winner is.
Name a few popular products and services, and I bet there have been similar solutions beforehand.
Yep, when you talk about known problems. Still often both the problem and solution (which is just another view of problem) lie just outside current scope of people imagination, and are only found by prospective minds when the way is open (other conditions met).
There was not simply some kind of existing solution for Internet 50 years ago.
There were solutions for this Internet thing 50 years ago, even if it's hardly imaginable today. If the problem you are speaking about is communication we had that 2000 years ago, in form of smoke signals. It sucked and was dog slow but it was not an unknown problem.
think there's a good balance between customer development/research and your own instinct/vision
In our example, we produce and sell incomplete ebooks, knowing full well we may get a few refund requests, precisely because it's invaluable for us to know how to convert a paying customer, and to ask those customers for feedback.
Our interview was pretty much spent trying to respond to those questions. This is why having an actual product with any sort of customers is so valuable, because that's live evidence that what you're doing is working. Unfortunately my partner and I had little more than an idea and half of a web application, which we didn't even get to demo because we were so caught up trying to defend our position. I literally never even turned my laptop around to PG and company, which is probably my biggest regret about the whole thing, because I had spent every free moment of the past several months working on it and maybe that could have said more about our ability to execute than a debate on whether X market for Y users even existed.
Then again, probably not.
What do you not yet know, how are you developing information about that?
This is knowing what is risky and what isn't. Some problems are just 'engineering' you do work and get them done. Others need 'new physics' which is code for an imagined but not yet designed feature or capability to work. Too many of the latter can be a real problem.
How many people do you think you'll need to realize this vision? How many to keep it current?
One of the more sad failure modes of startups is over hiring. More people can be good, too many people is really bad, understanding what the people requirement is can bite you if you don't get it right.
How will customers find you? What does it cost you to be visible to them?
Customer acquisition, especially in a demographic that doesn't congregate (small/medium business fits this category) can be unduly expensive. If you have a product that would sell like gang busters at $X but it costs $X + $Y dollars to get a customer, you need to fund to n customers such that the $Y starts going down via word of mouth or other coverage.
Stack rank your feature set in 'lifeboat' order, explain how you got that order.
You should have more features imagined or lined up than you can deliver, that gives you follow on. But you also need to know what is the minimum set for a viable product. Understanding how you get to that minimum set says a lot about your priorities, your sense of the customer, and your reasoning about the business.
At least, thats what I get from this article and every single essay I've read that was authored by PG.
I think people use marketing-speak to seem more impressive, but on us it has the opposite effect. The phenomenon is very much like the artificial diction that inexperienced writers so often adopt, and which does nothing but get in their way.
I know it's bad form to quote oneself, but I can't put it better than this:
"When you're forced to be simple, you're forced to face the real problem. When you can't deliver ornament, you have to deliver substance."
Do they really ask that? Do people really ever answer anything other than "Yes"?
I could see it if you had some idea that needed millions in funding to start moving, but then you wouldn't be at YC, I wouldn't think.
It took me a long time to realize that when the odds of getting into something were described as e.g. 1 in 10, that didn't mean the odds for any given applicant were 10%, but rather (to the extent the people deciding were good judges) that for 10% of applicants the chance was nearly 100%, and for the other 90% nearly zero.
The famous example mentioned is W.S. Robinson's 1950 study of literacy among immigrants. He found that states with higher populations of immigrants had higher literacy rates, but the average literacy rate among individual immigrants tended to be less than the average population. He concluded that immigrants must move to areas where the literacy rate was higher.
It's not too much of a stretch to make a similar argument for Silicon Valley as a whole or refute any individual startup's odd's of success as 1 in 20.
A simple graphic illustration of this is smoking. A smoker's probability of dying of a smoking-related disease before age 65 is 15.6%. However, my probability of dying of a smoking-related disease (assuming I smoked) is either 0% (I don't die of a smoking-related disease) or 100% (I die).
People don't understand why some people smoke when there is such clear evidence of the increased probability of death due to smoking-related disease. Well, for each smoker, the probability is either 0% or 100%. If the smoker believes his probability is 0%, he will continue to smoke. If he believes his probability is 100%, he is a hypochondriac.
Thus, smokers either believe they are untouchable or they are crazy.
This is why it is so hard to sell "it's good for you" things... they are almost invariably statistically good for a large population, but can make no guarantees of "goodness" when applied to a singleton.
This applies in spades to health-anything:
* Individual's health: Lose weight and exercise - it's good for you.
* Program's health: testing is not guaranteed to find any bugs - if it were, running testing a second and third time would always find more bugs.