

Paul Graham Says Y Combinator Is Pickier Than Ever, ‘Hardly Any’ Bad Startups  - aashaykumar92
http://techcrunch.com/2013/03/26/paul-graham-picky/

======
j_baker
_“There are hardly any startups in this batch that are bad,” Graham said._

I believe one of two things about this statement, neither of which is what pg
likely meant by it:

1\. YC has bad startups it just hasn't recognized yet.

2\. YC has an entirely mediocre batch of startups due to not taking any risks
on "bad" startups.

~~~
mapgrep
Or he was attempting what hu-mans refer to as "humor" :-)

~~~
stcredzero
A better alternative than what hu-mans refer to as "hue-less."

------
lmm
Is this really the right approach? I remember PG writing that if YC were truly
rational they should have a _bigger_ proportion of failures (because they
should be taking much "riskier" ideas, because of the power-law distribution
of outcomes).

~~~
eah13
This is a good and interesting question.

Since YCombinator depends on finding Dropbox and AirBnB scale startups, I
imagine one of the most important metrics to them is whether they've rejected
a business that went on to achieve that scale.

Of course being in YCombinator can increase a venture's chance of hitting that
type of success, so keeping track of who they rejected is just a proxy for how
well their applications strategy is. They may have rejected a company that
_could have become_ AirBnB or Dropbox. But this is less important since in
this case that would indicate that this ability lies with YC, not the startup,
and so it's less important which companies they pick. If true, this would run
counter to the founder-centric model they profess, so I'm skeptical it's how
they feel.

This question of who to let in reminds me of the tradeoff of precision and
recall in IR. A large class can reasonably be termed higher recall, while a
class where they actively exclude companies with predictors of failure
increases the precision. THe two metrics are inversely related, but it's
possible to have high precision and recall if you're only looking for a very
few number of things and you pick them all.

It seems to me that culling out likely failures would only make sense if the
partners had determined that the presence of these likely-to-fail companies
negatively impacted their ability to help other companies reach their
potential. This seems a likely rationale to me based on PG's comments about
how dying startups take up so much of their time.

So what it really seems to represent is a vote of confidence in the partners'
ability to help startups increase their chance of massive growth. And/or a
recognition that likely-to-fail startups have deleterious effects on the rest
of their batch that outweigh the likelihood that they'll be successful
outliers. Either way it doesn't seem to have much impact on companies that
apply.

It will be interesting to see if PG writes a How Not to Apply essay. Such an
essay might destroy the predictive value of these behaviors, but if it stops
the behaviors and they were causally linked to bad outcomes then it's a net
gain.

------
RKoutnik
Here's hoping pg writes an essay on what YC thinks the "predictors of failure"
are. I'm sure some applicants for S13 are probably panicking, having optimized
their application for the "old" version of the YC selection process. I'm not
too worried, as we're exceptionally strong on the one data point he's
provided.

~~~
wilfra
Much like the Google guidelines on SEO, I would imagine pg's response to this
would be something like 'the best way to optimize your application is to
ignore optimizing your application' and instead focus on building something
awesome.

~~~
RKoutnik
He's written quite a bit [0] on what they look for in founders. I'm not
talking about pg writing a "How to optimize your app" essay, but literally
"Indicators of Failure"

[0] <http://www.paulgraham.com/founders.html>

~~~
wilfra
Right, you want him to give you more signals about what they are looking for
so you can tell them what you think they want to hear - that's the wrong
approach. You should instead focus on being awesome and hope that YC
recognizes how awesome you are.

The perfect application may look identical to the perfectly gamed application
- but the intent is different. And it's a bit naive to think YC isn't really,
really good at sniffing out that intent.

~~~
stcredzero
_> And it's a bit naive to think YC isn't really, really good at sniffing out
that intent._

At this point, YC probably has a useful amount of data. I wonder if he's
thrown a Bayesian filter at it? One of the things PG noted in his "A Plan for
Spam" essay, is that his Bayes filter flagged indicators that he never would
have thought of. I wonder what kind of data someone could get from a corpus
consisting of YC's data, plus web searches on the applicants?

------
jcr
The linked article (and title) says:

> _“There are hardly any startups in this batch that are bad,” Graham said._

But the following [1] says:

> _Y Combinator founder Paul Graham said this he feels like the contracted
> size of this class means that there are essentially no weak startups in the
> bunch_

There's a huge difference between "hardly any bad startups" and "essentially
no weak startups" so it seems someone at techcrunch is misquoting pg.

[http://techcrunch.com/2013/03/26/y-combinator-
winter-2013-de...](http://techcrunch.com/2013/03/26/y-combinator-
winter-2013-demo-day-batch-1/)

~~~
loyalelectron
Hey, I'm the writer who wrote the second example cited here -- very good point
in showing the difference between the two, so I wanted to try and clarify.

When Graham said the "hardly any" line on stage, it drew a pretty big laugh
from the audience -- it seemed like a bit of humor on his part. The earnest
meaning and connotation I took from that (and comments Graham gave off-stage)
was that there were no obvious weak links in this batch.

~~~
jcr
Thank you for the additional insight and context for the quote, and your
paraphrase. The quote makes a lot more sense as a joke, so it would be good to
note that in the article.

------
SilasX
And if there _is_ a bad startup -- like one that looks like it's going to run
away with customers' money (or at least make them panic about it) -- don't
worry, they just clip out any mentions of the YC association.

<https://news.ycombinator.com/item?id=5428449>

~~~
chc
If that is the best example you can find of this theoretical phenomenon, I
don't see why you'd bother dredging up such a load of nothing.

~~~
SilasX
It doesn't bother you that "YC 'XX" appears on every article about a nascent
company regarding good news, then gits stripped from the title when one of
them appears to be dicking over its customers?

~~~
chc
No, it does not. The (YCwhatever) doesn't even get slapped on _all_ stories
about YC companies. There is a rather large difference between the ones it
goes on and an attempt to contact the company through HN, and I don't see any
evidence that the sole differentiator is positivity.

But even if it were, not including it in the title of negative articles on HN
would hardly be the same thing as removing any mentions of their association
with YC.

------
aashaykumar92
"He [pg] said that this time around, YC looked at 'predictors of failure,' not
just 'predictors of success.' For example, he said that in the past YC might
have chosen a company that had great founders (a predictor of success), but
this time it might have filtered that same company out because those founders,
while great individually, all hate each other (a predictor of failure)."

The given example implies that YC has chosen founders who don't like each
other in the past. Seems remarkably odd and hard to believe IMO. It may have
meant to say that the founders seemed LIKELY TO hate each other eventually but
if they even disliked each other at the interview, I can't imagine the YC
partners being ok with this.

~~~
rdl
I think he was just giving an easy to understand example which didn't really
reflect reality. The problem with predictors of failure, unlike success, is
that it's a lot easier to hide them once you know what they are. If you know,
for instance, that having founders who when asked say they're doing a startup
because they hate having a boss, no non-idiot will give that as an answer when
asked, even if they believe it, ruining the predictor.

~~~
aashaykumar92
Right, I agree. And exactly because of this, I hope pg doesn't divulge into
what these 'predictors of failure' are from his perspective.

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nwenzel
Why the big fuss about saying some startups are "bad"? I'm sure some startups
are bad. There's certainly a possibility that some bad startups looked good
and made it through the screening process. Other accepted bad startups may
have been risky bets that didn't payoff.

I think at least a few people have a problem with the directness and harshness
of the statement. But if I was one of those bad startups, I'd appreciate the
candor and directness. That would be far preferable to someone being "nice"
and allowing me to continue down the wrong path.

Being "nice" isn't really that nice at all.

------
mesozoic
This is opposed to last sessions where Paul Graham said lots of the startups
that just started and he had subsequently just allowed into his program were
bad?

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huslage
YC Has ONLY bad startups if Demo day is any sort of barometer. Some will be
"successful" for the investors. Ridiculous garbage.

------
rodrigoavie
So what does he mean by "bad startup" anyway?

Is that a startup that supposedly will hardly succeed?

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eli_gottlieb
Ah, so the present Silicon Valley bubble is about to pop.

~~~
RKoutnik
People have been predicting the pop for a while now, I don't think that YC
being picky (< 2% of applicants make it) is a sign of the apocalypse.

They hit scaling problems, so what? It's not indicative of a larger problem.

~~~
stcredzero
_> > Ah, so the present Silicon Valley bubble is about the pop._

Note he said "about the pop," and not "about to pop."

~~~
eli_gottlieb
That was a typo.

~~~
stcredzero
Oh, I read it as "about the pop" -- that it's about the small percentage of
companies that hit it big.

------
wilfra
Reminds me of the slogan for the strip club Déjà Vu:

"1000's of Beautiful Girls and 3 Ugly Ones"

