[dunkelheit]

People always bring Dropbox to these discussions as an example of a startup that was dismissed by HN but turned out to be huge, but turns out there are examples of the opposite thing happening too!

Does anyone remember Color Labs? Go read this thread and marvel at the similarities: https://news.ycombinator.com/item?id=2364463. A stellar team backed by top VCs who invested (extraordinary at the time) $41M sets out to build a location enabled photo-sharing app. VCs tout it as "the next Google". Most of HN is pretty critical with some voices advocating caution and saying "let's not be so dismissive, maybe there is something more to it". Well, it turned out there was nothing more to it.

So no, being dismissed by HN does not automatically mean that your idea is good and you will be successful.

[gofreddygo]

I see this as a pessimism/optimism spectrum. We are on the extreme left if we can reliably predict successes and on the extreme right if we can reliably predict failures.

As we pick a few datapoints (Dropbox, Coinbase, Airbnb) and we average it out, we are pushed towards the left.

More data we pick (colorlabs for example, and I'm sure many others) we are pushed more towards the right.

Most popular article dealing with VC news, startup promotion, funding news, valuation bragging, acquisition gossip, startup failure reports picks data that push the narrative towards the extremes.

My instinct says we are squarely around the center where we can't predict shit.

[ZephyrBlu]

> My instinct says we are squarely around the center where we can't predict shit

Completely agree. There are a lot of people in this post trying to rationalize their own biased opinion on what predicts success or failure though.

[IgorPartola]

To expand on your model, I think our ability to predict success and our ability to predict failure are separate things not on a continuum with each other but orthogonal metrics. We need to count false positives and false negatives here.

I predict that HN is no better at predicting success than average. It might be better than average at predicting failure but given the distribution that might not be that hard: if you dismiss every idea AND most ideas fail, then you always look like you are getting it right with a few occasional wrongs. Think about it in the inverse: if most startups succeeded spectacularly but a few failed miserably and you always were bullish on all startups, people would just say that you are almost always right.

The only real difference between predicting success and the result being failure and the opposite is that in this world success is unbounded (your valuation isn’t constrained since you can create a whole new market segment), but failure is always bounded. Therefore getting a success wrong sucks more than getting a failure wrong: you could have made a lot of money by correctly predicting a unicorn.

[gofreddygo]

> I predict that HN is no better at predicting success than average

I can't fully agree on this. In a fair game (coin toss) your chances are just that, average. In a game where your experience, network and wealth can influence the outcome, things can be different. This is common in the enterprise market.

In the consumer market (which isn't more fair, but just works differently), that model fails miserably, that's where we start seeing the failures of the predictions and bets made.

What I see happening, is the vested parties (VC, Founders, investors) trying to cherry pick data points (from both markets), and then bragging about how they are good at predicting in both markets, but when you add in more data you see, that is not the case.

[aerosmile]

I am really surprised that you didn't choose the more obvious line of reasoning, which would be to bring up examples of companies that PG predicted to be breakout successes and then they failed. PG marveled about Instacart and Flexport well before anyone else, including myself (I know members of the founding teams in both companies very well, and think very highly of them... but even so, I didn't see their companies as the type of breakout successes that they became until PG made his case for them). The constant hate against PG is really starting to get tiring, especially when you see such sloppy reasoning. Why judge his reasoning based on what other VCs thought? Saying PG = VC industry is a really stunningly poor argument IMO.

[sombremesa]

Yep, you can actually go through the list of companies YC has funded on the website and most of them are out of business today (as you’d expect based on the stats on VC backed ventures). Of course, nobody talks about those.

[aerosmile]

I am struggling to understand what you're trying to say. Technically what you said is perfectly correct, but in a "the sun goes up in the morning and comes down in the evening" kind of a way. I doubt there are many people on Hacker News who don't realize that most VC backed ventures fail.

What would have been more insightful is a conversation around relative benchmarks. For example, "do YC companies fail at a higher rate than the cohort of equally funded companies?" (hint: no).

Or perhaps, if you're trying to criticize the VC industry, perhaps ask, "if a VC put in money in every YC company since the beginning of YC, what would their IRR be today?" (hint: massive).

[sombremesa]

I'm trying to say: 'Of course, nobody talks about those.'

Since it's soooo obvious that we should all hide our failures and glorify our successes without questioning this practice (I did say 'of course'), I understand how you missed the point.

[deckard1]

There were people also defending Theranos and WeWork.

I take all articles and comments here with a huge grain of salt. Especially Paul Graham.

https://idlewords.com/2005/04/dabblers_and_blowhards.htm

Way back in 2005. Back when lemonodor was a thing.

[gist]

The essay is really just self serving to keep stoking the YC starmaking machinery (see lyrics to 'Free Man in Paris' by Joni Mitchell). Keep people dreaming and some of the crazy ideas will hit.

People often forget that even Apple (or might not know if young) was not wildly successful and almost went bankrupt (or close to that) and had to be bailed out by Microsoft.

Also forgotten is that the quality of the execution matters a great deal. Dropbox or Coinbase w/o good execution and attention to details would not be where they are today. Ditto Color Labs with great execution would not work necessarily.

[ChrisArchitect]

Dropbox got big because iPhone users were so desperate to be able to share files between people and desktops that they started using it in droves. The desktop users that took it on were simply looking for some more storage and it just took off from there. There was no reason to pay attention to it initially (and still isn't imo) and over in android phone land everyone had no reason to either other than to retrieve files their friends sent them.

[Uehreka]

That’s not how I remember it at all. The first time I heard of Dropbox it was in 2010-ish (1 year before I got an iPhone and several years before iPhones had a usable file system) when folks in my dorm were using it to share music libraries. I was a CS major and had never even heard the word “samba” (yeah, I know) and it seemed super useful for all kinds of things.

I mean, that’s just me, but my understanding was that it didn’t take off on mobile until after it had established a secure foothold on the desktop.