To sound a note of caution… I spent a number of years acquiring various kinds of non-monetary capital that are useful for startups. Looking back with my current state of theoretical knowledge and memories, I suspect I may come to see this period as involving too little caution. The key concept acquired between then and now is KellyBetting.
I still haven’t worked through the applications of this concept to startups in a way that I feel is “settled”, but depending on the precise nature of the risks and rewards and the bankroll of the typical person accepting startup equity in place of cash, the Kelly Criterion may indicate that startups should usually not be more than hobbies for “normal” (non-rich, non-certainly-immortal, declining-utility-in-dollars) humans. Note that if startups are roughly as risky as a simple Kelly calculation says they should be, this might still be cause for concern because most people who raise theory/practice issues with Kelly say that it over invests in risks.
I’m still exploring ways that the theory might line up with reality, but even my limited state of knowledge has caused me to scale back my startup enthusiasm in the last year or so. The math might come out more positive if you value the knowledge capital gained through startup work in the correct way, for example, but that’s particularly tricky to calculate. If anyone else has thoughts on this subject I would love to read or hear them.
For reference, Robin already wrote about Kelly betting to claim that the present era is visibly unstable because most investment firms, and the economy in general, seems not to be engaged in a Kelly strategy at the present time. In some sense, Robin claimed, a financial system not dominated by Kelly-following-financial-entities would probably be a system that has no significantly old Kelly-following-financial-entities, because in the long run they “win” at finance.
Another source on Kelly betting that is directly applicable to startups flows with the “invest in the team, not the idea” dictum. The post “Optimal startup burn rate and the Kelly criterion” is no longer available in the wild but is retained on archive.org and discussed the optimal team size and experimental product cycle given a starting bankroll. (The blog is LaserLike and is not itself down.)
For what its worth, I’m not totally bearish on startups, and sort of have one cooking… I’m just trying to pursue startup stuff with an eye on keeping a bird or 6 in the hand while pursuing startup stuff in parallel. In this vein, if anyone is or knows a solid hardware hacker with RFID experience/interest, especially if they are ethical, planful, world-savey, “rational”, and/or live in (southern?) California, I’d appreciate hearing from you. No particular startup interest or equity tolerance is important—just hardware skills, character, and an interest in educational conversation :-)
I have extensive experience in this realm, including both independently re-deriving Kelly before learning about it and then working extensively with variations of it, in nominally Kelly-optimal conditions. Kelly is only optimal under a very strict set of criteria, and those criteria de facto do not occur in practice. It’s a great guide to the landscape, but a terrible perscription in most situations. Common errors include misunderstanding what counts as a bankroll, inability to access large portions of the real bankroll, changing returns to investment size, the existence of limiting factors, having almost any real utility function, unknown unknowns and edge uncertainty which is almost always correlated, psychological impact and inability to precommit credibly to Kelly, outside perceptions and their impact on your bankroll or utility, not accounting for calculation errors, odds or outcomes that are impacted by bet size, and more.
I may write a top-level post going into more detail (feedback on this idea is appreciated), but here I will deal only with this particular case.
In a start-up, the bankroll definition and potential is one key. Your bankroll includes more than you think, and that’s especially true in a start-up world where you can, even in failure, get more investment and start again, or join someone else’s start-up, or just go back to a day job. Kelly assigns infinite disutility to going broke, and going broke is standard procedure in the startup world. Also, how you take your compensation is largely for motivation and signaling and to keep control of the company, all of which impact the result. In bankroll terms my investing in my own company, and taking $0 other than expenses from my start-up work was madness, but it was clearly the correct play and has paid off handsomely in numerous non-bankroll ways even if no money results!
Going full speed at a startup, even in failure, is often a winning play as you develop connections, reputation, experience, skills and other neat stuff like that, laying the groundwork for future success.
I’d be interested in reading that post! If you do, could you explain more about the grounds on which you’d be applying Kelly to this problem at all, though? I’m somewhat unclear on that—see my other comment in this thread for detail.
In this problem, you’re starting a business, and you can consider that business as a bet, out of which you hope to gain a job, income, investment money from your equity, reputation, experience, and so on, all of which can be abstracted. Alternatively, you can look purely at the equity vs. salary trade-off in the context of Kelly, which as I explained above is deeply flawed. It’s not a great scenario for such calculations, but they can still provide insightful context.
That’s kind of reassuring. I’m just starting to read about Kelly, and my first reaction was “and your knowledge of the final outcome comes from where?”.
It also occurs to me that “Invest in real estate, they aren’t making any more land” is an effort at Kelly prediction, and we all know how well that worked out.
It is a classic mistake to treat your estimates as known expected outcomes when calculating how much to bet. This is one reason why real world gamblers almost always use half Kelly or even quarter Kelly rather than full Kelly.
“Invest in real estate, they aren’t making any more of it” is, in effect, a prediction of the expected returns to investment and/or the reliability of investment. Kelly would advise you on how to take advantage of the expected returns from real estate, once you nailed down your beliefs more carefully. For real estate, Kelly is rather horrified, as it finds many people investing far more money than they have into a single house. That sounds insane when you say it like that! However, a richer understanding of all a person’s assets together with the tax advantages of mortgage interest, and the inability to cheaply adjust the size of that investment, can make that reasonable under Kelly if you think the bet is stable (e.g. that the house can’t go to zero if it’s insured, at least not in any scenario where you care much about that).
Your comment rings my “math applied incorrectly” alarm—I may just be misunderstanding, e.g. you might be motivated by a logarithmic utility function in amount of money made, but that’s a very different thing from the reason we would expect the financial system to be dominated by Kelly-following-financial-entities—so just in case, let me try to explain my understanding of why Kelly is so important, and why it doesn’t obviously seem to be related to the question of whether to start a startup. Any corrections very much appreciated!
Kelly and financial markets
Suppose three investment funds are created in the same year. Let’s say the first fund is badly managed and loses 5% of its capital each year; the second fund gains 5% each year; and the third fund gains 10% each year. After 100 years of this, which of the three will be the most important force in the market? I didn’t specify that they had the same starting capital, but the first fund is down to 0.6% of its start capital, the second fund has increased its capital 130-fold, and the third fund has increased its by a factor of 13,800, so if they didn’t differ by too many orders of magnitude when they started out, the third one beats the others hands-down.
Of course, the growth isn’t really constant in each year. Let’s suppose your capital grows by a factor of r(i) in year i. Then after 100 years it’s grown by a factor of r(1) r(2) … * r(100), obviously, and we’re interested in the fund whose strategy maximizes this number, because after a long enough time, that fund will be the only one left standing. We can write this as
i.e., maximizing the mean of the log growth factor.
Now, imagine that the growth your strategy achieves in a particular year doesn’t depend on the amount of money you have available in that year: if you have $1 million, you’ll buy N shares of ACME Corp, if you have $10 million, you’ll just buy 10*N shares instead. Also assume (much less plausibly—but I’m pretty sure this can be generalized with more difficult math) that the same bets are offered each year, and what happens in one year is statistically independent of what happens in any other year. Then the log growth factors log(r(i)) are independent random variables with the same distribution, so the Law of Large Numbers says that
(1/100)(log(r(1)) + log(r(2)) + … + log(r(100)))
is approximately equal to the expected value of log(r(i)). Thus, after a long time, we expect those funds to dominate the market whose strategy maximizes the expectation of the log of the factor by which they increase their capital in a given year.
From this, you can derive the Kelly criterion by calculus. You can also see that it’s the same criterion as if you only play for a single year, and value the money you have after that year with a logarithmic utility function.
So what about startups?
An important assumption above was that the same bets are available to you each year no matter how much money you happen to have that year. If each year there’s a chance that you’ll lose all your money, that would be terrible, of course, because it’ll happen eventually, and then you are out of the game forever; but barring that, your strategy looks pretty much the same, whether you have $1M or $100M. But if you invest $100K-equivalent in sweat equity in a startup and cash out $10M, you do not tend to re-invest that return by creating a hundred similar startups the next year.
Conversely, suppose your startup fails, and according to some sort of accounting you can be said to have lost 30% of your bankroll in the process. For the above reasoning to apply, not only would you have to start another startup after this (reasonable assumption), but the returns of this next startup, if it succeeds, should be only 70% of the returns your first startup would have yielded—because see, our assumption was that the return on a successful bet is a constant times the amount of money you’ve bet (dividends on 10*N shares vs. dividends on N shares), and you’ve lost 30% of your bankroll, so now you can only be betting 70% of the resources you were betting before.
It seems to me that this makes basically no sense. If you start another startup right after the first one, you’ve gained experience, you’ve gained contacts, and it seems that if anything, you should be able to build a better startup this time. Even if not, it seems strange to say that if in some sense you bet 30% of your personal resources in your first startup, then this should imply that your next startup will be exactly 30% worse than the one before, and the one after that will be worse by exactly 30% again. (And that’s not even taking into account that you probably won’t start enough startups for the Law of Large Numbers to become relevant.)
In conclusion, it seems to me that if the Kelly criterion applies to startups, it must be for a very different reason than why we’d expect to see Kelly-following-financial entities. (Zvi, who has clearly thought about this more than I have, seems to agree with you that it applies in some way, though.) Did that make sense, or did I misunderstand you somehow?
the bankroll of the typical person accepting startup equity in place of cash, the Kelly Criterion may indicate that startups should usually not be more than hobbies for “normal” (non-rich, non-certainly-immortal, declining-utility-in-dollars) humans.
Let’s see… Somewhere Paul Graham says that >90% of startups will fail, so our Kelly odds are 9:1. What’s the return on a won bet? Well, the recent Kaufmann Foundation report on VC funds puts the single best VC funds at an overall return of ~8x but that’s not enough because that implies that we may not even break even if we lost ~9 investments for every 1 investment returning 8! (receiving 8 back on a 9:1 bet)
If startups are negative expected value, the KC is not useful: it presumes bets are positive expected value and the question is what fraction to bet at any time to avoid ruin. I suppose that treating them as lottery tickets and assuming you are risk-seeking might make it useful, but I don’t know how to do that.
Maybe time-value will help. Thinking of a LWer I know, he received the rough equivalent of a year’s salary when the startup ‘won’. But the startup itself took years and naturally wasn’t paying the salary a big competitor might, so it’s not obvious that he was better off in the end, which brings us back to the expected value question.
Yeah, but I don’t think that really applies to startups! (What is ‘the other side’? Are there people who offer shorts on arbitrary startups for less than millions?)
I don’t understand your calculation. Even the best VC funds probably make some losing investments, so to achieve an overall return of 8x, the winning startups must yield more than that.
If startups are negative expected value, the KC is not useful: it presumes bets are positive expected value and the question is what fraction to bet at any time to avoid ruin.
On the contrary, in some sense, that’s when the KC is most useful. The correct amount of money to gamble on losing propositions is 0!
My estimation of startups in general is that startups are a good way for exceptional individuals to capture much of the value they create. The problem is that it’s difficult to tell who is exceptional beforehand, especially if one can only measure sparkle and not grit, and also especially if one has not determined their own level yet.
In that vein, I am cautious about finding cofounders in ways like this.
The major value-add of professional VCs is that they are (should be) better at picking startups than most people. It’s very much possible for 90% of startups to fail while VCs still make money. (For one, successful startups can use much more capital; and the rest of the money is supplied by unsophisticated founders.)
I was under the impression that VCs often had significant industry contacts that the fledgling company would then have access to, and that advice for founders is to not sign a deal with someone who is only offering money. (Of course, that advice given by a connected investor is self-serving, and should be taken with a grain of salt.)
This is beautiful, I really appreciate your giving it a shot to ask for what you want on here even though you’re dubious about getting it. There are a lot of awesome people, some of whom I know about personally, who are browsing through this, and I think seeing these sorts of comments and requests that show someone who is really thinking and realizes how hard start-ups are and is very selective, is likely to bring forth more such people and quality.
My request is that if you do get emails from someone promising and anything good comes out of it, that you please respond back with at least a quick line saying so on this thread—whether or not I do more things like this in the future will depend highly on that sort of feedback, and other people will be much more likely to try what you’re trying if it works for you. Thanks for trying it! :)
Responding (as sort of requested) almost a year later now...
The total outcome of the comments seems to have been educational, with a number of people learning and Zvi raising issues with Kelly that I hadn’t already noticed and helping to educate me, but the ostensible purpose was to “get emails from someone” and so far no one has contacted me by outside channels on the basis of having made the grand parent comment. The lack of networking success on the basis of this comment doesn’t seem like a particularly bad outcome to me in that my goal was mostly to cause education to happen that pays dividends for LWers in general in the semi-long-run :-)
I appreciate your follow up. I couple of things did happen with other projects too:
one is that one of the better versions of Anki did get created—you can see up in the newer comments somewhere, where it was linked by hacker news.
Peter is also collaborating with someone working on his version, although I don’t know whether or not this post had a impact on their collaboration.
I worked for awhile with one of the people Eliezer mentioned.
The backwards kickstarter folks were talking for awhile, and someone ended up working on a similar project with another group—I haven’t followed up with them.
I think its likely that other stuff happened—I only found out about the better-Anki program because I ran into the guy who was behind it at a party. Likewise with my post about starting group houses—I know of several group houses that started that used it as part of their process, but I think only one commented. The co-working post has also been very successful, although not in the way I had anticipated—I don’t know of much in the way of individual partnerships created, but the study hall that started is still going and populated almost 24⁄7, several months later.
To sound a note of caution… I spent a number of years acquiring various kinds of non-monetary capital that are useful for startups. Looking back with my current state of theoretical knowledge and memories, I suspect I may come to see this period as involving too little caution. The key concept acquired between then and now is Kelly Betting.
I still haven’t worked through the applications of this concept to startups in a way that I feel is “settled”, but depending on the precise nature of the risks and rewards and the bankroll of the typical person accepting startup equity in place of cash, the Kelly Criterion may indicate that startups should usually not be more than hobbies for “normal” (non-rich, non-certainly-immortal, declining-utility-in-dollars) humans. Note that if startups are roughly as risky as a simple Kelly calculation says they should be, this might still be cause for concern because most people who raise theory/practice issues with Kelly say that it over invests in risks.
I’m still exploring ways that the theory might line up with reality, but even my limited state of knowledge has caused me to scale back my startup enthusiasm in the last year or so. The math might come out more positive if you value the knowledge capital gained through startup work in the correct way, for example, but that’s particularly tricky to calculate. If anyone else has thoughts on this subject I would love to read or hear them.
For reference, Robin already wrote about Kelly betting to claim that the present era is visibly unstable because most investment firms, and the economy in general, seems not to be engaged in a Kelly strategy at the present time. In some sense, Robin claimed, a financial system not dominated by Kelly-following-financial-entities would probably be a system that has no significantly old Kelly-following-financial-entities, because in the long run they “win” at finance.
Another source on Kelly betting that is directly applicable to startups flows with the “invest in the team, not the idea” dictum. The post “Optimal startup burn rate and the Kelly criterion” is no longer available in the wild but is retained on archive.org and discussed the optimal team size and experimental product cycle given a starting bankroll. (The blog is LaserLike and is not itself down.)
For what its worth, I’m not totally bearish on startups, and sort of have one cooking… I’m just trying to pursue startup stuff with an eye on keeping a bird or 6 in the hand while pursuing startup stuff in parallel. In this vein, if anyone is or knows a solid hardware hacker with RFID experience/interest, especially if they are ethical, planful, world-savey, “rational”, and/or live in (southern?) California, I’d appreciate hearing from you. No particular startup interest or equity tolerance is important—just hardware skills, character, and an interest in educational conversation :-)
I have extensive experience in this realm, including both independently re-deriving Kelly before learning about it and then working extensively with variations of it, in nominally Kelly-optimal conditions. Kelly is only optimal under a very strict set of criteria, and those criteria de facto do not occur in practice. It’s a great guide to the landscape, but a terrible perscription in most situations. Common errors include misunderstanding what counts as a bankroll, inability to access large portions of the real bankroll, changing returns to investment size, the existence of limiting factors, having almost any real utility function, unknown unknowns and edge uncertainty which is almost always correlated, psychological impact and inability to precommit credibly to Kelly, outside perceptions and their impact on your bankroll or utility, not accounting for calculation errors, odds or outcomes that are impacted by bet size, and more.
I may write a top-level post going into more detail (feedback on this idea is appreciated), but here I will deal only with this particular case.
In a start-up, the bankroll definition and potential is one key. Your bankroll includes more than you think, and that’s especially true in a start-up world where you can, even in failure, get more investment and start again, or join someone else’s start-up, or just go back to a day job. Kelly assigns infinite disutility to going broke, and going broke is standard procedure in the startup world. Also, how you take your compensation is largely for motivation and signaling and to keep control of the company, all of which impact the result. In bankroll terms my investing in my own company, and taking $0 other than expenses from my start-up work was madness, but it was clearly the correct play and has paid off handsomely in numerous non-bankroll ways even if no money results!
Going full speed at a startup, even in failure, is often a winning play as you develop connections, reputation, experience, skills and other neat stuff like that, laying the groundwork for future success.
I’d be interested in reading that post! If you do, could you explain more about the grounds on which you’d be applying Kelly to this problem at all, though? I’m somewhat unclear on that—see my other comment in this thread for detail.
In this problem, you’re starting a business, and you can consider that business as a bet, out of which you hope to gain a job, income, investment money from your equity, reputation, experience, and so on, all of which can be abstracted. Alternatively, you can look purely at the equity vs. salary trade-off in the context of Kelly, which as I explained above is deeply flawed. It’s not a great scenario for such calculations, but they can still provide insightful context.
That’s kind of reassuring. I’m just starting to read about Kelly, and my first reaction was “and your knowledge of the final outcome comes from where?”.
It also occurs to me that “Invest in real estate, they aren’t making any more land” is an effort at Kelly prediction, and we all know how well that worked out.
It is a classic mistake to treat your estimates as known expected outcomes when calculating how much to bet. This is one reason why real world gamblers almost always use half Kelly or even quarter Kelly rather than full Kelly.
“Invest in real estate, they aren’t making any more of it” is, in effect, a prediction of the expected returns to investment and/or the reliability of investment. Kelly would advise you on how to take advantage of the expected returns from real estate, once you nailed down your beliefs more carefully. For real estate, Kelly is rather horrified, as it finds many people investing far more money than they have into a single house. That sounds insane when you say it like that! However, a richer understanding of all a person’s assets together with the tax advantages of mortgage interest, and the inability to cheaply adjust the size of that investment, can make that reasonable under Kelly if you think the bet is stable (e.g. that the house can’t go to zero if it’s insured, at least not in any scenario where you care much about that).
I think part of the situation is that naive investors don’t quantify—if real estate is a good investment, they don’t think about how good it might be.
It’s interesting to watch “Kelly” drift in and out of being personified.
Your comment rings my “math applied incorrectly” alarm—I may just be misunderstanding, e.g. you might be motivated by a logarithmic utility function in amount of money made, but that’s a very different thing from the reason we would expect the financial system to be dominated by Kelly-following-financial-entities—so just in case, let me try to explain my understanding of why Kelly is so important, and why it doesn’t obviously seem to be related to the question of whether to start a startup. Any corrections very much appreciated!
Kelly and financial markets
Suppose three investment funds are created in the same year. Let’s say the first fund is badly managed and loses 5% of its capital each year; the second fund gains 5% each year; and the third fund gains 10% each year. After 100 years of this, which of the three will be the most important force in the market? I didn’t specify that they had the same starting capital, but the first fund is down to 0.6% of its start capital, the second fund has increased its capital 130-fold, and the third fund has increased its by a factor of 13,800, so if they didn’t differ by too many orders of magnitude when they started out, the third one beats the others hands-down.
Of course, the growth isn’t really constant in each year. Let’s suppose your capital grows by a factor of r(i) in year i. Then after 100 years it’s grown by a factor of r(1) r(2) … * r(100), obviously, and we’re interested in the fund whose strategy maximizes this number, because after a long enough time, that fund will be the only one left standing. We can write this as
r(1) r(2) … * r(100) = exp(log(r(1)) + log(r(2)) + … + log(r(100)))
and maximizing this number happens to be equivalent to maximizing
(1/100)(log(r(1)) + log(r(2)) + … + log(r(100))),
i.e., maximizing the mean of the log growth factor.
Now, imagine that the growth your strategy achieves in a particular year doesn’t depend on the amount of money you have available in that year: if you have $1 million, you’ll buy N shares of ACME Corp, if you have $10 million, you’ll just buy 10*N shares instead. Also assume (much less plausibly—but I’m pretty sure this can be generalized with more difficult math) that the same bets are offered each year, and what happens in one year is statistically independent of what happens in any other year. Then the log growth factors log(r(i)) are independent random variables with the same distribution, so the Law of Large Numbers says that
(1/100)(log(r(1)) + log(r(2)) + … + log(r(100)))
is approximately equal to the expected value of log(r(i)). Thus, after a long time, we expect those funds to dominate the market whose strategy maximizes the expectation of the log of the factor by which they increase their capital in a given year.
From this, you can derive the Kelly criterion by calculus. You can also see that it’s the same criterion as if you only play for a single year, and value the money you have after that year with a logarithmic utility function.
So what about startups?
An important assumption above was that the same bets are available to you each year no matter how much money you happen to have that year. If each year there’s a chance that you’ll lose all your money, that would be terrible, of course, because it’ll happen eventually, and then you are out of the game forever; but barring that, your strategy looks pretty much the same, whether you have $1M or $100M. But if you invest $100K-equivalent in sweat equity in a startup and cash out $10M, you do not tend to re-invest that return by creating a hundred similar startups the next year.
Conversely, suppose your startup fails, and according to some sort of accounting you can be said to have lost 30% of your bankroll in the process. For the above reasoning to apply, not only would you have to start another startup after this (reasonable assumption), but the returns of this next startup, if it succeeds, should be only 70% of the returns your first startup would have yielded—because see, our assumption was that the return on a successful bet is a constant times the amount of money you’ve bet (dividends on 10*N shares vs. dividends on N shares), and you’ve lost 30% of your bankroll, so now you can only be betting 70% of the resources you were betting before.
It seems to me that this makes basically no sense. If you start another startup right after the first one, you’ve gained experience, you’ve gained contacts, and it seems that if anything, you should be able to build a better startup this time. Even if not, it seems strange to say that if in some sense you bet 30% of your personal resources in your first startup, then this should imply that your next startup will be exactly 30% worse than the one before, and the one after that will be worse by exactly 30% again. (And that’s not even taking into account that you probably won’t start enough startups for the Law of Large Numbers to become relevant.)
In conclusion, it seems to me that if the Kelly criterion applies to startups, it must be for a very different reason than why we’d expect to see Kelly-following-financial entities. (Zvi, who has clearly thought about this more than I have, seems to agree with you that it applies in some way, though.) Did that make sense, or did I misunderstand you somehow?
That was a very good explanation; I found it significantly more illuminating than Wikipedia’s.
I’m not too clear how we would apply KC to startups (as opposed to specific contracts in prediction markets).
Let’s see… Somewhere Paul Graham says that >90% of startups will fail, so our Kelly odds are 9:1. What’s the return on a won bet? Well, the recent Kaufmann Foundation report on VC funds puts the single best VC funds at an overall return of ~8x but that’s not enough because that implies that we may not even break even if we lost ~9 investments for every 1 investment returning 8! (receiving 8 back on a 9:1 bet)
If startups are negative expected value, the KC is not useful: it presumes bets are positive expected value and the question is what fraction to bet at any time to avoid ruin. I suppose that treating them as lottery tickets and assuming you are risk-seeking might make it useful, but I don’t know how to do that.
Maybe time-value will help. Thinking of a LWer I know, he received the rough equivalent of a year’s salary when the startup ‘won’. But the startup itself took years and naturally wasn’t paying the salary a big competitor might, so it’s not obvious that he was better off in the end, which brings us back to the expected value question.
Yeah, I dunno.
KC does apply to negative EV bets. The formula emits a negative allocation (ie “take the other side”).
Yeah, but I don’t think that really applies to startups! (What is ‘the other side’? Are there people who offer shorts on arbitrary startups for less than millions?)
I don’t understand your calculation. Even the best VC funds probably make some losing investments, so to achieve an overall return of 8x, the winning startups must yield more than that.
I did say it doesn’t make a whole lot of sense to me.
On the contrary, in some sense, that’s when the KC is most useful. The correct amount of money to gamble on losing propositions is 0!
My estimation of startups in general is that startups are a good way for exceptional individuals to capture much of the value they create. The problem is that it’s difficult to tell who is exceptional beforehand, especially if one can only measure sparkle and not grit, and also especially if one has not determined their own level yet.
In that vein, I am cautious about finding cofounders in ways like this.
The major value-add of professional VCs is that they are (should be) better at picking startups than most people. It’s very much possible for 90% of startups to fail while VCs still make money. (For one, successful startups can use much more capital; and the rest of the money is supplied by unsophisticated founders.)
I was under the impression that VCs often had significant industry contacts that the fledgling company would then have access to, and that advice for founders is to not sign a deal with someone who is only offering money. (Of course, that advice given by a connected investor is self-serving, and should be taken with a grain of salt.)
This is beautiful, I really appreciate your giving it a shot to ask for what you want on here even though you’re dubious about getting it. There are a lot of awesome people, some of whom I know about personally, who are browsing through this, and I think seeing these sorts of comments and requests that show someone who is really thinking and realizes how hard start-ups are and is very selective, is likely to bring forth more such people and quality.
My request is that if you do get emails from someone promising and anything good comes out of it, that you please respond back with at least a quick line saying so on this thread—whether or not I do more things like this in the future will depend highly on that sort of feedback, and other people will be much more likely to try what you’re trying if it works for you. Thanks for trying it! :)
Thanks for the support! I put the URL and a note in my calendar, so I will probably comment again here with an update on how it worked.
Responding (as sort of requested) almost a year later now...
The total outcome of the comments seems to have been educational, with a number of people learning and Zvi raising issues with Kelly that I hadn’t already noticed and helping to educate me, but the ostensible purpose was to “get emails from someone” and so far no one has contacted me by outside channels on the basis of having made the grand parent comment. The lack of networking success on the basis of this comment doesn’t seem like a particularly bad outcome to me in that my goal was mostly to cause education to happen that pays dividends for LWers in general in the semi-long-run :-)
I appreciate your follow up. I couple of things did happen with other projects too:
one is that one of the better versions of Anki did get created—you can see up in the newer comments somewhere, where it was linked by hacker news.
Peter is also collaborating with someone working on his version, although I don’t know whether or not this post had a impact on their collaboration.
I worked for awhile with one of the people Eliezer mentioned.
The backwards kickstarter folks were talking for awhile, and someone ended up working on a similar project with another group—I haven’t followed up with them.
I think its likely that other stuff happened—I only found out about the better-Anki program because I ran into the guy who was behind it at a party. Likewise with my post about starting group houses—I know of several group houses that started that used it as part of their process, but I think only one commented. The co-working post has also been very successful, although not in the way I had anticipated—I don’t know of much in the way of individual partnerships created, but the study hall that started is still going and populated almost 24⁄7, several months later.