In SiliconValleyStartupLand there are memes that some repeat as if they were absolute truths. One of them is “the first employee of a startup gets screwed.” Sure, and the black guy always dies first in movies. While we are at it, you cannot get pregnant the first time you have sex (yes, some people believe this).

The truth is that being the first employee of a startup could be shitty, or it could also be a great investment of your time and effort. When I say “great investment” I’m not talking about outlier outcomes such as that of Craig Silverstein, Google’s first employee. That’s just winning the lottery several times. For the sake of the argument I’ll stick with the more common case; a startup raises a seed round or even a series A. They hire a few good people, operate for a few years, and exit for a number between 0 (failure) and maybe 100M.

In the worst case scenario, no employees (including the founders) receive a payout at the end of the journey. In the 100M case, the founders are set for life. Employee #1 (let’s call him Joe) makes a nice chunk of change but not enough to “solve the money problem.” If during all that time Joe had been working as hard as the founders while making a shitty salary, he will feel like he got a raw deal. This raises an obvious question: why did Joe take a shitty salary, a comparatively small equity stake, and then proceed to work as hard as a founder? Answer: Joe did not know what he was doing. He sold himself short.

So, without counting on riding a Google (or even an AirBnB or a Heroku), when/how/why is it good to be employee #1? Let’s describe one very specific case:

Bob is relatively young. He just finished college, and he’s working as an engineer for some boring corporation far from the coasts. He’s smart and ambitious, and he’d like to start a company. Maybe he even has an idea, a prototype, a potential cofounder named Pedro. What he doesn’t have is a few months worth of Bay Area living expenses in the bank.

Bob would like to move to the Bay Area with Pedro, make connections, raise money. They’d be burning their savings quickly while learning the Silicon Valley game. It may work, but it would be much harder than for someone who’s already been here for a while. Of course there are ways to solve that problem. Being accepted by an incubator such as YCombinator is one of them. However, most people won’t be that lucky.

In this particular case, being employee #1 of a startup could be the way to go. Bob (and maybe Pedro) could move to Silicon Valley for free, and make a reasonable salary. By reasonable I mean: you can rent an apartment in a decent location, live well, and have disposable income. Any startup with funding should be able to pay you a competitive Bay Area salary. If a startup cannot do that for you, then they need to make you a cofounder.

Bob will also get some equity, which could be 5% of what a founder has if he’s lucky. He should negotiate the best deal he can get, but not place any expectations in the potential value of his stock. He may leave before his first cliff, get diluted in subsequent rounds of funding, and of course the startup could crash and burn after a winter or two. The important thing is what Bob should try to accomplish while at the startup, namely:

1) Learning what being a founder means. He will have a chance to see the struggles of the founders up close, perhaps a window into their decisions and thought processes. He can take notes, imagine what he’d do differently, see how things turn out.

2) Making connections. Bob is in Silicon Valley, so he can attend all sorts of events. He can go talk to customers. He may work with potential partners for the startup. If the startup is doing well, he has all the time in the world to meet people who could become potential cofounders. If it’s not, then he’s getting a better deal than the founders from a financial perspective.

Bob is getting paid to get a crash course in startup life. He’s not committed to the company like a founder, so he has the option to abandon ship if/when things look dire. Also, he gets a lottery ticket as a nice bonus. Put this way, one or two years as employee #1 could be the best option for Bob.

If you’re not in Bob’s situation, then you may not want to take that gig. Just don’t go around preaching absolute truths about how stupid it would be to be employee #1, or about how black guys always die first.

Discuss this post on Hacker News

Whether I like it or not I’m an angel investor, even though I prefer a different label. I don’t want to picture myself as a has-been who doesn’t have the fire to build another company. A lucky bastard who plays Fantasy Football with money that other people would use to educate their kids, buy a car, pay debt. While that may be true, I invest in startups because I need to feel useful. If I were a fulltime money manager, or a VC with a responsibility to LPs, I would have a duty to find investments with the best possible rate of return from a strictly financial standpoint. I would not want to be in that position. I invest in some startups because I genuinely enjoy it. I don’t plan to allocate more than 5% of my portfolio to startups. Losing it all would not be a catastrophe. On the other hand, I get an immediate psychological payoff from the investments I make. I thought about how to maximize the “personal return” I’d like to get from my investments, and I ended up with a few rules (somewhat flexible, subject to change). Here they are:

1) I strongly prefer investing in companies located in San Francisco (city proper, not the Bay Area).

Why? I live in San Francisco, and I enjoy driving on Bay Area freeways as much as having a root canal done by a drunken dentist who hates my family. I like to be able to take public transportation and have meetings with founders, sometimes spontaneously. I may find myself having an IM conversation with a founder, and think it would be best to just grab coffee and scribble on a whiteboard. One of my portfolio companies is about eight blocks from where I live, and another one is fifteen minutes away by Muni. If I believe those meetings could be helpful to the companies, that makes me feel useful. That’s a positive return to me. If I had to drive to Palo Alto or Mountain View, I’d have to subtract two hours of soul-destroying driving from that return.

It turns out that San Francisco is one of the best cities in the world for certain kinds of startups, and there are plenty of them to choose from. If I lived in Chicago, Berlin, or Madrid, I might not invest in startups at all.

2) I invest in companies that I believe are trying to improve the world.

Notice that this is a very subjective statement. Someone might think Facebook or Twitter are improving the world; I don’t. I avoid the entertainment industry, and anything where the revenue stream is based on advertising. I prefer investing in health, transportation, education, and (under some very specific circumstances) finance. Don’t get me wrong, I’m still trying to make money with my investments. This is not charity, and I’m not Bill Gates (although I’m a huge fan of his current work). There are tons of profitable businesses that I believe can improve the world: better and cheaper medical technology, cleaner / less risky transportation, applications to help people avoid financial suicide, etc. My vision of a better world may not coincide with yours. I may be wrong or misguided, who knows. What matters to me is believing that the potential contributions of these companies to the world outweigh their negative externalities.

3) Hey, why didn’t I start that company?

As an electrical engineer and software developer with decades of experience building internet infrastructure, there are certain areas where I believe I could contribute much more than the puny sums that I can invest. If I see a company that I would have wanted to start, I’d like a chance to contribute to its success. I’ve been around Silicon Valley for a while so I’m connected to many engineers and investors whom I deeply respect. Some lawyers, even. Thirty years after writing my first program in Basic I still code for fun, and I doubt I’ll ever stop. I like to analyze data, find relations between variables, extract insights that are sometimes far from obvious or even counterintuitive.

My skills make me useful to a relatively small subset of all startups out there. I recently attended a Demo Day for a well-known incubator. I had the impression that 95% of the startups who presented could not benefit from my investment any more than they would by taking money from a random stranger. For the others, I would be excited to be involved in some form. I’m not looking to become an employee of a company, and I like having the option (but not the obligation) to contribute work. When I make an investment that’s financially meaningful to me (probably more than to the startup), my brain automatically starts paying attention to its market, competitors, technology, introductions I could make, plugins or applications I would write, etc.

I wrote this post because I felt like it, but hopefully I did a decent job at selling myself as a potential investor. If your seed-stage company fits the criteria above, please contact me.

By the way, don’t follow me on Twitter

Warning: what you are about to read is mostly speculation. Take with a grain of salt. Don’t trust my numbers blindly. Find your own data.

The suicide rate in the United States is twelve per one hundred thousand inhabitants. That means that every year, around 38,000 people kill themselves. About one hundred per day. Of course, not all suicides are equal. For example, some are the result of a carefully planned decision. Others are not so planned. Perhaps they are not spontaneous, but they are more preventable. I’m not going to claim expertise in the subject, most of what I know comes from conversations with my father; he was a psychiatrist who treated suicidal patients for decades.

Continuing the line of my recent posts, I decided to plot suicide rates vs. household gun ownership by US states:

Sources:

• Suicide rates by state.
• Percentage of households with guns by state.

The above chart surprised me. The correlation between the two variables is pretty high (0.6). What’s going on here? Here’s the first hypothesis that comes to my mind: suicidal people with easy access to guns are more likely to actually kill themselves.

I can imagine a scenario in which someone crosses an emotional threshold, grabs a gun from a drawer and kills himself (the majority are men). In a parallel world there is no gun in the drawer, this person would not be able to commit suicide so easily. Perhaps he would go out and drive his car into a wall, but this would give him more time to reconsider. The time elapsed between deciding to shoot oneself and being dead can be very short.

If you believe that these people should not die, then you could use this hypothesis to make the case for gun control. The majority of US gun deaths are in fact suicides, and firearm suicide is by far the most common method, so this is not an insignificant problem.

Of course there are other possible interpretations of the data. Maybe people in certain states are more predisposed to suicide AND to own guns? Occam’s razor would say no, but it’s worth a look. On one extreme we see states like Montana, Wyoming and Alaska. On the other, New York, New Jersey, Maryland. There are certainly demographic differences across these states: population density, income levels, etc. Could Montanans be three times more suicidal than New Yorkers due to those factors? I don’t know, and I can’t rule it out.

It’s also interesting to observe what happens across countries. I scraped Wikipedia’s List of countries by suicide rate and plotted that against Number of guns per capita by country:

In this case, the correlation is almost nonexistent (0.08). Of course, no other country comes close to the US in guns per capita so this is not a complete surprise. Also, the data is different: this is total guns per capita, not percentage of households with guns.

At this point, all I have is the question: would it be possible to prevent thousands of deaths every year by making guns more inaccessible to suicidal individuals? Would it be worth the effort? I wish I could offer answers to these questions, but I’m just one guy with some free time. All my data and “insights” come from Google, Wikipedia, and R. What data is out there that I could be missing?

Final note: this is a very sensitive topic. If you are going to comment on this post, please be reasonable and rational.

I decided to plot country murder rates against gross domestic product per capita, and also against Gini coefficients. I scraped the data from these sources (.csv files at the end of the post if you’d like to use them).

• GDP per capita (Wikipedia)

• Intentional Homicide Rates (Wikipedia)
• Gini coefficients (World Bank)

This is what Murders vs GDP per capita look like. The Pearson correlation in the chart (r) is -0.32.

Murder rates vs. Gini indexes. r = 0.5

This the same chart as above, restricted to countries in the Organization for Economic Co-operation and Development (OECD):

And the same chart, zoomed in (Mexico and Chile are outside):

Finally, the data. One caveat: if you look at the World Bank spreadsheet, you will see that not all countries have current Gini statistics. I used the most recent one for each country. These charts might look different if all countries were current.

• murders.csv
• gini.csv
• gdp.csv
• oecd.csv (from Mark Reid).

Now, do I dare draw any conclusions from these charts? We see the correlations, but what do they mean? I see many poor countries with high murder rates and high inequality. We could speculate that the problem for those countries is the failure of rule of law. It’s even more tempting to guess what’s happening in the last chart. Developed countries like the US make it easier for individuals to become very wealthy, and don’t offer a comparatively good safety net for the relatively poor. This incentivizes people to work hard, start businesses, avoid poverty. Obviously not everyone will succeed. Perhaps the price to pay for this model is a higher murder rate.

Of course it would not be serious to arrive at that conclusion from these hasty charts, but I can pose the question. Feel free to play with the data, and to suggest other variables to analyze.

Speaking in Newtown, CT yesterday, President Obama said:

We can’t tolerate this anymore.  These tragedies must end.  And to end them, we must change.  We will be told that the causes of such violence are complex, and that is true.  [...]  Surely, we can do better than this.  If there is even one step we can take to save another child, or another parent, or another town, from the grief [...] then surely we have an obligation to try.

It was a comforting speech for the victims of a tragedy, so it would be unfair to criticize the arguments from the point of view of logic. However, it is worth analyzing the issue of mass shootings as a problem that might be addressable with public policy.

I would start by measuring the magnitude of mass shootings as a problem. How does it compare to other issues such as preventable diseases, regular crime, terrorism? I searched for data, and found out that in the past 30 years, 543 people have been killed in 70 mass shootings. That’s an average of 18 deaths per year. For comparison, three times as many die from lightning strikes.

The New Republic article linked in the previous paragraph states “I can’t say exactly why mass shootings have become such a menace over the past few years, and especially in 2012.” Given the low numbers, it’s likely that it is just a random fluctuation without statistical significance.

To put things in perspective again, half a million Americans die every year from tobacco use. Two hundred thousand die from medical errors. Those numbers are large enough that it’s possible to track changes with statistical significance, and evaluate the effect of public policy. There must be a fair amount of low-hanging fruit. For example, it’s feasible that a 100% tax on the price of cigarettes would save thousands of lives ever year. Why is this not attempted? Probably because the special interest group that controls tobacco sales is powerful enough to stop it.

For mass killings, the numbers are already so low that the logical question would be: is it worth doing anything to try to reduce even more the chance of mass killings? What could be the undesired side effects of implementing policies to that effect? For example, let’s say that someone came up with a vaccine that guaranteed that a child who received would never be a mass killer. However, one child in 100,000 dies from an adverse reaction to the vaccine. Clearly the vaccine itself would cause more deaths than mass killings, so it’s a net negative if we are trying to minimize unnecessary deaths.

At this point, I have to disagree with Barack Obama. I don’t think we have the obligation to try to reduce the incidence of mass killings because there are high chances that an intervention would be iatrogenic: the cure be worse than the disease. This is not a politically correct thing to say, so you won’t hear politicians say it. That doesn’t mean our legislators will do anything, of course. Mass killings are as inevitable as lightning deaths, and they will continue to be news precisely because they are infrequent and horrible.

Who knows, maybe doing nothing is the right thing. There are medical procedures that are not recommended anymore because they have potential complications, and they offer no measurable benefits when compared with inaction.

What makes matters more complicated is that mass shootings bring up the issue of gun ownership in the US. If this killing had been a bombing nobody would be talking about gun control. However, many people who normally don’t think about gun crime are emotionally moved by mass shootings. From a logical viewpoint, we should be more concerned with gun crime in general. If gun crime is a significant problem, then gun control could be a solution to that problem. Surely gun control would have side effects, but it’s likely that those side effects would not offset the gains.

So, is gun crime a problem? In the US there are about 3 gun homicides for every 100,000 inhabitants every year. That means about ten thousand people are shot to death in the country. For the average American, the odds of being murdered with a gun are 1,000 times higher than those of dying in a mass shooting. His/her odds of dying of cancer are “only” 60 times higher than those of being murdered with a gun, so the problem is not insignificant.

Let’s say that we believe that the cost of implementing gun control is less than the benefits. Perhaps we can save four thousand lives every year if we make it harder for criminals to obtain guns. More importantly, we can do it without taking any resources away from the fight against the main causes of death: cancer, heart disease, and accidents. How would we go about it?

The US is a very unique place when it comes to guns. As of 2009 there were 310 million non-military firearms in the country. It is possible to make it illegal to produce and buy new ones, but what do we do with the existing ones? What kinds of imbalances would be created if those who would only use guns to protect their property could not own them? What if most potential murderers kept their guns, and all the guns turned in (say, for cash or tax breaks) were the ones less likely to murder anyone? What kind of black markets might arise for guns and bullets?

I’m not even going to try to answer those questions, because they are extremely complex. I personally hate guns. I have never owned or even fired one. I wish they didn’t exist, but they do. However, believing that gun control would immediately save lives is magical thinking. It might work in the long run if implemented correctly for the US, but it when it comes to reducing murders it would not be a silver bullet (pun intended).

The other issue that many bring up when mass killings happen is mental illness. There is little question that those responsible for mass killings fit most definitions of “mentally ill.” However, they are a minuscule minority. At the same time, mental illness is a horrible condition that causes an enormous amount of suffering. It affects millions, and there is no question that it would be a good idea to address it through public policy. This might have the bonus of preventing the odd massacre in which the potential perpetrator could have been under treatment for a condition such as paranoid schizophrenia. However, not all sufferers of this condition would seek treatment. Norway has one of the best healthcare systems in the world, and that didn’t stop Anders Behring from killing 77 people. Some conditions are asymptomatic for a long time, and manifest themselves too quickly. “He seemed like such a nice, quiet guy. I don’t know why he flipped out.”

If there is one point I’d like to make with this long rant is that public policy should not be dictated by emotions. Minimizing unnecessary deaths and appeasing public opinion are different things. Most human beings do not understand concepts such as statistics or iatrogenics, so they will clamor for immediate feel-good action. I wish I lived in a world where people (or at least leaders) would always analyze issues rationally. Where they would act to maximize public good instead of their chances of being re-elected. All I can do is ask my readers to try to understand all sides of a delicate issue before forming an opinion, like I attempted to do in this post.

Discuss on Hacker News (please be civil!)

I took the data and the script from @mdreid‘s blog post about Gun Deaths vs. Gun Ownership, and plotted Total Murder Rates (murders.csv) vs. Gun Ownership out of curiosity. The results are interesting, draw your own conclusions.

For all countries:

For OECD countries:

Zoomed in without Mexico and the US:

One caveat: the comparison between “countries” is somewhat arbitrary. The population range for the countries in this set spans two orders of magnitude: millions to hundreds of millions. Their ethnicities, geographies and densities are different as well. We must be careful in drawing conclusions when comparing small, relatively homogeneous countries such as Finland against a population with the size and heterogeneity of the US.

I just read a blog post entitled “You can do it alone” as well as the ensuing discussion on Hacker News. Paul Graham says:

You can certainly start a business without a cofounder. What’s hard to do, empirically, is to start one that gets really big.

Well, it’s always hard to start a business that gets really big regardless of the number of founders. Paul doesn’t address the implied question: how much harder would it be for a single founder?

Regardless of the answer, I know first hand that it’s possible to be a successful single founder of a startup. Obviously it has advantages and disadvantages when compared to having co-founders: more effort, more potential reward, always on call, no safety net, etc. Ultimately it’s a personal decision, and I won’t give a generic opinion (although I have no interest in ever doing it again).

However, investors have their own reasons to prefer startups with more than one founder. These reasons are not always obvious to founders, or even to investors themselves in some cases. Let me put on my dunce investor hat and tell you a couple of mine:

1) Single point of failure. As someone who built network infrastructure for a living, I tried to avoid having one component that would take down a whole system if it failed. When a startup depends on a single person, it is much more likely to die if this person gets abducted by aliens (unless it’s just for a couple of days, and the memories of the experiments are erased. But I digress). I often wondered what would happened to IndexTank if I disappeared, and I believe it’s very unlikely that it would have survived. Two or more co-founders are like having your online business running on several availability zones of a cloud provider. I was like the US-East (N. Virginia) AWS data center for IndexTank. We eventually distributed the service across regions, but I couldn’t clone myself.

2) Higher motivation for an early exit, or not selling. If a company with three co-founders needs to sell for X so that they all feel they’ve “solved the money problem,” then one of those founders would be happy to sell for X/3. This is clearly a risk for investors; it lowers the expected value of the investment even if the companies prospects no different than if it had multiple founders. The converse is also true: if the single founder happens to be a megalomaniac world overtaker, then it will be harder to convince him to sell even when it would represent an excellent return for investors.

To sum it up, a startup with a single founder is a riskier investment, and there is no reason to believe the return will compensate for the risk. It follows that rational investors must try to convince a single founder to get a co-founder.

This is just one more example of ways in which investors and founders can have misaligned motivations. Being honest and open about this issue is good for both parties.

If you use Twitter or Facebook, you may occasionally see status updates that look like: “I crushed a 7.2 mi run with a pace of 7’24″ with Nike+ Running App. #nikeplus.” About a month ago I started collecting those tweets into a database, to see what interesting stats I could extract. Here are the results.

I collected about 300k tweets, of which about 85k had both the distance and the pace of the run. Some were in miles and some in kilometers, so I normalized everything to the metric system. I cleaned up some obvious errors or misuses of the system, e.g. people who “ran” at inhuman speeds such as 50 mph. Cheetahs . I used the remaining data to plot a few charts. The first one is a histogram of distances people ran, split into weekdays and weekends:

A few insights from this chart:

• As expected, longer distances quickly become infrequent.
• People run longer on weekends. In fact, the average distance for a weekend run is 8.75 km compared with 6.47 km on weekdays.
• Certain distances seem to be particularly popular during weekends, and they look like typical race lengths: 10k, 16k (10 miles), the half marathon and the marathon.

Here is a chart highlighting the difference between weekends and weekdays. For the comparison I normalized both datasets as if I had 100k runs of each, even though obviously I collected more weekday data than weekend.

How about speeds? I tried to see if people run faster on weekends, it turns out that on average they don’t. I did expect the run length to make a difference in speeds, and it does. Here are the speeds for 5k and 10k runs, 5k runs are obviously a little faster on average.

The average speed for people who track their runs with #nikeplus seems to be around 10 or 11 km/h, which is a bit slower than I had guessed. Of course, I have no idea if this self-selected group of people who share their runs on the internet is representative of all runners. However, if you’ve ever run a popular race this curve will seem very familiar to you: the middle of the pack is always crowded, the elite athletes are few and spread out. Same for the slow runner / walkers who finish as the roads are being reopened to traffic.Can you think of more insights you would extract from the data? My code is on Github if you’d like to play with it.

This morning I saw the following headline on a Wall Street Journal blog:

Women Executives Make Venture-Backed Companies More Successful: Study

That’s an interesting assertion, so I read the study to see how the authors had arrived at that conclusion:

in comparing successful versus unsuccessful companies, the overall median proportion of female executives is 7.1% and 3.1%, respectively, demonstrating the value that having more females can potentially bring to a management team

This is a questionable paragraph. For the sake of the argument, let’s suppose the study said this:

“In comparing successful versus unsuccessful companies, the overall median proportion of Porsches in the parking lot is 7.1% and 3.1% respectively, demonstrating the value that having more Porsches can potentially bring to a management team.”

Even though Dilbert’s boss might use this as an excuse to ask the execs to buy him a German car, Porsches are most likely a consequence of success. Therefore, the presence of Porsches in the parking lot doesn’t demonstrate that they add value. All it does is show a correlation.

Note that I’m not suggesting that this is the case with women executives! The Porsches in the parking lot are a caricature example to point out the flaw in the conclusion. Another paragraph makes the bias more evident:

The thesis for this paper claimed that having a higher proportion of female executives at venture-backed start-ups improves the ultimate success of the company

If you read the paper, you will find that the data doesn’t support that assertion. It is true that companies with more women are more successful. It doesn’t follow that the women improve the ultimate success of the company. The honest truth is that we don’t know what makes the companies more successful, and the authors blithely jump to their desired conclusion. Let’s look at other plausible explanations consistent with the results:

- In baseball, it is known that having the best players is strongly correlated with success. It would be reasonable to suggest that the same could apply to venture-backed startups. What if some companies are more likely to hire men rather than women, even if those men are not as qualified for their jobs? Those companies would be at a statistical disadvantage with respect to those who hire the best person regardless of gender. In this case, the title of the study could be “Discrimination Makes Companies More Likely to Fail.”

- It’s also true that most companies are started by men. From the study:

1.3% of privately held companies have a female founder, 6.5% have a female CEO, and 20% have one or more female C-level executives. The most common positions held by female executives were within Sales & Marketing roles, accounting for 27% of the total population sample.

Now, let’s look at a typical company started by men. Let’s assume that it’s relatively likely that the company will fail before hiring a female executive. In this case, we are looking at survivor bias: the companies that hired female executives were already more successful than most. Let’s also suppose that Sales & Marketing executives are only needed by companies that are relatively advanced in terms of product/market fit, and that many companies fail before getting to that stage. This would add even more survivor bias.

Note that I’m not making any assertions about whether the above explanations are true or false. I’m simply showing that they would be consistent with the data analyzed by the study, and that they have not been ruled out.

The sad thing about bad science and journalism of this sort is that it does not help to create a more egalitarian society, or to right a wrong. Instead of being honest and wondering what’s missing from companies that hire fewer women, it irresponsibly asserts that hiring women executives will make a company more successful.

I humbly ask the authors of the study to revise their hypothesis, and to try to get to the bottom of the issue. For example, how successful are companies at the stage in which women are hired as executives? Is it possible that successful companies are more attractive to female executives than unsuccessful ones? Perhaps successful companies have a higher interest in hiring women as executives?

If you have any other questions or hypotheses, I’m interested in hearing them.

Hacker News discussion of this post here.

This weekend I ran a poll using Google Consumer Surveys. Google assures me that the respondents represent the “US Internet population.” Here are two questions I asked:

• Do you you have a Facebook Account?
• Do you have a Twitter Account?

These are the results for the first question:

Full results and insights for the Facebook question

And for the second:

Full results for the Twitter question

Some interesting insights:

- For Facebook, women said yes more than men (48% and 37%, respectively). That’s a significant difference, even taking into account the margin of error. Is Facebook really that much more popular among women?

- The 35-44 age group had the most positive responses (48%). The 18-24 group only had 27%. Is Facebook losing popularity among the college-age population? Are they moving on to something else?

Overall, I was quite impressed with Google’s survey tool. What kinds of questions would you ask?

 Hacker News discussion of this post.