Those 8 years were painful. To make money, I worked as a bartender, an LSAT test prep instructor, as an adjunct law professor at a law school that was so bad it doesn’t exist anymore. I remember 4am at the bar in Chicago where I worked, cleaning up some patron’s puke off the floor, and thinking: I need to figure something else out.
All the time I was trying to find an idea for a startup. I still had the lawyer bit flipped on so lots of things I tried had a legal/regulatory bent. That was definitely a blind spot that held me back for a while.
The fun YC-related story on the founding of Cloudflare is that, before YC, Paul Graham used to host a conference called the “MIT Anti-Spam Conference.” He invited me the second year of the conference (2003, I think) to give a talk on how to write effective anti-spam laws. The very technical crowd was polite to the lawyer. I met a ton of interesting people, many of whom played outsized roles in machine learning over the next few years, including John Graham-Cumming, now Cloudflare’s CTO. Paul invited me back the following year saying I should do something similar.
I was pretty sure the audience wouldn’t tolerate the lawyer giving another talk about regulation, so I went to a young engineer on the team of the (bad) startup I was working on and suggested we build a system to track how spammers scrape your email addresses. He agreed to build the backend if I built the front end (which I largely stole from the hot startup of the time: LinkedIn). That turned into Project Honey Pot, which I gave a talk on at Paul’s conference. Project Honey Pot gave the initial seed of an idea that turned into Cloudflare. And the young engineer was Lee Holloway who cofounded Cloudflare with me and Michelle Zatlyn.
Lesson to me has always been even in times where you don’t feel like you’re making forward progress in your life and career, find ways to stay involved with interesting people and projects and chances are they’ll pay dividends in ways you don’t expect later in life.
I clearly remember walking back to Paul’s house in Cambridge after the 2004 conference where I’d presented Project Honey Pot. I believe he and Jessica had relatively recently started dating. They were talking about startups and how people didn’t understand how they worked. Paul suggested they should teach a class at MIT. And that, of course, is what later turned into YC.
There were other dramatic events that evening in Cambridge that I think sharpened all our minds and made us appreciate there’s no time like the present, but I’ll leave that story for another day.
Basically, intelligent behavior is optimizing for "future asymptotic entropy" vs maximizing any immediate value. How intelligent a system is then become a measure of how far in the future it can model and optimize entropy effectively for.
> They're burning almost $1 billion a year and they have no good solutions to this
Maybe they should have something to show for this $1B/year and take a cut of this $250B+ industry to cover the costs? They appear to have about %30 market share, so they need to capture less than %2 of the value created with their tool to break even and if they can't do that or they are providing tech for the less than average profitable part of the industry they should shift focus or reduce costs.
AFAIK it's only natural for businesses to go out of business if they can't capture more value than they consume.
In almost 20 years I've learned that, at least to me, the most challenging group to manage are mid-level developers.
Juniors don't have a lot of experience with complex code, so they just make simple code which I can understand with a glance.
Mid-level developers are often into trying new stuff and fall in love with complex solutions, so the code isn't really easy to understand, but damn if it isn't interesting, full of crazy new libraries, patterns and ideas.
Seniors have a lot of experience with complex code, so they just make simple code which I can understand with a glance.
The folks who are telling you you’re wrong don’t understand Nyquist’s criterion very well. Curse those undergrad courses for only effectively teaching about Nyquist at baseband frequencies.
You can sample 100MHz of bandwidth at 1GHz just as you describe at 210MSPS. You’ll get everything in the 950-1050MHz band.
Trouble is, without an antialiasing filter, you’ll get every other band that’s a multiple of that sampling rate. The Nyquist criterion works at every multiple of the sampling frequency.
Bandpass filter your analog input appropriately from 950-1050MHz and you’re golden.
This is the way nearly every commodity Wi-Fi chip downsamples 2.4/5GHz raw RF. Sigma-delta ADCs are cheap, fast, and space efficient for die area using this method.
"In signal processing, undersampling or bandpass sampling is a technique where one samples a bandpass-filtered signal at a sample rate below its Nyquist rate (twice the upper cutoff frequency), but is still able to reconstruct the signal.
When one undersamples a bandpass signal, the samples are indistinguishable from the samples of a low-frequency alias of the high-frequency signal. Such sampling is also known as bandpass sampling, harmonic sampling, IF sampling, and direct IF-to-digital conversion."
Truth is, and this applies to all companies regardless of size, is that you don't have to be first, best, biggest, fastest, or most well-known in order to win market share that out-paces your investment. The AI pie is going to be very, very big. To estimate this size, let's take McKinseys rough estimates of job displacement (~30% of ~60% of jobs, ~20% of work) and use that to estimate the actualized [US, apologies] GDP that can at some point be attributed to AI: it is in the 4-5 trillion range using today's figures.
To say a market that large will be owned by only 4-5 companies doesn't make sense. Let's take the PC market for example: there are roughly 6 companies that make up ~80% of the market, sure. However, let's look at a tiny participant compared to the total market (~65B): iBuyPower at rank #77 had sales of 40MM or 0.06% (small, expected) of the market with a much smaller capital investment. If look at this percent compared to 5T, we would be at 3B. While the 5B investment stated in the headline could result in a lower ranking and smaller share, the point stands that there is still a lot of money to be made on the long tail. Even if Anthropic fails, there will be other companies with similar infusions that succeed.
Matt Levine is fond of this highly relevant quote by Bagehot: “Every banker knows that if he has to prove that he is worthy of credit, however good may be his arguments, in fact his credit is gone.”
It seems that CEOs of banks haven't learned anything since 1873 when this was observed.
A smart man once said, "I'd rather be a hypocrite than the same person forever." It was Adam Horovitz, of Beastie Boys, when confronted about going from sexism in their early content to defending gender equality later in life.
I wrote a long response to this but accidentally refreshed my tab, so you're getting an abbreviated response = /
I can give you one of my favorite examples. I have a pretty intense job, and I've struggled to some degree with the way stress eats into both my work productivity and my well-being after work. I wrote this script to mitigate the bouts of workday akrasia that induce me to almost-unconsciously procrastinate, as well as the unfortunate habit of checking work email/Slack after work hours or while on breaks (one of the pitfalls of not physically separating my work and recreational machines).
I use a simple launcher app called gmrun, which allows defining custom protocol prefixes. I've defined a few of these protocols, but my favorite is "m:", which switches "modes" on my laptop. Appending a prefix-string of either "work", "rec", or "all" rewrites my i3 config file to switch to the corresponding "mode" by selectively disabling a set of switch-to-workspace keybindings. It's about 100 lines of straightforward Python code incl docs and newlines, took me half an hour, and it paid for the time I put into it in less than a week. Probably a _dozen_ times a day, I catch myself trying to switch to the workspace that has my messenger apps or personal browser windows, and disabling the keybinding is enough to short-circuit the stress-driven impulse to distract and procrastinate and remember that I am trying to do focused work. It works very similarly for checking my email/Slack after work hours, something I almost never do now for the same reasons.
This is pretty tuned to my situation, OS setup, and personality, but that's pretty much the point: I'm extremely spoiled by Linux, i3, etc due to having a system that's been custom-fitted to my every need every moment of my computing life since late high school. If there's a rough edge, I sand it; if there's an optimization opportunity, I take it (if the ROI seems clearly worth it).
Not to get on my soapbox, but it saddens me a little that so many people I talk to, particularly technical ones, have become disconnected from just how many affordances general-purpose computers can offer without ever being _forced_ to avoid choosing the ease of a one-size-fits-all approach.
For my own startup, I built a small cluster of 17 servers for just beneath $55K, and that had a month-to-month expense of $600 placed in a co-lo. In comparison, the same setup at AWS would be $96K per month. And it is not hard, easy in many ways. Do not be fooled, the cloud companies are peddling is an expensive scam.
Bob starts with 11 units of utility. Fred starts with 2. It costs 1 unit of utility to exist. Each of Bob and Fred invest their remaining utility in the utility market, which grows at 10% per year regardless of what either of them do. 25 years later, Bob has 109 units of utility, and Fred has roughly 12 units of utility. At the beginning of this thought experiment, Bob had 5.5x the utility units of Fred. At the end, he had more than 9x.
This is a simple thought experiment that I hope illuminates something important: in an economy where there is year over year growth, inequality grows by default as a function of exposure to the market. Here, Bob starts with more and can be more exposed to the market. In this example, Bob started with 5.5x more assets - but in America today, the top 10% of households have a median net worth of $1.6m, and the 40th-60th percentile of households have a median net worth of $88k, a multiplier of 18x (note: this data is from 2016).
Most Americans have little to no exposure to the market, while the richest 10% own 84% of stocks. There are many factors driving inequality, and I don’t think anyone would argue that some people are more economically productive than others. But it’s not the case that inequality in the United States is purely a function of hard work by talented people - there are very significant structural factors.
My advice is that if components need to release together, then they ought to be in the same repo. I'd probably go further and say that if you just think components might need to release together then they should go in the same repo, because you can in fact pretty easily manage projects with different release schedules from the same repo if you really need to.
On the other hand if you've got a whole bunch of components in different repos which need to release together it suddenly becomes a real pain.
If you've got components that will never need to release together, then of course you can stick them in different repositories. But if you do this and you want to share common code between the repositories then you will need to manage that code with some sort of robust versioning system, and robust versioning systems are hard. Only do something like that when the value is high enough to justify the overhead. If you're in a startup, chances are very good that the value is not high enough.
As a final observation, you can split big repositories into smaller ones quite easily (in Git anyway) but sticking small repositories together into a bigger one is a lot harder. So start out with a monorepo and only split smaller repositories out when it's clear that it really makes sense.
One of the first articles I remember reading on HN was back in 2009. The gist of the article was that you shouldn’t praise your kids for being smart, praise them when they work hard. Rewarding hard work will better serve them in the long run since being smart will plateau at some point.
I have a 9 and 11 year old and I still bristle a little bit when my mom says y’all are so smart.
All the time I was trying to find an idea for a startup. I still had the lawyer bit flipped on so lots of things I tried had a legal/regulatory bent. That was definitely a blind spot that held me back for a while.
The fun YC-related story on the founding of Cloudflare is that, before YC, Paul Graham used to host a conference called the “MIT Anti-Spam Conference.” He invited me the second year of the conference (2003, I think) to give a talk on how to write effective anti-spam laws. The very technical crowd was polite to the lawyer. I met a ton of interesting people, many of whom played outsized roles in machine learning over the next few years, including John Graham-Cumming, now Cloudflare’s CTO. Paul invited me back the following year saying I should do something similar.
I was pretty sure the audience wouldn’t tolerate the lawyer giving another talk about regulation, so I went to a young engineer on the team of the (bad) startup I was working on and suggested we build a system to track how spammers scrape your email addresses. He agreed to build the backend if I built the front end (which I largely stole from the hot startup of the time: LinkedIn). That turned into Project Honey Pot, which I gave a talk on at Paul’s conference. Project Honey Pot gave the initial seed of an idea that turned into Cloudflare. And the young engineer was Lee Holloway who cofounded Cloudflare with me and Michelle Zatlyn.
Lesson to me has always been even in times where you don’t feel like you’re making forward progress in your life and career, find ways to stay involved with interesting people and projects and chances are they’ll pay dividends in ways you don’t expect later in life.
I clearly remember walking back to Paul’s house in Cambridge after the 2004 conference where I’d presented Project Honey Pot. I believe he and Jessica had relatively recently started dating. They were talking about startups and how people didn’t understand how they worked. Paul suggested they should teach a class at MIT. And that, of course, is what later turned into YC.
There were other dramatic events that evening in Cambridge that I think sharpened all our minds and made us appreciate there’s no time like the present, but I’ll leave that story for another day.