sarchertech

Those numbers can be misleading though.

If your average per request in the application layer is say 20ms. Your p50 is probably 10-15ms and your p99 is probably something like 80ms. p99.9 is probably a good bit higher than that.

If your site is highly interactive, everyone using it is going to regularly run into actions that take long enough that they notice them, and it won’t feel snappy.

Let’s say you went all out and wrote the application layer in C with purely static allocation. You could easily see a p50 around 1-2ms and a p99 of 3-5ms. (This is obviously dependent on the app).

Even with an average time spent waiting in the database of 80ms, you’ve already made a noticeable difference.

That’s not even mentioning the biggest impact, which is that you can likely get by with far fewer application servers.

Now does it make even more sense to optimize your queries? Yes. Definitely. But with faster application stack you can start moving more things into the application layer and out of the database which is generally harder to scale.

And if you have or can build endpoints that don’t hit your database at all, those will actually be 10x faster than before every time.

You’re making my argument for me. The percentage of people who are actively trying to get into FAANG but don’t is higher than the percentage of people actively trying to become doctors.

It’s more selective. So comparing FAANG salaries to the average doctor salary isn’t useful. To find something equally selective, you’d need to pick a higher paid subset of doctors.

>Some reactors we operate today are older than the oldest people on the planet!

That is not correct.

> At high interest rates, that debt can easily grow by hundreds of thousands of dollars while you complete a residency program.

Sure. But that’s not what you said. You said you had many fiends that graduated med school with $500k-$750k in debt. I think you were lying or your definition of many was highly exaggerated.

> That is simply not enough to pay the cost of living in a state like Massachusetts

$58k is the national average. Not the average in a high cost of living area like Massachusetts.

> My main point is that training to become a doctor carries so much financial risk that it selects against folks from poor socioeconomic backgrounds that would otherwise make great physicians.

There is almost zero financial risk.

Eventual graduation rate is 96%. Eventual match rate is around 99%.

Are there doctors that could have make more money going into finance sure. Are there doctors who are financially ruined, not meaningfully.

>In 2018 the AAMC published a study showing that 51% of medical school matriculants were from families in the top quintile for family income

1. Doctors kids are more likely to become doctors.

2. High income is correlated with intelligence and intelligence is partially heritable.

3. Kids from high income families are more likely to have extended family and friends who are editors who encourage them to become doctors.

4. Med school requires college and college and children from income families are much more likely to have college degrees.

5. Medical school entrance is competitive and high income kids are much more likely to go to better colleges.

6. High income kids are much more likely to have higher grades in college because they don’t have to work.

7. High income kids are much more likely to go to better high schools which impacts what college they get into and how well they do there.

The list goes on and on. The cost of medical school is so far down that list.

Sure it is. But a less well trained cheaper doctor looks almost exactly like a PA.

Sure but I don’t think there are 10x as many people competing to become doctors than there are competing for FAANG jobs.

95% chance that the practice you are referring to isn’t ran by the doctor, so they have nothing to do with the way the business is ran.

There are 10x more physicians than FAANG developers in the US.

There are 10x more physicians in the US than there are FAANG developers in the US though.

If you want to compare FAANG engineers to doctors the most accurate comparison is to the top 10%.

Those developers are almost all concentrated in extremely high cost of living cities as well.

Physicians also get special loan programs, better insurance rates etc…

I’m sure there are some people who are put off by that but

The average med school debt is half that and only 30% of borrowers end up owning $300k or more.

Fewer than 1% of us med school graduates never find a slot. And that includes people who start families, move into industry etc and voluntarily leave.

The bottleneck is residency slots not med school slots.

My wife and most of our friends are physicians and I don’t know anyone with $750k in debt.

The average debt is a little over $200k. Only 30% of graduates have over $300k in debt and they are considered high debt graduates.

Family Medicine salaries are above $200k in every state in the nation for full time doctors.

None of the doctors I know come from families with generational wealth.

Here is the nationwide average for resident salaries by year and its higher in higher cost of living areas.

Program year 1—$68,166.

Program year 2—$70,499.

Program year 3—$73,301.

Program year 4—$77,593.

Program year 5—$81,807.

Program year 6—$84,744.

Program year 7—$89,187.

Program year 8—$94,215.

Your entire picture is inaccurate.

Very few people make it into med school who can’t make through.

Also the bottleneck is residency slots, so even if this is the case, it wouldn’t change anything.

You mean they can’t get an undergraduate degree. That’s a different problem.

Many of the programs you listed don’t cut any time off. They’re just a special pipeline program that can help you get into med school.

Of the ones that do save time, most cut 1 year off not 2. And they do it by having students take more than a full time load during undergrad.

It’s essentially the same thing as taking an extra class or 2 every semester so you can finish undergrad in 3 years instead of 4.

I randomly sample 15 of the programs listed there and 14 were 8 year programs. Only 1 had an optional 7 year program (if you were willing to take more than full time load or go to school in summmer). And there were no 6 year programs.

We already have a system for cheaper doctors.

It’s called physicians assistants and nurse practitioners. They are essentially exactly what’s you’re talking about. They make less and they have less training.

In most countries that do this training is longer which that total training time is only 1-2 years shorter.

So you’re doing a few things.

1. Moving more training from cheaper colleges to more expensive medical schools.

2. Moving the filter from undergrad to medical school

3. There is no national curriculum in US high schools, so essentially the first 2 years is getting everyone on the same footing. Removing this without changing high school, puts students at poor high schools at an even greater disadvantage.

It’s 8%.

The bottleneck is funding for residents and the AMA has been lobbying for more resident slots for nearly 30 years.

Essentially no one pays for medical school outright. They take out loans. Those loans aren’t credit based. People aren’t priced out of being doctors.

I’ve worked on HR software. There are currently at least 3 large scale, bespoke, homegrown payroll/HR systems in use by the Federal government. There used to be many more. There are many reasons to outsource software but the government can’t hire enough engineers is not one of them. It’s clearly been done before.

>Just customizing something like PeopleSoft to fit is a large task in itself, let alone trying to implement bespoke software

Customizing large enterprise software is more like writing bespoke software than it is what most people think of when you use the word customization. You end up paying enormous vendor margins on top of the costs for something that is effectively bespoke software.

There is so much bespoke software out there that is at least as complex as government payroll software.

Enterprise software is complicated mostly because of number of customers it can support.

Bespoke software can be orders of magnitude less complex. There are many reasons companies choose to use vendor solutions, but for large organizations it’s usually not “we literally can’t hire enough engineers to build it.”

There are so many counter examples.

Last time I looked the other app stores didn’t show anywhere near that much of a bump (that was a several months ago though).

And a few months ago I went through a random sample of new apps on the App Store and the vast majority were just wrappers for AI APIs. So it was more of a new gold rush situation than a productivity bump.

There was much more than just the high profile egregious cases though.

Most food adulteration is a quality issue more than a safety problem.

Buy old peas but put a little green coloring in is almost the exact same thinking as let’s replace the metal gears with plastic ones to save a dollar per item. The vast majority of companies doing that didn’t kill or seriously injure anyone.

Companies have always been doing this.

2 things.

1. If you turn the temperature down too far, the output is just bad and no amount of running prompts optimization will let you hill climb your way to good performance.

2. It’s not about determinism vs non-determinism. It’s about chaos. A perfectly deterministic model is still chaotic. Meaning that very small changes to the input result in very large changes to the output.

Turning temperature down doesn’t actually get you predictable or reproducible behavior across different inputs.

I don’t know if that’s true. Look at the amount of lethal product defects over the last 100 years.

And before the FDA existed, companies were perfectly willing to put formaldehyde in milk, mercury in candy, and arsenic in vegetables.

If turn the temperature down for tests, they won’t match production behaviors. If you turn it down too far in production, the output will just be bad.

Yeah but in my experience AI boosts output of those humans 10x and only boosts output of programmers who do write maintainable code 50-100%.

This isn’t a web UI, it doesn’t need icons.

But more importantly, if you aren’t the kind of person who could make a halfway decent text only poster before, you are going to make the posters at the top of the article. Those are objectively harder to read than something typed up in word.

You aren’t going to know to tell the AI to “ Go for a clean, unfussy, bright layout with a bold striking spring-themed graphic. Avoid pastel/airbrush/oil style art or images of people.”

That’s an assertion with no evidence that doesn’t match my experience.

Agents require far stricter guardrails than humans. Without linters, tests, static analysis, oracles etc… no agent can create a large program.

Even if you’re correct, you just build those checks into CI so that neither humans nor agents can skip them.

I said

“You can’t deterministically keep them from making even a tiny fraction of all the possible errors they can and do make though.”

And you replied

“This may be platform dependent.”

I’m unsure how else to read that other than an implication that this might be possible on some platforms.