Having been early at a startup that relied on Postgres I think this post doesn't put enough focus on monitoring and alerting. Postgres has a few key failure modes that you want to avoid ever happening, and you can use alerting to get early warning that you're danger of it happening.
For example, AWS will send you an email if you're approaching XID wraparound. In a startup that email is very likely to be missed, especially if it's sent on Boxing day. You want whatever AWS is watching to send you that email to be something connected to a pager.
Not really that related. Refinement culture is concerned with evolving aesthetics and marketing which is partly a response to globalization and the rising middle classes of asia, partly related to digitization, and partly just a normal evolution of style.
What George is talking about here is much more related to the ideas of Nick Land, technocapital, Marshall McLuhan, and man's relationship to industrialization.
> Isolation is basically impossible because the Internet follows you everywhere. And it’s perfectly uniform, there is no other Internet, just a place with five corporate towns and some Chinese ones that are really hard to visit if you don’t speak Chinese.
This is McLuhan's "global village".
> I don’t think I’m properly capturing the scope of the machine. First you build the fence to keep the animals out then you build the fence to keep the animals in. It’s a Fullmetal Alchemist homunculus maybe it has already eaten your soul.
I think 99% of the commenters in this thread seem totally tone deaf to the article and the phenomenon being attacked by geohot. Granted, he doesn't articulate it well, but as you say, these aren't new concepts and much better introduced by Nick Land, Mark Fisher, Byung-chul Han etc.
Major Sandbox providers (e.g. Modal) run on non-hyperscaler bare metal not AWS and so don't need to markup on AWS's markup. Thus, prices are comparable or better than AWS.
In that case it's still overpriced because they're charging hyperscaler prices without offering a hyperscaler level service in terms of scalability, reliability, security, trust, etc.
Unfortunately supply is quite limited. If you want to horizontally scale on these instances you need to have a good relationship with AWS so they'll give you a big allocation before c9i is a thing.
I haven't personally tried, so I can't say for certain, but Lambda has publicly stated they run on bare metal EC2 instances, presumably the supply of whatever instance types they use should be fairly healthy
The interesting part to me is less the exact hardware generation and more the control plane around placement, isolation, and startup latency. That is hard to copy outside AWS.
> Well, we tried switching back to GitHub Actions, and… yeah it still sucks. Blacksmith has grown explosively because it makes an increasingly frustrating bottleneck in the dev cycle faster.
Where's the "grown explosively" bit coming from? Google doesn't have growth news from 2026, only early 2025.
> That means each employee's AI spending cap is ~11% of that median compensation package.
Probably better to use the fully-loaded cost of the engineer, which is much higher than their compensation package. The fully-loaded cost is the total cost paid for the labor power of the engineer, and it includes big ticket items such as office space, food, equipment, insurance, payroll tax, fringe benefits, recruiting costs.
If the median compensation package is $330k/year then the median fully loaded cost is probably around $450-500k.
My usual rule of thumb for the US is north of double the received compensation but something in that range sounds reasonable with such high compensation. It's actually really interesting and underappreciated how that fully-loaded cost varies from country to country. Canada (for most salary ranges) is about half again instead of double owing to the insurance portion coming out of income tax rather than being a hidden expense so Vancouver ends up being attractive for trading 160k USD for like 120k CAD in compensation and then also lowering overhead from 100k USD down to like 60k CAD. The savings can be extremely dramatic.
Why would double be a good rule of thumb for typical US SWEs? Most of the costs aren't proportional to salary, and the ones which are aren't anywhere approaching 50%, much less double.
The costs to hire management and "support staff" like TPMs that scale with SWEs that help them meet goals is proportional to SWEs - often that is taken for the higher end fully loaded costs, depending on how you define it. Office space in downtown SF, Mountain View, or Palo Alto costs more than office space for back office workers in Nashville or Utah. Firms that hire SWEs often have fringe benefits like free food etc. and while they may apply to all workers, it tends to go along with hiring lots of SWEs.
But yeah, double is insane. When I saw prices for COBRA from Facebook, it was $3300 a month, and that was god-tier insurance - the insurance benefits were so good they had a custom list of what was covered that was probably way better than anything available on the market (e.g. you want brand name drugs? no problem. You don't want to try both ambien and trazadone before taking a sleep medication doctors actually recommend? No problem - etc.) - but for my needs it was barely better than COBRA costing way less than half. $3300/mo, or even $1200/mo for an entry level ops worker is a lot of their salary, and probably where the double comes from. At SWE compensation most of it ceases to scale.
The fully loaded costs including proportional management costs isn't relevant to the true marginal engineer, but estimates I've gotten from higher-ups definitely factor into engineering decisions about "should we spend engineering time to save money/make more money - how much will doing this thing cost the company" (opportunity costs are also relevant, but usually less grounded, since most projects don't have concrete benefits like "we will save $x/yr in infra costs")
DORAs. Rather than being sedatives, they directly target receptors in your brain that make you think you should sleep. I think the oldest one came out in like 2011.
It's kind of like neuroscientists found the trigger to tell your brain "we're going to do a clean shutdown now, trigger transition to runlevel 0".
Quiviviq, Dayvigo, Belsomra. All still on-patent, so they don't have generics and are pretty expensive (like $1000/mo if your insurance doesn't cover them). A lot of doctors won't recommend them in practice because most of their patients won't yet be able to get them covered.
GoodRX is always worth checking out, a ton of manufacturers will have coupons if you have insurance but they won't cover it.
Ask your doctor about them, look them up in your insurance's formulary to see what's required (e.g. if you have tried both Ambien and Trazadone and can document it), and see what they can do, before writing it off!
The expectation is Belsomra will lose its patent in 2029 and then generic makers can try to get one approved - so it's not that far off!
While the fully burdened cost of an engineer being double his salary sounds suspicious, this is indeed broadly the case. It has been (sometimes significantly) more than double in the case in every US employer where I worked and where I saw both numbers. In one case it was a hair under 3x.
My experience was not with pure software houses; we had some labs, measurement and RF equipment, but even without the hardware component the offices, insurance, admin expenses, HR, janitors, conference travel and so on would easily bump the total employee cost to double the salary. My 2c.
I’ve even heard the rule “twice the salary” being used here in EU, but the tax and insurance burden may be higher. All kinds of those are based primarily on total payroll amount.
That number usually includes cost of habitat and others. It's also a stupid number as it is skewed by how much you can squeeze out of your employees. A better number would be to compare it vs revenue per capita.
For a traditional software engineer? I retired last year after 3 decades and my salary was about the same as it was in the early 2000's at the last company I was at. Maybe I should have negotiated more but I thought only FAANG paid traditional pre-AI engineers more than $250K.
There is a tier just outside of FAANG that pays similarly or better, prominent examples being Uber, Airbnb, Stripe, Block, Databricks, Datadog, Pinterest, Snowflake, etc.
It is also possible that capping at $1500 will give you ~99% of the benefits. So even with gains that are much higher, a cap could be a rational decision. Also, most decisions, especially around AI aren't exactly rational, so I wouldn't read to much into this number.
It’s also worth noting that’s the peak benefit. Expect most engineers to not hit those limits on the regular (if at all, since limiting this puts skills in focus again), and that limit to come down over time as the easy processes are automated and humans are re-tasked with harder problems relative to their TC.
This is not a good bellwether for the AI industry, including its adherents. Their growth assumed a level of indispensability that’s not being reflected in hard numbers and real costs, which lends credence to the notion that these IPOs being fast-tracked are meant to try and cash out before the bubble really pops in earnest. There’s no way consuming enterprises are going to pay such insane costs for such minimal uplift in the long run, and the AI companies can’t keep offering subsidized tokens via subscription plans at their current pricing.
