This was for a question about how billing works.
It went like this;
1. Case created.
2. Unassigned for seven days.
3. Open real-time chat, talk for 25 or so minutes where I guide a first-line Indian chap who plainly doesn't know about the subject in hand and who is as we talk reading the AWS docs I've already read. At the end, just as I couldn't find an answer, he couldn't - which is good, he didn't try to give me the wrong answer - he escalates. That's fine - a lot of questions are simple and even silly, and first line support is there to handle them - but they could have done all this without me, if they'd opened the ticket themselves rather than me having to chase.
4. Eleven days later, comes back with exactly the wrong answer. In the meantime, I had figured out the correct answer, and reply, explaining it to him.
5. Next day, I get a wall of plainly AI generated text telling me my answer is correct.
It seems to me a key issue here relating to AI generated text, is a misunderstanding on the part of AWS that I as a consumer will value that answer exactly (or indeed, even remotely) as I would value the answer from a human.
I do not. I almost ignore AI generated text, as I think it as unvalidated response.
Even Stripe - once legendary for the quality of its support - has apparently given up now. I had to deal with it recently over a case where the merchant was seeing an unexpected change in the way it was collecting payments and the AI bot was worse than useless - it actively suggested incorrect explanations and resulted in several days of trying to change the wrong things while the problem persisted.
For my own businesses we give this issue a heavy weight when choosing which services to use. We have even seriously considered moving existing integrations to different services over this one issue recently. If we're integrating with a service then we want to know there's a real person who can actually help if we have questions or anything goes wrong. Failing to provide that because it's cheaper to push everyone through the AI bot is a statement of intent about how much you value your customers.
I've been at places where the AWS annual spend was a real lot of money, let's say way over 100k but not 1 million USD.
Support tickets went unanswered for months, assigned account reps left us hanging for months with multiple follow ups, etc.. All tickets opened within the last 6 months got AI generated responses with massive delays that indicate the ticket wasn't read by a human due to how inaccurate the response was based on the questions asked.
We literally pay hundreds of thousands a year in Oracle support contracts, and this is what we get? AI bots? Nope. Migrating to Postgres is now a top priority.
This "replace people with AI" nonsense has to stop. [0]
[0]: https://www.forbes.com/sites/jonmarkman/2026/04/06/oracles-m...
Out of curiosity, why is it relevant that this person is Indian? AWS employs a lot of Indians on their actual product and engineering teams, who have built AWS, and surely do know their own work well. Isn’t this just an issue of support mostly being lesser-paid people who work off scripts, rather than of race?
Now with H1B sponsorship, where I've heard rumors of companies taking away passports of their workers, it is very much evil, but not slavery.
When you hear the accent, you know it’s likely the business has done this, unfortunately.
Indian tech support works just fine when it’s more integrated with Indian engineering and product ownership, as support in the US would be with an American company.
This enforced adoption of immature GenAI reminds me of Milo Minderbinder trying to make people eat cotton in Catch 22, because he had inadvertently obtained a huge amount of it.
there’s no heroic clash with other civilizations, they simply rot away
I still don't have an explanation why people are doing this. Is it part of leadership training? Or do presenters have their own theory that including this stuff makes the presentation more memorable and enjoyable?
Why was leetcode so popular? Because Google did it and they were the cool kids at the time.
This is how many large enterprises still operate today. Ironically, the main argument is that it's faster to provision VMs on-prem than it is to get approval to run in the cloud.
Bureaucracy always beats tech.
And things only got better post-Industrial Revolution when labor organized and forced the issue.
There's no guarantee that will work again if labor has reduced leverage due to AI reducing their value.
I think in one way or another this all works itself out, but I'm not convinced it won't be a very painful (and possibly violent) transition to whatever comes next.
There are paralles to the industrial revolution, but it seems the working class is cut out from being able to deny labor in exchange for better conditions.
A software engineer getting four months severance after a layoff exists in a different universe from this so no. There is no precedent. Don't you dare talk about the industrial revolution because its not even in the parking lot of the ballpark.
You're right, it's not in the ballpark. It's at the gates. The game isn't on simply because they poisoned the opponent in the duggout.
It's time. It needs to stop now while the body count is low. This isn't about some dev getting severence. They've taken away the street sweeper position and are watching us eat each other.
There were always other problems too, pressure on the company in both directions across many different product lines on both cost (any number of cheaper baremetal providers who are much faster at providing customers instances than they were a decade ago), and product quality (any number of startups to now bigger companies, databricks probably being the biggest success) along with a number of expensive bets that were made that didn't work out especially as interest rates began to rise (there were numbers of of different services ranging from IoT, AI, business support, robotics, groundstation, that essentially all failed).
AI infra being their latest bet, along with doubling down on custom hardware is smart, but these roles don't require the same number of SWEs and instead require a different type of high skilled professional.
Unrelated to your main point, but it's "alumnus" in the singular form. For bonus language nerd points, you would use "alumna" to refer to a woman, or "alumnae" to refer to multiple women. Not sure how Latin handles mixed gender groups, though I would guess it's "alumni".
I personally think it’s not worth it.
It’s well into the IBM phase now. Primarily providing important but boring commodity infrastructure, but the top talent that can drive real innovation has long since left the building.
It’s race to stay relevant in AI but always seeming 2-3 steps behind everyone else is one such example of the current sad state of affairs.
I also joined in 2022, and it aligns so much with my experience. Good manager that moves on, then a gradual erosion of "insist in the highest standards" towards a dreaded "good enough", GenAI only accelerated it IMO.
It has become extremely difficult to hire at any level, we have had an open position on my team for a senior data scientist for a year and a half now, with barely any candidate applying, and none of them being competent.
Similarly the average level of new employees has dropped dramatically. The famous "hiring bar" is now below ground.
It‘s the golden age for software engineer employers.
I bet as the managers publicly nodded in praise for his heroic act, their hands were already typing his name to be sent to HR for “get this guy out of here on any excuse you can” note. (In reality it would be a nonverbal hint of sorts. Nothing to leave any trace discoverable by lawsuit)
And this is not a dink on the ai tooling itself but on the organizationan processes that provide the context in which the AI code generation is being used.
Bad processes will always produce bad low quality outcomes regardless of tbe technology.
Has that changed, or is it the non-AWS part of Amazon?
Hardly an Amazon-only thing. In fact, enterprises need this mindset, because people moves on, retires, or just suddenly die. With that said, due to its late-stage capitalistic ethos, Amazon is just too overly gleeful about this tasteless reality of life. It's the equivalent of a nephew coming to an aunt's funeral and shouting "A week ago, I told her everybody dies! And now she did! Wasn't I right??? Everybody dies!"
> Also, last year the focus at AWS turned fully and almost desperately toward GenAI.
I wonder if I'm being too cynical, but late-stage capitalism companies also love profiteering, and the mere prospect of firing all those pesky workers and not having to pay their salaries is like cocaine to those organizations. Which is why I think Amazon fulfillment centers will at some point rent robots at a price point between 2x and 3x their current human labor costs, in the hope that it will eventually make economic sense.
Enterprises typically have this mindset. Most corporations I worked for in fact treated employees exactly like this.
As for needing this mindset, I am not so sure. There is a spectrum in between going under because a storied employee retired and treating employees as meaningless numbers in a spreadsheet.
But ultimately I fully agree with the whole of your post. I just had to nitpick about this.
AWS has been this way for a lot longer than GenAI, since the basic infrastructure products were built out early on. But when I read this line about throwing things out there quickly, I also think of Google and even Anthropic. Google has a long list of products that got created and killed, as part of their internal politics and promotion culture. Anthropic is currently rushing vibe coded slop all the time to try and win over OpenAI and set up their IPO.
Maybe all the rich high funding companies can afford to this and maybe it is the right thing for them to do. They can afford to make big mistakes without hurting their stability. A true startup or smaller company can’t - they would shutdown because one big investment that fails is enough to destroy the whole company.
> To invent you have to experiment, and if you know in advance that it’s going to work, it’s not an experiment. Most large organizations embrace the idea of invention, but are not willing to suffer the string of failed experiments necessary to get there. Outsized returns often come from betting against conventional wisdom, and conventional wisdom is usually right. Given a ten percent chance of a 100 times payoff, you should take that bet every time. But you’re still going to be wrong nine times out of ten. We all know that if you swing for the fences, you’re going to strike out a lot, but you’re also going to hit some home runs. The difference between baseball and business, however, is that baseball has a truncated outcome distribution. When you swing, no matter how well you connect with the ball, the most runs you can get is four. In business, every once in a while, when you step up to the plate, you can score 1,000 runs. This long-tailed distribution of returns is why it’s important to be bold. Big winners pay for so many experiments.”
Both are following the same strategy. Amazon has a $2.86 trillion market cap. That's the equivalent of 143,000 $20 million Series A startups. Companies like Amazon and Google are basically an integrated herd of cash cows plus a VC portfolio.
Many storied companies can be described this way. It’s a shame. Have any companies hit such scale and kept the ethos and magic of before? Is it inevitable for companies to enshitify themselves in the pursuit of their shareholder’s goals?
No they utterly failed and needed a special non fungible employee to get them to do their job.
If any of you young'uns read this, that is not how we had to do provisioning before cloud.
VMs already existed before AWS came out. You could already provision a new server usually in minutes and rent it month to month.
In fact, all the existing VM server companies had to start calling themselves cloud companies because pointy haired bosses couldn't understand what cloud really was.
Where could you rent VMs in 2006?
IIRC there were two ways to run stuff, get your own server or get an account on a big shared computer.
Linode definitely had something along those lines.
Amazon won on APIs and overall integration but VMs were around already.
I remember the story really well as this is when i joined the workforce as a young GNU/Linux fan.
I was renting a Debian VM from Bytemark in 2005 that I used to host a mail and web server. I think they were one of the first operators in the UK.
And they were cheaper than renting AWS. MUCH cheaper. They still are.
The original point of AWS is that could scale according to demand. Have 10 VMs running at lunchtime and 1 VM running at midnight.
But using a cloud VM also required less server admin experience. It was a bit easier and came.pre-configured with things like firewalls.
And THAT is what ended up being the USP of cloud hosting. Especially when they started rolling out all the SQL as a service, redis as a service, etc.
You didn't need to really understand servers to run a server, and it turned out almost all developers really didn't want to understand servers. TBH, I don't, server admin sucks. Right now I'm working somewhere where I have to think about SSL certs occasionally and I consider it a complete waste of my life.
Digital Ocean came out like 5 years after AWS, what was revolutionary about that wasn't that you could spin up VMs quickly, it was the price. VMs went from $20-30 p/m to $5.
For developers who weren't SV rich, that meant you could run a side project without it being a significant cost.
I'm glad to see that one core amazon principle has endured the 10 years since I worked there, even if none of the actual leadership principles have survived /s