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.

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 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.

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.

"Fungible" implies they are a commodity, easily swapped for someone else. In other words, they are so low-value that they are interchangeable.

"Flexible" or "generalist" instead connotes that they are so high-value that they can operate well in multiple domains, easily shifting to where they are needed most.

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.

The goal was never to solve a real problem, like we evangelized for decades. That was how it was explained when resources (mainly time, but also money) were scarce and we could not just throw things at walls. Now we can, and you won't see anyone talk about "make something people need".

Things will be low quality until something sticks, and then money will be poured into it. It's not a bad strategy, but my takeaway from this is: there are multiple plausible explanations for the same thing. People have an incentive to not give you the correct one if it helps you compete with them. But they will give you a sensible one. AI won't protect you from this, experience and real knowledge will.

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.

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.

Has that changed, or is it the non-AWS part of Amazon?

Anecdotally, this seems to be the new "mission statement" of many companies.

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?

The recovery from being an orphaned customer account serves as the litmus test. In this case, it took someone who was unique and non-interchangeable and poked "the right bear" -- and it succeeded. But that's precisely the way that enshittification of the principle occurs.

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.

Side note, and unpopular opinion ahead: while it takes a lot of courage to write things like this and I respect it, but being fired and writing negatively (no matter how justly) about your former employer is considered by many employers as a red flag and can hurt you going forward (even if you are 100% right).

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.

> It also assumes that there is a limitless supply of people with the required skills, and a willingness to work for Amazon.

I think one major concern here is that "apparently" AWS is in such good place they don't have to worry about anything. People, their reputation, their employees, future stability, growth. Nothing is of worry. They have reached the IBM status where everything is awesome. However, executives are usually paid precisely to worry about these things. Though, we've seen executives are pretty stupid these days. So, I guess it's clear AWS is clearly not the exception.

No they utterly failed and needed a special non fungible employee to get them to do their job.

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

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.

AWS services still are generally reliable and available. I’d think we’d be seeing cracks here if the organization were in shambles. AWS seems to keep humming along.