I'm also an AWS alumni from many years back now, and truthfully, the organizational problems really took off when Jassy moved to being CEO of amazon as a whole and major leaders left the company (Charlie Bell, et al.).
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 used to see AI generated images with lots of unintelligible writing or misspelled words in slides, but the speaker left them in anyway. “Good enough” is not customer obsession.
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.
I don't know if there is another industry that behaves this childishly. There might be. But good grief, how much more juvenile can ours possibly get? AI-generated images with obviously nonsensical text is something I never thought I'd see in professional meetings. But it is becoming more and more common.
I think a key goal of senior management at any big company in the last 6 months is to make rank and file fungible or obsolete. It’s one big experiment. There are precedents like the Industrial Revolution. Things get worse for the workers for a generation or so.
> There are precedents like the Industrial Revolution. Things get worse for the workers for a generation or so.
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.
The story about recovering the account rings very close to me. At least they had coworkers cheering for him, I feel teams are shrinking so much that we'll end up with just the LLM of choice to pat our back with "good work" and "you're absolutely right"
Co-workers cheered while managers were sharpening their axes. One doesn’t do such “heroics” without approval, making the system look incompetent and broken and then apologizing for it without being decapitated in the public square for everyone to learn the implicit lesson. Anyone cheering for him publicly should watch their back, too.
The economy sucks, and they do pay decently for software engineers. Especially now that the rest of FAANG aren't massively over-paying for college hires, I doubt the supply of bright young minds will ever entirely dry up.
There are now more highly competent devs ready to work for cheap available now than ever before and all of them are boosted with state of the art coding agents…
It‘s the golden age for software engineer employers.
The account recovery story says a lot. At some size, companies start handling people as tickets. Sometimes it only gets fixed because one person inside still cares.
Our company also requires everyone to use more AI-related tools, and I don't think there's anything wrong with that. But the quality of work produced using these tools really depends on the individual's ability. Some people don't put in much effort, and the results they produce are really sloppy, which bothers me a lot.
Absolutely. With his name in the public and apologizing to the customer for sheer internal incompetence. Then also cheered on internally.
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)
> Amazon has a really odd viewpoint when it comes to the people who work there. They view almost all employees as “fungible”.
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.
This genai is going to bring about huge quality drop in software across the stack and across the domains. I already see orgs that had reasonable software processes transform into orgs where the only metric is how much generated code you can slap and slop together and how fast. There's no success here for anyone.
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.
I was enjoying the article and then he makes some of the most bizarre claims about what cloud did and how we had to provision servers
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.
> Long story short, I was able to get his resources restored. All I did was manage to poke the right bear and the support team did the rest of the work (and they were amazing).
No they utterly failed and needed a special non fungible employee to get them to do their job.
“I have to say being fired from AWS is actually a relief. There have been a lot of changes to the company since I joined in 2022, and the company I wanted to work for is no longer the same company.”
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?
Not possible once big parts of the company start not knowing other big parts of the company and the company also has a board of directors that must increase shareholder value at all costs.
> In this whole pivot to GenAI, AWS has lost its focus on the customer. Instead of working backwards from a genuine customer need, the goal seems to be to create as many things as fast as possible, throw them into the world and see which ones gain traction, whether or not they serve a real need.
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 be fair, even though they have "working backwards" and "customer obsession", amazon has always been about making lots of different experimental bets. Bezos:
> 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.”
> 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.
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.
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
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.
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.
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.
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)
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.
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.
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.
No they utterly failed and needed a special non fungible employee to get them to do their job.
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?
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.
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