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