Dear AWS, please let me be a cloud engineer again

> Then there was AWS re:Inforce – the annual security conference – which was themed “Security in the era of generative AI”.

This tagline is representative of every part of the hype around GenAI. It makes it sound like security has fundamentally changed and we all need to re-learn what we know. Everything to do with GenAI is treated like this: we need new security plans, we need AI Engineers as a new job title, we need to completely reevaluate our corporate strategies.

Security in the world of generative AI is not substantially different than infosec has been for a while now: User prompts are untrusted input. Model outputs are untrusted input. Treat untrusted input appropriately, and you'll be fine.

The same goes for "AI engineers", who are in the business of wiring up APIs to each other like any other backend engineer. We take data from one black box and transfer it to another black box. Sometimes a black box takes a very long time to respond. It's what we've always done with many different kinds of black boxes, and the engineering challenges are mostly solved problems. The only thing that's really new is that the API of these new black boxes is a prompt instead of a deterministic interface.

Don't get me wrong, there will be things that will be different in the post-LLM world. But my goodness do the current crop of companies overestimate how large that difference will be.

AWS is way too bandwagonny these days. Back when it was all engineers they built things on the basis of "this is cool technology". These days marketing runs large parts of AWS and plans are decided more on the basis of "this will look cool on a PowerPoint slide".

I keep going back to the basics: Serverless is servers. Machine learning is servers. GenAI is servers. And, from what I've heard, most of AWS revenue is servers and storage.

(For the record: I am also an AWS Hero, and an AWS customer since 2006.)

I didn't get it. All of the new features they're adding are for AI, but the old features still exist, right?

If nobody wants you to use them, is that because everyone already has as much conventional architecture as they need? Perhaps the new opportunities are all in AI because we've pushed conventional stuff as far as it could go, and we were just rearranging deck chairs.

I'll be honest that, if we've run out of ideas, I dunno if AI really solves any problems I want solved. But even if not I don't see how appealing to AWS fixes anything.

I think the main issue here is brand and growth. AWS needs to convince CIOs/CEOs to use them over Azure/GCP, not engineers. And even if AWS cared about convincing engineers, we already prefer AWS so introducing new services for container orchestration wouldn’t move the needle. What does move the needle is being perceived by enterprise leadership teams as just as cutting edge as the competitors. “Generative AI” is the only signal those teams understand these days.

Good reflections. It kind of remind me of the big data era where everything needed to revolve around big data.

However, what happened is that it became apparent that not everything needs to be big data. Business needs will shine through as they always have and dictate what is truly important.

I'm not afraid of the wave of gen AI. Think of it as the new power tool that just came out that everyone's currently talking about. You'll add it to your toolbox because you don't want to be obsolete. It'll blend into everything else once the hype wave is over.

I don't know, if you get existential worries about your job because one supplier jumps on a hype bandwagon at a few conferences, then aren't you a bit too married to that supplier? I don't mean from a company perspective, I mean personally. I don't understand how AWS conference topics prevent anyone from being a cloud engineer.

This is just in general true of generative ai. In many ways it commoditizes skilled labor. They do not care about people in the posters situation. It is meant to lower the bar and make the labor cheaper.

An "AWS Serverless Hero" is upset AWS are acting vain around their AI posturing.

AWS is desperate to climb up the value stack. Compute and networking is a commodity (with fat margins at retail prices to be sure), and the second and third place providers are willing to make deep discounts to land big deals. That's not going to justify those future lofty valuations.

The problem is, for all it's talk over the last few years, AWS remains a complete non-player in the GenAI space, much less so than Azure. In my opinion the problem is exactly the same as for every other high-level service they've tried to launch. QuickSight, Lex, Polly, Cognito, CodeGuru, SageMaker, etc: they're not good. Nobody ever said "I really like QuickSight, I sure wish it had GenAI capabilities". So when the hastily-expanded QuickSight team(s) then goes on to release 42 different Q enabled SKUs, nobody cares. For various reasons, AWS is organizationally incapable of launching a non-infrastructure product that is simply great, as doing so would take attention to detail and deeply caring about things like UX which are anathema to Amazon.

On the positive side, GenAI model access will be commoditized and part of the basic undifferentiated cloud infra, and AWS will do fine there.

I finally went to an AWS event this year: the AWS Summit in DC.

It was an awesome (and awesomely overwhelming) experience, but I completely agree with the author. GenAI EVERYWHERE.

The other topics that the author brought up from re:Invent 2022 were still present, but not without heavy mentions of how AI contributes to them.

That said, I have some predictions that might make OP happier.

DevOps and Platform Engineering is still a hot topic, especially in a world where companies are repatriating back to the data center (or are at least going hybrid). All of the 2010s bare metal tech (Foreman, Ansible, etc) are going to come back in big ways, and Kubernetes consumption will only increase. eBPF and systems engineering is still hot and will really help here for high-performance observability.

Companies that won't repatriate or want to use the cloud for prototyping will want to focus on cost optimization. This requires serious cloud engineering skills (using spot instances and S3 lifecycle policies is table stakes; much more can be done, especially on reporting and automation).

GenAI will help here (super helpful for analyzing time series data and surfacing patterns), but having the fundamentals will always be useful here.

Hear hear. I'm a founder of a GenAI startup, left Google to do it. And yet, cannot believe how much debasement has occurred, and trust has been lost, by every. single. product. and. company. thinking it has to have an AI story, and it has to be the story.

c.f. Google IO keynote this year. I couldn't tell you a single thing Google is launching this year, beyond limited, rushed features where Gemini chat is in a side pane.

And that's not on me: it's because Google literally didn't talk about a single other thing.

And as usual, Google is out of touch and doesn't get the joke, c.f. at the end, Sundar presenting their own count of how many times they said AI.

I sorely miss tech industry of the 00s, I simply cannot imagine ex. 2000 Apple/Steve Jobs falling for this. There's this weird vapid MBA brain drain in charge everywhere. But hey, stonk goes up.

it's not only cloud services. The AI hype has hit self-hosted services and "normal" / "offline-first" applications as well.

For example, the team / leadership / foundation behind Home Assistant has been pushing AI features hard in the past 18 months or so. This coincides with my feeling that there hasn't been any relevant improvement in Home Assistant's core features and usability — it's in stagnation for over a year now.

This is of course my own opinion, but it makes sense: if a significant share of resources is spent on AI stuff, that share is not available anymore for other needs.

The last sentences of the article say:

> Your first leadership principle is customer obsession: “Leaders start with the customer and work backwards”. > I’m your customer, and I’m begging you: please let me be a cloud engineer again.

However, as with many enterprise products, the author is not the customer; it’s the user.

The customers are the companies that buy AWS because it’s an essential technology for their strategy. When the whole tech world is talking about generative AI, they want to be there, and Azure seems to be ahead because of the MS deal with OpenAI. (even if they are not ahead, customers' perception matters most).

So basically, what Amazon is trying to do by making all of these conferences and announcements about GenAI is to send a message to their customers: we are ahead on the wave of GenAI and you can still trust that our products are going to help you be on the hype.

AWS mainly earns from new modern managed services because ppl do not want to manage anything and AWS does it for them. All those services are too expensive and AWS markets those and keep talking about those as conventional managed services have less margin.

> Your first leadership principle is customer obsession: “Leaders start with the customer and work backwards”.

> I’m your customer, and I’m begging you: please let me be a cloud engineer again.

Only AWS knows how many H100 GPUs they have, how busy they are. How many people are paying for them, how many people want them and can't get them, and how many people just don't care at all.

It's possible that the focus on GenAI for Re:Invent 2023 wasn't based on any hard data like that, and is really just up to the whims of Adam Selipsky since Jassy moved over, but maybe someone who better knows their planning process can comment.

I have to say I find their GenAI offerings muddled at best. I genuinely don't understand what Bedrock is trying to solve.

Go experience the joy of becoming a Linux engineer, where you need the permission of no-one to practice your craft.

It is one of those typical moments for all big corp when fight for customer is less important than fight internally for employee survival. In this case, AI is the tag to keep oneself "relevant" and in the job.

Related content: Corey Quinn on the AWS GenAI obsession

https://www.lastweekinaws.com/blog/amazon-genai-services/

AWS really feels they were left behind so they are overcorrecting a bit.

In private they are truly thirsty for AI applications they can write uses cases on that they even offer upwards of 100K credits for Gen AI purposes only.

TBH AWS re:Invent is frequently like that. In 2017 or so there was an absurd amount of “Alexa integration” events that were completely useless. I get the sentiment but, you know, it’s really just a giant marketing and pre-sales exercise.

I feel I am going to be downvoted for this, but...

I think the technical specialty that will be most at threat from automation by AI would be the exact job that he authored has -- solutions engineers that build commodity cloud infra on AWS, Azure, G cloud, etc.

Look at progressions and range of abstraction between standard sys admin IT work to serverless deployments, especially with IaaC tools.

You can describe your architecture to chatGPT and it can spit out a CloudFormation YAML. It will be rudimentary and poor, but I could see a Gen AI tool offered by cloud providers where al you do is describe your app and then deployed infra on your behalf, and optimize form there.

Not trying to talk down on folks who do this type of work, but sharing my opinion on where I think the author is ultimately coming from.

I'm just going to say it: Gen AI is a complete and total nothingburger.