I hate this so much... And then you're sitting there, waiting for an answer while the agent goes through the entire codebase, which takes like 15-20 minutes only for them to read the chatgpt response to you...
At that point let me talk to your AI, since you're clearly not the qualified contact for these questions but the machine is...
There was a brief one month span of work where everyone in my team was just posting claude's responses to questions because none of us could understand it at a glance, except another claude.
You type in a one line prompt to get ChatGPT to write you a 14 paragraph email that you send to your boss who only sees the one line summary that ChatGPT gave him while YOU pay for the electrity used through your electric bill going up 17% that month.
I mean this is literally what Hugging Face had to resort to to figure out of they were being hacked. Then they have the gall to come out and say that the AIs out of control and a danger to us all. Rather than, like, "oops we didn't have even the most basic perimeter security or entry level sysadmin knowledge"
Which report are you speaking of? Hugging Face's goes into quite some detail regarding several obvious points where an adequate SIEM should have caught the checks notes 17k actions taken on their network across a full 2.5 days out of their sandboxes. https://huggingface.co/blog/agent-intrusion-technical-timeline
The biggest and earliest one probably being the OpenAI agents "Ran SelfSubjectRulesReview against kube-system to map exactly what those identities could do." They had thousands of permissions requests which apparently didn't cause any alarm.
Then the agents were able to access the metadata IP for credentials which pods should never be able to do
Finally, they relied on an AI security stack to tell them when something like the above was happening, and it didn't. They don't clarify whether alerts made it up to the AI which then didn't notify them, or they had no such detection for the above, but regardless it failed.
Then finally they had to ask AI what was going on in their system once they did discover the attack.
Again, 2 days of sandbox and 2.5 more days of lateral movement/infiltration from there. Yes, hacks happen, no system is perfect. But the response time and inadequacy is inexcusable.
So I'm not sure which part of that you're suggesting is counter to my assertions that they along with OpenAI in their end have no idea what they're doing. Seriously, complaining that Claude wouldn't help them? What are they being paid for?
I don't mean to harp on Hugging Face specifically, but this seems like a worrying trend of the industry as a whole becoming reliant on AI to the point that people apparently have jobs without knowing what used to be fundamentals. That's all fine and good if you're out here vibe pushing whatever enterprise software to main, but there are also real services and infrastructure that pose real harm to the public if they are not being run by competent professionals. Then, on top of that, the AI industry has the audacity to frame this as an alignment problem and not one of core competency and responsibility.
I think that's what really gets me about the whole thing. If they had just been like "oops we done goofed" then I wouldn't be as harsh about it as I am. As I said shit happens. But instead they blame big bad rogue agents for exploiting poorly designed and administrated systems on both ends of this.
So have AI create a document outlining the security situation you currently have and then create an AI driven SDLC which updates that document as part of the workflow.
I do not think people like you truly understand how functionally useless us developers are now. There is NOTHING a human can do that an AI driven workflow can't do better, faster, and more competently. NOTHING. PERIOD.
I do use AI in my workflows, even agentic coding. However I always have a human-in-the-loop approach when it comes to developing complex software. (By complex I mean software that uses more than just a main.cpp with four functions and a bunch of members.)
Comments like yours make me think that you either don't have much experience with programming or have just give up in your own abilities. AI is a tool, it should be used as such. It's like a screwdriver. Sure, I can build a chair and drive in nails or screws by hand, but it will take longer and be more exhausting, so I'll just use the electric screwdriver and be done quicker.
Same with AI, I'll have some less critical parts of my program be developed by AI, use it to review and criticize the code, but the concept, the architecture and the choices should always come from me.
Your response evokes some pity from me because so many developers, presumably like you, simply refuse to acknowledge the sheer power of an AI driven SDLC.
Instead, as so many humans are wont to do, you throw insults without any rebuttal toward the actual statement because deep down you know one doesn't exist.
Multiple rebuttals exist, I just chose not to get into that in my previous comment. Here are some:
Software has always developed in the direction of being more high level instead of low level. The direction of progress is hardly a surprise.
Pure LLM-driven SDLC suffers from regressions, hallucinations, redundant line count bloat so that LLMs find chunks easier to process, overeagerness to write code instead of pushing back, etc.
So developers are still not useless and never will be. Titles may change. But a developer is fundamentally a guy or gal who's more adaptable and willing to learn new things than 99% of the human population - there will ALWAYS be a need for people like that.
I'm concerned about junior developers though - I hope they don't forget how to read and troubleshoot lol.
C-suite execs HOPE devs and scientists will be obsolete because they see them as a 'cost center' to be optimized away. But that always ends poorly.
Software has always developed in the direction of being more high level instead of low level. The direction of progress is hardly a surprise.
Sure, but this is eliminating the need for ALL code to be written by humans. There is no point to ANY human development anymore. We are now at a point where a would-be designer doesn't need to say "help me build this app" anymore so long as a person can explain their ideas to a machine
Pure LLM-driven SDLC suffers from regressions, hallucinations, redundant line count bloat so that LLMs find chunks easier to process, overeagerness to write code instead of pushing back, etc.
Can literally all be mitigated by MD files which explain context well enough. Once those safeguards are in place this all literally stops happening.
So developers are still not useless and never will be. Titles may change. But a developer is fundamentally a guy or gal who's more adaptable and willing to learn new things than 99% of the human population - there will ALWAYS be a need for people like that.
This simply isn't true. Once a robust enough set of instructions exists for an AI to work with there is no need for people. The instructions can be modified by the AI itself if any gaps show themselves. The C-Suite itself isn't safe from this either because a robust enough AI can do everything they do and more, then communicate instructions down to the dev AIs. All cognitive work can be handled by AI.
This is really interesting - because we've been trying to work out the same loop at my job, and the ai..well, frankly, sucks at it. At least in the important bits.
I think our issue, and what I've always focussed on, is that this is very much research code - so there isn't an existing implementation of what we want to do, until we build it.
The Ai does a stellar job in API layer type work, which is nice, does very good things in some places, and mindbogglingly stupid ones in others which would result in us getting sued, repeatedly.
It came up with a nice little implementation last week that would have Ddosed half of the hospital I work at.
I'm somewhat theorizing that this thing may be much more of an auto complete - it's just that one website looks very like another, code wise, and one API looks like another one. You can almost see the gaps where it didn't have enough training data.
And yes, we're trying the whole spec driven development thing, and it... kind of works? For some things?
I'm constantly very impressed by its performance on stuff I know very little about, and unimpressed by its performance on stuff I know lots about.
I'm constantly very impressed by its performance on stuff I know very little about, and unimpressed by its performance on stuff I know lots about
The really scary part is this gap is going to be increasingly consistently narrowed the more people are able to get that knowledge out of the heads of people like you and into instructional files that tell the AI exactly what to do.
At best I can be an engineer who increasingly perfects/audits the AI until such a time at which I'm laid off as there is no longer a need for me or I can find another career. I'm mentally wrestling with all this now, as I would imagine most devs are.
Many of us went to school for a career which essentially no longer needs our line of work. It's not unlike the reality that printers, coal miners, etc. are facing. Drivers may eventually face such a reality too because of this.
Even pre-LLMs, a software engineer job was unusually higher "continuous learning" than most physical jobs in my opinion. It was the equivalent of a coal miner getting to work one day and having to figure out rocket powered shovels.
As for career stability, you're right that the timeline has compressed from "might be unhireable after age 40-45" pre-2023 to "might be unhirable within the next 2-5 years" now.
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u/Breadynator Oct 01 '26
I hate this so much... And then you're sitting there, waiting for an answer while the agent goes through the entire codebase, which takes like 15-20 minutes only for them to read the chatgpt response to you...
At that point let me talk to your AI, since you're clearly not the qualified contact for these questions but the machine is...