About a year ago there was a "Show HN" post (can't find it now) and the SteamDB guy won the internet that day.
He went into details on how running SteamDB wasn't much of a trouble and it was mostly eye candy on top of the Steam API, in some VPS for $100/mo total, and little maintenance (apparently the Steam APIs are fairly stable).
If he wants to cash it and check out, fine by me, you can't blame him.
Not really sure if this was your intention, but you're making a very compelling argument to keep teaching a "moral code" in schools, churches and homes.
It's good you can isolate yourself from it. But there's plenty of cases.
Open source maintainers being harassed or being demanded work through Github's issues. Or being feed AI slop to review endlessly. Or recruiters filtering resumes via Github activity graphs or repository stars.
And obviously the side shady market of all of the above (e.g. buying/selling popularity).
Like the parent comment, I can't wait for social media to be completely obliterated from code repositories.
> Open source maintainers being harassed or being demanded work through Github's issues
This isn't "psyops". Sure, it's a bad side of social interactions, but when you interact with other people, there's always some of this - in person as well as online.
The lead-off argument here seems more like "interacting with society can be bad".
I have no argument that selling popularity is bad and filtering by stars is stupid, but I don't blame Github for any of that.
You could equally well assign the success of certain coders to YouTube because they came to attention by showing off their work in livestreams. Which I do not. They found a way to advertise their own success, but it's theirs.
> The lead-off argument here seems more like "interacting with society can be bad".
The argument is that there's no need for that much social interaction to produce quality code, quite the contrary, the more social interaction, the more focus is lost.
I know it's an unpopular opinion, but there's a reason why the Linux Kernel communication is still done through acerbic email threads.
None of this is specific to GitHub. The exact same problems will sometimes happen any time users and developers communicate, which is a basic requirement of developing useful software. I doubt GitHub issues are worse than mailing lists or any other mechanism.
They almost have to be - which users will be able to get to your issues page and which will be able to find a mailing list? You'll have a much more selective audience in the latter
Demanding work isn't really an issue. Anyone can do that, and also reject the work. Dishonest actors on the other hand would take money for someone else's work.
Leaving AI completely aside, it still amazes me that people finds "novel" the idea of removing highly-paid white collar intellectual workers (software developers or otherwise) completely out of the loop.
No-code platforms date back to the 80's. Getting rid of engineers in general is even older [*].
Even relational databases and SQL were initially promoted as "ways to get rid of those expensive programmers to access your data" because they resembled some form of English.
The funny thing about the ad below is that stuff like "stop hiring / get rid of humans" would have been seen as highly insensitive in 1950's America, so they touted that as "put them to do something more important".
It's novel because previous rounds of automation were about automating specific tasks or well-scoped functions. There was always an implicit understanding that the white-collar worker would be freed to spend their time on more valuable, higher-level problems. But this time is different because of the generality of the technology. Agents promise to automate the process of thinking itself. And in many domains they can learn new tasks as fast as white-collar workers can find them.
> It's novel because previous rounds of automation were about automating specific tasks or well-scoped functions. There was always an implicit understanding that the white-collar worker would be freed to spend their time on more valuable, higher-level problems. But this time is different because of the generality of the technology. Agents promise to automate the process of thinking itself. And in many domains they can learn new tasks as fast as white-collar workers can find them.
Nah, sometimes the expectation and advertisement was that you could let go of the white collar worker because you're paying the overseas person 1/10th the amount. And "overseas person" is pretty general.
"Everybody knew" it was a bad idea to get a CS degree for a bit after the dot-com bust because of that.
(Some white-collar industries did get hit much harder by that; VFX is one I've heard in that context quite a bit.)
That's a good point. However, overseas people are still people. They need to sleep, get sick, and the better they get at their jobs, the more money they will demand. The cheap ones also often have communication barriers and work slower than the workers they're replacing.
AI models get better and more efficient every 3 months, run around the clock, can be copied infinitely, and unprecedented amounts of capital and research talent are being thrown at any limitations we can see with them (such as problems writing correct code in 2024, lack of agency in 2025, autonomy and self-improvement in 2026). That's the difference between labor replacement through outsourcing vs. labor replacement through automation.
We are either living in different worlds, or squabbling over different meanings of words.
Models have absolutely acquired agency as of 2025. Developers are no longer copy-pasting code from ChatGPT into their text editor, they're working with agents like Claude Code and Codex that can edit code, run terminal commands, do web searches, manage their own context windows, sift through gigabytes of logs with datadog MCP, etc.
Self-improvement is also being worked on. Claude Tag learns over time in slack convos. My company also has an agent that updates its own skill files after every conversation so that we don't need to keep reminding it about the same workflows every time. Is it clunky as hell? Yes. Are the labs plowing billions of dollars into "continual learning" and "recursive self improvement"? Also yes.
What you call a model acquiring agency I call plain old software with productivity workflows designed by humans, with deliberate goals. We must separate “model” and an execution environment using a model. [Model] ≠ [A glorified shell script doing API calls in a control flow based on heuristics]. Agents are not AI, they are plain old software. The weights are the model, and that very much remains a static artifact (and pre-post training models haven’t improved much over the last few years).
What you call self improvement is a duck tape hack to imitate persistence and save on inference. Every time you do an API call, anything that needs to be processed is sent to the model. Narrowing that context down saves money. Finding clever ways to do that improves apparent performance and value. The cleverness is still human.
These are all useful innovations on top of LLMs, which remain models that generate text and symbols based on static weights, which in turn represent training data and the provider’s preferences.
You say that as if the culture difference with a truly alien intelligence is insignificant compared to the culture difference with an "overseas person".
(Even assuming "intelligent" is a sensible label to apply to an LLM holding hands with a shell script in an infinite loop)
I’m at a fully remote company with staff in at least 8 countries speaking at least 5 languages. It works out fine. A possible analogy to AI is that a lot depends on how you use it. The “skill issue” doesn’t disappear, at least not yet.
To colaborate a bit with the no-code part, I worked at a place where they had some flows made with n8n, but the last one from non tech/software engineering left the company and left a bunch of flows breaking, because of some edge cases the flows aren't handling like reissuing credentials, throtling or bad input. The people dependent of said flows reached out to the engineering team to help fix them!
I don't think the no-code comparison is valid, it's always been fundamentally flawed since its many leaky abstractions sitting on top of systems programming code
LLMs can't replace developers but its foundationally different because it can operate on systems code instead of building abstractions on top
Marketing about a more efficient product that requires fewer engineers is obviously not new. The idea that human engineers are obsolete is pretty new, that's the claim that is getting pushback.
I understand that but I think it's in direct proportion of the money being raised, spent and thrown around, including the price tag, to replace such engineers. The more money you ask for, the wilder the claim needs to be.
I guess it depends on your definition of "too much", but also on your definition of "thinking".
What I've found is that LLMs are excellent tools for:
- Spitting out white collar corporate speak that sounds plausible to other corporate speakers
- Hugely accelerating the process of going through academia which, except for a few specific cases, is essentially years of copy/pasting
- Writing code as long as such code as been written many times before
- Figuring out which one of the 10 ads and 12 misleading links in a web search is the one you're looking for
- Summarizing a book in ten paragraphs so you don't have to read it
...which turns out a lot of people defined as "thinking". I don't agree with that. But in either case, not "too much" is being offloaded: it's all of it.
Those metrics are hugely misleading because they account for current fiscal year revenue and margins.
For Xbox being what it is today, which is mostly about the subscription and not the hardware console or the exclusives, you have to compound their acquisition frenzy of 2018-2020 or so, which totals about 75 billion+.
They didn't want the developers nor the catalog. What Microsoft wanted is to change the economics and dynamics of the entire games industry, to make it Netflix-like (play what's in the catalog today, pay monthly even if you don't play anything) vs. what Steam offers (purchase once, own "forever", even if it's de-listed).
But that didn't play out. Optimistic estimates put total revenue for Xbox since then in the 20B ballpark. At a ~5% margin (as other commenters have pointed out) the profit is about 1B dollars.
It means that after almost a decade, the entirety of Xbox is in the red for about 74 billion dollars, which is 74 billion away from breaking even.
Steam still dominates PC gaming. Xbox consoles can't be more irrelevant today.
This isn't about over-hiring or AI. It was a bet at the executive level that went horribly wrong. They can still do things like selling IPs at a bargain to compensate, but still. Horribly wrong.
Note: Microsoft doesn't publish hard factual data so the numbers above are somewhat speculative (e.g. "analysts data")
It seems really odd to have a Netflix consumption model for games. Generally people want to play a few favourite games for a long time and get very skilled at them. You just don't need to churn through content like movies.
You see 10 hours for indies and art games maybe. For big budget full price games people expect at least 60+ hours, which is why they tend to be full of padding.
The vast majority of "gamers" play freemium "games" on their phone. The next largest likely buy a console for one or two games, and maybe pick up another now and then (back in college one person's lamecube was permanently playing smash bros; another was on golden-eye - the two xboxes were for halo and madden respectively).
Painfully accurate. I've been "the engineer", "the new engineer", Mario and/or Luigi at some point in my career. I can attest, this kind of behavior is pervasive across the industry.
And I welcome the change. In my long experience in academia, I've only found two types of practitioners:
1% are the absolutely brilliant minds that academia was originally created for. People that, without a doubt, leave their mark in the vast corpus of human knowledge. I consider myself fortunate for meeting and learning from them, and I thank the academia ecosystem for that.
But the remaining 99% are the maximalists, as described in the article. More papers/students/grants, then repeat. Worse enough, they're absolutely useless outside of academia, as they never did anything at all outside that bubble.
An embarrassing lot of CS professors would stumble around your average production codebase.
I think AI is just the final nail in the coffin for the latter bunch, as they have been dogs eating their own tail for decades already.
I think it's very field dependant. In maths and biology I've seen very few professors that could reasonably be described as maximialists here; computer science really seems to be the outlier. My impression is that impactful CS professors tend to be more strongly associated with either maths, or the field that their cs research is being used in.
Arts faculty on the other hand seem to basically just be a popularity competition.
Matches my experience. Hard science may not have that many maximalists. Applied science and technology (electrical, electronics, computer science, even mechanical), I've found plenty.
What got me out of academia (yup, I was a professor) was:
Do you have vast field experience and want to get into the classroom to teach how it's really done? Tough luck, you should've spent your time writing papers.
No matter how much you know or how good you are, everything is about feeding the maximalist machine, if you're an outlier, worse people with better "scores", more papers and never leaving faculty will forever beat you until they retire.
I took a good look at the publishing process. Absolutely everything about it was back-channeling to carefully select the topic, scope and reviewers of a paper to get it through the process. Goodhart's Law at its finest.
Advice given to me: "aim for a lower rank and be happy with teaching the whole thing while the old professor takes a nap in the corner".
AI or not AI, anything destroying that self-perpetuating bureaucracy is welcome.
Most of the general, watered down tone of Corporate America that we love to hate comes from the legal department, usually at the late-stage point when they make all the decisions in a company: product, business, launches, strategy, direction, etc. Everything needs to run through legal, and they have a final say on everything, including every public communication.
That's why I'd love an interview with Steam's legal head. Sounds like they'd have some wild stories to share.
About a year ago there was a "Show HN" post (can't find it now) and the SteamDB guy won the internet that day.
He went into details on how running SteamDB wasn't much of a trouble and it was mostly eye candy on top of the Steam API, in some VPS for $100/mo total, and little maintenance (apparently the Steam APIs are fairly stable).
If he wants to cash it and check out, fine by me, you can't blame him.
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