I have spent almost my entire adult life (since 1986) shipping products. One of the very first things that I learned, was that "shipping" > "designing".
There's so much work in delivering products that will carry your brand, and then must be supported.
I liken it to having children. Conceiving them is fun. Delivering them is painful. Raising them, is a lifetime of work.
In my experience, the same type of thing applies to products that we ship (and charge money for).
People think otherwise with AI partly because Anthropic kept telling us that they didn't have to write code or review code any more for most of their work. Their agent swarms just comb through their github, slack and wikis to figure out what to do next, and another swarm of agents just review, test, merge, deploy, A/B test, and revert the code. Boris alone merged nearly 300 PRs in the past week (or two?). So the top research labs seem have broken the productivity seal.
And then they talk about this recursively self-improving AI that is so powerful, so autonomous that they advocate that every company should be prepared to "pause" the effort. And their Fable/Mythos has this specific restriction as mentioned in their model card[1] that they are going to reject requests to tune and train models because, well you guess it, the models are too powerful to be used by mere mortals.
[1] We’ve implemented new interventions that limit Claude’s effectiveness for requests targeting frontier LLM development (for example, on building pretraining pipelines, distributed training infrastructure, or ML accelerator design). Using Claude to develop competing models already violates our Terms of Service, but enforcing this restriction through our safeguards avoids accelerating the actors most willing to violate these terms. Unlike our interventions for cybersecurity, biology and chemistry, and distillation attempts, these safeguards will not be visible to the user. Fable 5 will not fall back to a different model. Instead, the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning (PEFT).
Realistically, nobody intellectually honest really knows.
Plenty of people say that by 2030 we have AGI, others estimate 10-20 years.
I personally say 5-15 years.
AI 2027 estimates for 2027: "OpenBrain automatescoding"
No one said 2 years ago, that AGI is coming in 2026.
But lets be honest, I do not know, thats true.
I ahven't seen technology like this which affects me directly. But from past we know what disruptive technology looks and feels like. The weaving chair/loom disrupted an industry, energy, steam engine, internet.
Now we have the most generic technology an LLM/AI at a time were every major problem was solved:
We have the internet which allows for fast communication, we have very fast hardware, we have a supply chain which can react/act very fast globally and we have the richest companies on our planet investing into this technology unseen amounts of money. We have a local race between the richest companies on the world and a global race between the biggest world powers on our planet.
And we have the smartest people on our planet involved in this too. A lot of peple from academy went to the industry, some gave up their tenure for AI.
It would be very ignorant to assume that all of this can't lead to significant and fast change in our society.
It might not, but its like looking at a huge wildfire 50km away and just going to bed.
Even if that were 100% true, it only collapses the coding effort to near zero. Anyone who's built and shipped a real product should know that coding is maybe 50% of the work, and on a mature product it can be much less.
Sometimes it takes hours of discussion and tracking down decision-makers just to figure out what the intended behavior is.
i dont write code by hand anymore but shipping something people want is as hard (or maybe harder?) as its ever been
i also run loops that comb through slack / github to auto-propose a fix & have another agent auto-review, but you need the human to stamp, and they fail in subtle ways architecturally
But even with this toy project, and the target market being someone I should know very well (me), I often struggle to figure out what I want the app to do. When I go through brainstorming or grilling sessions it'll often ask me a question about how the product ought to work and I'm just like ¯\_(ツ)_/¯ give me suggestions and I'll let you know.
Apart from many other issues with this, heavily subsidized subscription plans won't last forever, and if you start burning your own money on tokens in this way, you'll soon realize it's terribly inefficient.
Holy crap that is dark. I like learning about ML for fun, and now I have to assume that their model is intentionally misinforming me to sabotage my learning? It is absolutely bananas that somebody decided that was ok behavior.
But I think you could have a full open source training software pipeline that's set up to work with Wikipedia, Common Crawl, Books3, Library Genesis, Anna's Archive, and whatever other useful data sets people can name. There would just be a step where you have to provide your own copy of Library Genesis (or whatever subset of it you have managed to obtain).
https://corecursive.com/coding-machines-with-don-and-krystal...
This comment is not entirely on point with your comment, it circles around and above it looking for lift though.
If you're not doing work that requires your code to stay in home nation data centres, Claude for Deepseek, Deepclaude (https://github.com/aattaran/deepclaude) is a great way to get better at using Claude like tools for software development. It even does a pretty good job of putting together cover letters for job applications...
Using Deepclaude is very much cheaper than using claude... For hobby projects, I've found it useful. A recipe (for cooking) management app I've made took a couple of hours to put together and cost $US 0.5. Claude is far more expensive.
The downsides of Deepclaude for many are:-
- DeepSeek is a Chinese corporation so the Chinese Communist Party may ask for data if it wants it.
- DeepClaude isn't as fast as normal Claude, though it's still pretty fast and I think fast enough (YMMV).
- DeepClaude might not be as optimised for various code issues that Claude may be able to solve more quickly or effectively.
- The same safeguards are probably on DeepSeek, but you won't be "wasting" as much money as you might on using Claude.
Inference focused hardware (https://www.youtube.com/watch?v=nvPqHoVSenE, AI generated speech) may in the medium future cause a large enough cost/energy reduction for LLM tools like Claude to make local LLMs more attractive.
Inference focused hardware would make running Open Source models like DeepSeek on local machines far cheaper and control over safeguards would return to the end user.
Hopefully this leads to a localised LLM provision market where local businesses provide varieties of these "local" LLM services. Here, local could mean on premise through to state or nationally based LLM services. Eventually, government orgs outside of the US may demand this kind of LLM use, in the same way governments legally require data to be stored within national borders for many critical government functions.
A bloke can dream I guess...
...Could affordable inference focused hardware also cause the bottom to fall out of these stock market bending valuations for AI corps and their datacentre obsessions?... Not to mention the societal costs caused by the AI super corps building these data centres. At the moment, they're nearly making a profit... They seem almost like speculative companies... Is that a term?
Like did they break through the productivity seal? Or are they willing to spend that much more on it since they see their failure as a like existential threat to humanity. I doubt it our boss sees your software the same way.
Isn't this the classic "dev wants to do start-up, has no skills ouside dev, do builds a dev tool" trap?
If you can't make the visitor understand your entire complex product in 10 seconds, then you've lost them.
Your product has to be complex because that's where the software market is at. All of the low-hanging fruits have been taken by the time you identify them. Sure, someone will find a way to make money using new low-hanging fruits that arise due to technological changes but it's not going to be you. You probably don't have the business connections to make that work.
The structure of a good argument would be something like: certain tasks are fundamentally human and impossible to automate (which and why?) and by pushing AI use beyond what is optimal you are actually hurting your employees ability to do those hard parts.
A weaker but still useful argument is that most everything can probably be automated, but frontier models aren't there yet.
> "There's always an easy solution to every human problem; Neat, plausible and wrong."
-- H. L. Mencken
It's like the classic scenario, where you lash-up a barely functional UI demo, and the manager cuts your development schedule by 90%, because you "already have it working." That taught me to never do a lash-up demo. If I show something to someone, it is ship-quality (but often incomplete). It's a technique that I've used for years, and is a great way to involve nontechnical stakeholders, without risking stuff like "it's already working."
All that said, I think that AI definitely could automate a lot of the repetitive stuff involved in shipping. It's just that the CEO would fire the folks that could teach it, before it can learn, because they think that what they do, is "unimportant."
> with a functioning user acquisition funnel
How do you actually get this. I've got a product, the site is hand crafted, shows the complex product really well (and had good feedback on it) but how do I acquire the users?
It seems as the cost of creating software has plummeted, it's the actual sales side of it that's going to matter even more. I'm stuck at this point.
Who is your ideal customer profile (look up buyer personas) -- if you're B2B figure out both the profile of the company who would buy, as well as the person who would actually buy, and the person who would actually use the software: remember that buyer != user in B2B scenarios, and you'll have to figure out if the buyer, user or both is the best path to getting a sale. If you're B2C figure out your buyer personas so you know where to advertise.
Why would people want your product; sounds like you may already have this down but be ready to explain your value proposition concisely.
How will these people hear about your product -- a SaaS that falls in the woods doesn't make a sound, you need people to learn your product exists before they can pay for it. This is the point of figuring out buyer personas, you need to meet your customers where they are, and you can't know where they are unless you know who they are. This is highly dependent on your product/personas, and could range from running LinkedIn ads to SEO to having a Bluesky brand account to going to local meetup groups or conferences and trying to get your first handful of users in-person.
The sooner you realise this the better you will be moving forward. I won't debate you here, only returned to thank the other user that helped. Reflect on what is possible now compared to 3 years ago.
There is a definite lack of appreciation for the often repetitive grit, toil and maintenance work required to just have profit generating working software running reliably in production.
Don't think I've heard that one but certainly rings true to my experience.
Reminds me of "ninety percent of the game is half mental"
Tangential: it's always made me wonder about teams that believe "80% effort" is optimal.
As a matter of fact I tend to think of it the first 80% is 80% of work, the 80% of the 20% left is same as first 80% of work. The last 4% polishing is another first 80% of the work. I think that is a good rule for general project management.
Then there's the technical debt!
Shipping is frankly the easy part. It's the operating overhead that often breaks you.
I liken it to free puppies.
I have always prided myself on writing concise, high-Quality code, because it tends to be quite debt-free.
So far, LLMs seem to deliver code with "Louie Da Loan Shark"-levels of tech debt.
That describes my last week. What made it most annoying, was the need to release through TestFlight, because the memory issues would not appear, when tethered. Also, I was checking in constantly, because I had to revert and reset the context, several times.
It seems like the cost of changing hardware code is high enough to still insist on building it high quality, is that accurate?
Hardware people insist on treating software the same as firmware.
Bad firmware can cause real-world, physical damage, and be impossible to fix without a hardware recall. A firmware bug can wipe out a hardware company. A software bug can be embarassing, but can also be corrected a lot more easily (as long as it is being treated differently from firmware).
Maybe a couple of years ago, but these days, Opus 4.8 is frankly writing better software than what I've seen over the previous decades in non-tech enterprise. These previous two months, we've replaced so much technical debt we've been dragging along for the previous 5 years as our team went from 25 to 3 people.
This is in non-tech enterprise in Denmark and AI had absolutely no impact on us going from 25 to 3. That was all Putin and bad business decisions on the c-levels. Like keeping flexible loans to fund projects on the books when the interests rates were 0.01% because they might go to 0.001%. Anyway, I'm getting to the point where the AI does 100% of the work, but only if it's piloted by people who know what security, resource consumption and compliance is. The code itself is excellent though.
It likely depends on the implementation, and the tool.
In my work, the Swift code is not really that good (but it’s not terrible), but the PHP code is very good (better than mine). I use ChatGPT. Maybe Claude might give better Swift, but I’ve invested quite a bit of context in ChatGPT.
No. Opus 4.8 still writes bad code, just like every other time AI boosters have claimed "but the newest models are really good".
If you want, you can go through my history and you'll find that I haven't exactly been a fan of AI, but it's silly to deny that it's gotten good.
I remember a .sig that went something along the lines of:
I hate code, and want as little as possible in my software.That's common with newer engineers (and now, non-engineers). I believe that Mr. Dunning, and Mr. Kruger had something to say about it.
I also spent most of my career at hardware-oriented companies, and shipping hardware is orders of magnitude more difficult than shipping software.
It's as if the installation part is the hard bit, and after that it'll take care of itself for ... far enough into the future that it won't be <current manager>'s problem. It is solved.
... and that's just using the system, not fixing bugs and adding features.
I am not a children person. But I love this analogy.
To deliver something nice, we also must accept some suffering.
Good CEOs don't see their employees as an expense.
Good CEO's make such good money on their employees that everybody gets raises and bonuses, the company grows responsibly, and the stock is a good investment.
Too bad it's out of reach for so many executives.
If that's too challenging, I understand, but if they had real confidence as a business operator I don't see why so many would be kicking out anybody over AI when they could at least continue to make the same money off the same people going forward. OTOH in cases where AI is almost ideally helpful it should be no surprise if hiring is slowed, and doing the accounting it could very well add up about the same either way. But one way clearly indicates the limited vision of a lesser leader, why settle for that?
Two of the most macro giveaway characteristics are emotionalism and superstition.
Not just for CEO's and other executives, but anyone in a leadership position or with decision-making tasks to perform.
One of the legendary combinations is when superstition is used in place of technology, and emotional reactions completely prevail instead of genuine business acumen.
It's a pretty good estimate that almost every CEO who thinks it would be good if AI replaced their employees, that these CEO's fit squarely in the superstitious camp.
I would say that's just one growing subset of a much larger smorgasbord of superstitions to choose from, and some big-shots are bound to indulge a whole lot more than others :\
In that sense Altman and Dario et. al. were extremely successful in their cringeworthy campaign to establish themselves as priests of a new machine god religion. Even the people who don't want it believed them.
The good news is at least this year companies are starting to get a little more thoughtful about why they're paying for AI and what specific business function it serves.
Realities:
1. AI is a tool. You don't replace a job with a tool, just like you don't replace an apple with a sock. It was always an error of classification to think this way.
2. AI is a useful tool. For every CEO who thinks it justifies mass layoffs, there are dozens of people who don't want to admit that it does have a lot of utility. Anyone who isn't figuring out where this tool can make them more productive will have a hard time down the line imho.
3. We can infer from the priors that jobs will continue to be a thing, just like they still were after the inventions of printing presses, cars, power looms, etc. but there will be some pretty massive churn, some roles maybe disappearing entirely, new ones getting created, same goes for skill sets.
4. Businesses will use this churn to the best of their ability to either reduce costs or increase output. That second part is the key the AI haters don't seem to recognize. Thanks to competition, not every business wants to just fire everyone. Yeah, America's financialized and monopolized and less competitive than it used to be, but still, plenty of businesses will repurpose their budgets to produce more and expand.
So in terms of real specific and concrete things I've seen so far.
If you're in customer support that's a pretty rough spot, a well designed RAG system can turn 20 minutes of research into 20 seconds. Customer support budgets flow downstream from actual usage/customer base so if they can do more with less people will get laid off, they don't expand scope, they automate and cut the budget.
If you're a developer, your position's a lot more secure than that, coding agents are pretty incredible but they are simply not at a point where they can think through architectural decisions, and they occasionally go off the rails and trash everything. These things need to be operated and steered. Yes that's 100% the future of the profession and I'm sorry if someone doesn't like that, being a blacksmith who forges metal things by hand is also very niche these days, kind of sad if you loved blacksmithing but it happens. Devs also have to be aware that a PM/product owner can likely do some of their job now and I think any dev whose preference was to avoid thinking about customer or business requirements is going to find his utility is shrinking. A mass shrinking of the profession is unlikely but things will change and the only rational paths forward honestly are to retire or to figure out now how you fit in, it's a career opportunity if you get ahead of the curve even.
Lastly there is a whole other domain now which for lack of a good term I'll refer to as "prompt engineering," it requires some level of systems design thinking, but basically no programming expertise. The best candidate for this work is a person who possesses business process knowledge as well as systems oriented thinking. Maybe these jobs will end up finding a home in the IT department or something. As an economy we're barely recognizing them yet but I see that in engineering we can increasingly implement places for a prompt input, and then hand some workflow/business domain decisions off to someone who understands them better and they just tweak their prompts over time to get a great system. Pretty sure new jobs will be created and formalized around this over time.
It is a fairly good summary of my PoV.
It's happening! We can see it! The future is somewhat legible and in it we don't all die! (Well we do, but mostly for the usual reasons)
We just gotta keep getting out of bed and making a smart choice or two between now and then!
I think it’s exceedingly rare that a CEO is actually competent at their job. In most cases it’s the labor class propping the company up, and in some cases the workers are doing so against the wishes of the CEO. Not that executives want to ruin the company, they’re just incompetent and therefore make terrible decisions constantly.
I know this can be hard for engineers to sometimes accept, but relationships (aka politics) are a key part of business. Rarely is one technical solution absolutely superior to another, making purchasing decisions come down to relationships.
Politics is also about compromise and managing a bunch of differing opinions/desires, which is one of the key skills of a CEO.
Except, it seems, when it comes to the current AI zeitgeist. Then it feels a lot more like CEOs are taking a "my way or the highway" approach. Maybe they can compromise on just how necessary it is for all employees to use AI?
But... that is kinda the job? CEOs are, first and foremost, the public face of the company. They're the one who talk to VCs / banks, regulators, major customers, the press. They're very highly paid PR reps / fall guys that shield everyone else, including the board of directors and all the VPs and SVPs, if something goes wrong.
For most companies, especially large companies, it's not important for a CEO to be good with software engineering, business development, etc. That, at least in principle, can be handled by other parts of the hierarchy.
If you are the CEO of a company, you should have expertise in whatever your company does, and If your company is primarily a software company, then you should have expertise in software engineering. You cannot effectively manage something that you don't understand.
Knowing which ass(es) to kiss when: $9,999,999
And that's how CEOs justify their exorbitant compensation
However, I think there's a reason why coops seem to succeed at smaller scales, but there are essentially no large innovative coops.
There are a few large boring coops, and some small innovative ones, but seemingly something is making the CEO/investor board model the one large innovative companies are all using.
I suspect that it's both (1) access to capital is far harder for coops, and (2) that workplace democracy and hardcore mission focus aren't fully compatible. That is, "you cannot serve two masters" without losing focus on one of them.
If a company doesn't accumulate capital, it doesn't scale in complexity. It can grow by having more people do more of the same things, but it can't move into markets that demand anything complex.
Do they tend to make greater revenue or profits? Pay higher wages and offer greater benefits to employees?
I think there's also a tendency towards longer tenure and higher value employees due to the investment in the company's future being a sort of central tenant of their attractiveness.
There are some case studies here, but it's only one professor in a largely non-capitalist approach overall:
https://www.reddit.com/r/Cooperative/comments/1bm5s5s/richar...
https://en.wikipedia.org/wiki/Workplace_democracy
Acting like centrally planned dictatorships is a good form of collaboration is just so off base. There's no reason to think that introducing democracy into the work place wouldn't immediately benefit both workers + customers.
If this sounds crazy the C suite + board already vote on who gets hired into the executive team, vote for the direction of the company, and vote for their compensation packages (hint, they never decrease them).
Why shouldn't workers be legally enabled to do the same? What is the justification to this? I'm curious to hear it because the only way people can justify the current system is declaring that some people are actually more deserving of prestige, money, and benefits while others deserve to suffer.
With income inequality increasing, healthcare outcomes worsening, and children literally becoming stupider isn't it time to question the current system and ask ourselves if this is the society we truly want?
Because I would love for it to be true.
https://en.wikipedia.org/wiki/Ricardo_Semler#Semco_1990%E2%8...
There is academic research on this too if you're curious but it's mostly in English, Spanish, and Portuguese.
But yes, there isn't much "evidence" because this system hasn't been tried en masse; however if you look at our current neoliberal hellscape, it's pretty hard to imagine it doing worse. Also neoliberalism wasn't really "tried" either, it was thrusted upon us by a group of individuals that wanted it.
One thing to keep in mind is that society can change quite quickly if you want it to. I'm sure the children that died working in factories during the 1800s never imagined such a society where children are valued, cared for, educated, and protected but it did happen.
It has happen before and it can happen again. It only happened because people were willing to fight for it.
The rules are allowed to be changed at anytime if we deem so, a better world is possible.
I believe the Germans have had success with including labor representatives on corporate boards. Maybe we can start there.
That was never put to a vote but it still thrusted upon a country where the results are what you would expect: the worse income inequality ever seen in the history of the nation, life expectancy has increased, deaths of despair have reached record highs, more children go to bed hungry, healthcare is being ripped from civilians, and corporations are legally allowed to poison and kill civilians (health insurance companies with their death panels, manufacturers causing cancer valleys) with zero legal repercussions.
So yeah maybe we should actually go the extreme into the other direction, if democracy is good enough to lead nations it's good enough to run businesses. If you're a worker IDK how you would argue otherwise. Being able to keep your boss/leadership accountable by voting for them out seems like a win for every workplace metric imaginable.
Imagine how better of a company Meta would be if Zuckerberg wasn't allowed to waste billions accomplishing nothing. In a just society he would have been voted out, but in a neoliberal society he is granted an insurmountable amount of wealth.
I'm sorry but this society sucks and acting like we can't do better, be better is beyond pathetic.
Health care is a different topic and yes, socialized healthcare systems seem to perform better across the board.
The idea that opponents of neoliberalism have to recreate all aspects of society and consider every potential edge case isn't realistic, and it's not how systematic change actually occurs.
Once again, the Q is this. Where is the evidence that neoliberal economics has helped Americans? Income inequality is at its absolute height, along with deaths of despair.
I'm sorry but why are you personally defending such a sick society? Did you vote to implement neoliberalism in the 1970s or what? Where you the one who told Ford to tell NYC to suck it?
There was an unequivocal claim that it will work better than our current system.
“Acting like centrally planned dictatorships is a good form of collaboration is just so off base. There's no reason to think that introducing democracy into the work place wouldn't immediately benefit both workers + customers.”
That sounds more like there’s no evidence that it won’t work than an unequivocal claim that it will.
Now, corporations usually have the problem of competition, so if they aren't responsive (or at least responsive enough), they get out-competed by those that are. Is that enough to make them different from governments? Perhaps, but I don't know.
That's just neoliberalism baby!
Yet they seem still inclined to elect them.
Much of the “competency” of a CEO in practice is to be able to accept the relentless drama and abuse without turning into an emotional wreck. Yeah, they have to make decisions, but that isn’t the part that makes the job difficult. That role takes an insane toll on the human spirit, and very few can do it for any length of time.
The cush job is often being CEO adjacent. You get most of the perks but also avoid most of the emotional abuse and drama.
I don't hold much empathy for higher-ups, for other reasons. But its clear to me man was not meant for this. Large orgs are almost destined to be dysfunctional, as they move beyond "you have to study hard and make a real effort to remember everyone" to "no matter how much you try it is literally impossible to remember everyone, more people are being hired and fired each day than you can keep up with"
So it self selects for sociopaths. Good to know
Group 1: company stays small, like a ma & pa shop or small service, with few employees. This is a mixed bag of really hard working individuals and scumbags. The scummy ones aren't breaking any laws or doing anything nefarious, they just found a financial opportunity and shoved themselves in as a middleman and just subcontract out everything and do literally nothing except sit to the side and collect a paycheck.
Group 2: large company, making a name for themselves with hundreds of employees. I only know one guy who meets this category, and he is incredibly talented and hard working
Group 3: wildly successful, international company. Again I only know one guy, so I can't generalize, but he is super lazy. I think this is what y'all are referring to when y'all are hating on CEOs. To give him some slack, he was hard working when we met, and he actually made numerous companies, but this one exploded and now he lives in luxury. He hasn't lost his moral compass, but he doesn't really needs to work hard anymore either.
I should caveat that all of these folks who I know built their company. They weren't hired into one and fought their way to the top with politics or anything. Maybe I surround myself with ambitious people rather than politically toxic people, because otherwise I think it is odd that every single one of the many CEOs I know built their company, rather than getting the seat in a different way.
on the contrary, it seems to be one of the few jobs that seems to require absolutely no qualifications to have.
What you need to do to be CEO is.... convince someone to lend you money in the hope that you'll get it back to them.
I've worked under some absolutely awful people who wouldn't pass an interview anywhere, but somehow they're CEOs, because they can smarm there way into more money consistently.
And it should be noted that many of these people lending money are in a similar situation of not being required to have any qualifications. Sure, some of them have worked their way up through sound investment after sound investment, but many of them were either born into their position or simply got lucky at some point along the way. Just think of all the money investors threw away pursuing crypto and NFTs for example. Many of those investments were transparently stupid from day 1.
FTFY
FTFY
This is a broad range of skills and to actually be a CEO, you need to really hone these skills and be among the very top. To be good at those, just enough to qualify for a modest CEO role at a small start-up, you generally don't have the time to be good at anything else.
Saying that you don't need any skills is mischaracterizing it. You don't need any value-creating skills, yes, but you need significant value-capturing skills.
I can imagine a world were all companies become empty of workers and only executives remain and they would just have meetings with each other while they starve and would explain it away as a new diet they're on. There would be no petrol and they would be forced to walk to work and would say that it's their new fitness routine... And they would all believe each other.
Most of them got into a prestigious school on legacy, paid for by wealthy parents. Many were above average IQ, but by no means geniuses. They had access to computers earlier than others, due to said affluence. They seem unable or unwilling to comprehend they're overwhelmingly on average, "nepo babies" to steal a term from the world of entertainment.
Getting funding is a value add, but I agree calling it "skill" misses most of what makes someone "good" at it. We've built things to overwhelmingly rely on funding gated by other private school people though. It would be nice if we could have that person with access pitching without them also being in charge of running a company, product development, or managing people. But then it would require the same of the investors. The investors would then need to evaluate products and ideas and markets. And the markets would have to reward that. Things would need to be different.
I think CS is a little unusual in that places like Berkley are ranked highly. (Interestingly, Harvard has a rather low CS rank and Zuck was in the process of transferring to psych because he can't handle anything quant, but due to FERPA no one will call him out even as he repeatedly steps outside the law)
>Getting funding is a value add, but I agree calling it "skill" misses most of what makes someone "good" at it. We've built things to overwhelmingly rely on funding gated by other private school people though.
I think part of the issue is that a big chunk of startups are straight up grift. My complaints about gatekeeping aside, I think if I had a legitimately good idea I could either submit to yCombinator or talk to contacts who've cashed in stock and get investors.
That's mostly due to the fact I'm well known for valuing authenticity though and my personal brand is such that folks would take my proposal seriously.
I met a LOT of people who went to places like Stanford who basically... they always meet the metrics, at the expense of all else.
Anyways, I think in general we try to generate too many "startups" when we're really striving for small businesses.
But because the funding is the truly difficult part, we hyperfocus on that.
Meanwhile, I've seen plenty of startup ideas that while benefiting from the Ycombinator social network, have initial costs such that you could hit up a few rich friends who've known you a while with a solid business plan and get bootstrapped... but that would require domain knowledge and the respect of your peers, two things many founders lack ;-)
I spent most of my time in government, and I was quite shocked in private industry how enthusiastically nearly everyone had taken to the class divide. It was a bit like A Brave New World. Even when resenting it, the lower class totally bought into the mythos of the upper class. It was very clear I would never be an executive at my company, but at the same time, my particular company was riddled with incompetent and corrupt executives.
I didn't feel or sound like one of them, and I refused to lie or bullshit. And every one of them could tell, and it forever marked me as an outsider.
With that said, I've been programming for 25 years and I've only been a CEO for 3, so take what I said with a pinch of salt.
I do think people overestimate titles like this a lot, though, and it really comes down to what the company actually does and what is demanding for that company at that position/role. The CTO of a some-bullshit-as-a-service company may as well be straight out of college, because they're likely doing something trivial that literally anyone (including LLMs) could put together. The CTO of a well-used and reliable streaming service that handles a meaningful part of the world's Internet traffic is obviously solving a more interesting and demanding problem, and their decisions are going to be more important.
There was a time when I used to recommend "Out of the Crisis", a book from Demming, to business leaders.
Problem is, "Out of the crisis" still assumes as a premise that companies compete on the quality of their products, that making money comes from actually making and selling stuff. That leaders are not the anti-intelectual morons that believe that absolutely any thing can be explained with a 15 minutes deck, that math and statistics are passtimes for weird geeks that don't add "business value" and because of that, is a book that could have steered us toward a better world in the 80s, but now it is completely useless, because its recipes can't handle the level of degradation things goto into.
have to do politics -> bad ceo
NOT(have to do politics) -> NOT(bad ceo)If you're interested in discussing the specific claims you're making, I really don't think that billions of people are hopelessly addicted to social media, and I would love to hear your basis for claiming this. My understanding (from e.g. https://www.nature.com/articles/s41598-025-27053-2) is that genuine compulsive use of social media is quite rare, and most people who describe themselves as "addicted" are just regular users who enjoy it but kinda feel like it's a waste of time.
> Meta Settles Lawsuit That Claimed Social Media Addiction Screwed Up Schools
> On Thursday, Meta settled a lawsuit brought by a Kentucky school district that claimed the tech giant’s social media platforms have created a mental health crisis at its schools.
> The case was considered the first of its kind and a bellwether (a case that is representative of a large pool of lawsuits and will be a test for future litigation). The plaintiffs argue that social media platforms have had a major negative impact on the mental health of school-age children, which in turn has caused a burden on the education system, as American schools were forced to redirect resources to counter this problem.
> The settlement comes shortly after Meta lost a key bellwether social media addiction trial. Back in March, a judge in Los Angeles ruled that Meta was liable for the adverse mental health effects a now 20-year-old suffered after getting addicted to Instagram from an early age. The representatives of the young woman argued successfully that it was Meta’s deliberate design choices, like the infinite scroll and face-altering filters on stories, that had exacerbated her addiction and subsequent mental health issues like self-harm and depression.
---
https://en.wikipedia.org/wiki/Careless_People#Myanmar_genoci...
> The military junta in Myanmar was facilitated by Facebook to post hate speech that sought to foment sexual violence and promote genocide against the Rohingya. "Myanmar would have been a better place if Facebook had not arrived" Wynn-Williams writes.
> Wynn-Williams argued that Facebook failed to moderate hate speech against the Rohingya in Myanmar, including the use of the racial slur kalar. She noted that the company only had two Burmese language moderators, both based in Dublin, for the entire country, and claimed that one of the two moderators gave a pass to hate speech while removing pro-human rights content. She further claimed that she raised concerns that the moderator was "in cahoots with the" junta, only to have her concerns dismissed by the content team. Additionally, she claimed that her efforts to have Facebook's Community Standards rules translated into the Burmese language were resisted by the company communications team, who told her that "Myanmar isn’t a priority country" in the region.
---
https://en.wikipedia.org/wiki/Facebook%E2%80%93Cambridge_Ana...
> In the 2010s, personal data belonging to millions of Facebook users was collected by British consulting firm Cambridge Analytica for political advertising without informed consent.
> The data was collected through an app called "This Is Your Digital Life", developed by data scientist Aleksandr Kogan and his company Global Science Research in 2013. The app consisted of a series of questions to build psychological profiles on users, and collected the personal data of the users' Facebook friends via Facebook's Open Graph platform.[2] The app harvested the data of up to 87 million Facebook profiles. Cambridge Analytica used the data to analytically assist the 2016 presidential campaigns of Ted Cruz and Donald Trump.
> Other advertising agencies have been implementing various forms of psychological targeting for years and Facebook had patented a similar technology in 2012.
---
https://www.the-independent.com/tech/facebook-manipulated-us...
> Facebook manipulated the emotions of hundreds of thousands of its users, and found that they would pass on happy or sad emotions, it has said. The experiment, for which researchers did not gain specific consent, has provoked criticism from users with privacy and ethical concerns.
> For one week in 2012, Facebook skewed nearly 700,000 users’ news feeds to either be happier or sadder than normal. The experiment found that after the experiment was over users tended to post positive or negative comments according to the skew that was given to their news feed.
> The research has provoked distress because of the manipulation involved.
> Studies of real world networks show that what the researchers call ‘emotional contagion’ can be transferred through networks. But researchers say that the study is the first evidence that the effect can happen without direct interaction or nonverbal clues.
> Anyone who used the English version of Facebook automatically qualified for the experiment, the results of which were published earlier this month. Researchers analysed the words used in posts to automatically decide whether they were likely to be positive or negative, and shifted them up or down according to which group users fell into.
It literally just requires filing an LLC or Corporation. There are several SaaS companies that will do it for you.
I think we'd get zero volunteers from CEOs who have assistants.
(Note: this is not meant to be an insult to human assistants! I think they do a valuable job and should not be replaced by AI either).
The Open AI guy said it's now better than doctors (he said it, not me lol). He's replaced his doctor, right?
CEOs get signals from multiple channels that cantbe accessed by AI or ordinary workers
so that alone becomes a moat
same with sales jobs theres a plane that AI cannot observe (yet)
Before using AI ask yourself: Would you outsource this task, with all the risk that come with it? If yes, go for it. But if no, then don‘t use AI.
a bad king and a bad CEO could be replaced with a spinning top with no loss in productivity (and maybe some gain).
It also made me realize that most the so called “creatives” in marketing and PR also just repeat variations of the same few templates. Not much real creativity there.
I don't think that's the flex he thinks it is.
But AI is expected to lie^H^H^H hallucinate
The code is human + AI, the management is only AI
(discussed 6 months ago https://news.ycombinator.com/item?id=46072002)
Would you rather take instructions from a ruthless robot or ruthless flesh sack?
They're too busy playing golf
Naive and stupid, but it was downvoted and flagged away into oblivion with zero chance for a conversation.
There are also a LOT of bad software developers.
When they meet, the software developer is fired.
The CEO exits after a while, after exercising their stock options...
It was a whirlwind of a ride as the company caught up on 10 years of engineering maturity and 3 years of AI usage progress in 9 months. The improvement in output has been noticeable, and the quality has not dropped. In short, cycle time and throughput rose and quality remained stable.
One of the things we are talking about is the future. As the team learns how to use AI well, the amount of code will grow at a faster pace. The focus is now on writing things we really need, and ensuring the quality does not degrade.
We are trying to get the engineering team to lean into understanding the product and business domain, and also adopting a QA mindset.
One of the engineers is not interested in the business domain. He loves typing code. I am afraid that within six months it will not make sense to have him around. He is relatively junior and wants well-specced tickets, and is reluctant to use AI. Right now, Opus writes better code than him, and solves business problems more acutely, with less time spent on writing careful specs.
If he gets fired, the budget will likely be re-allocated to AI.
In 7 months, it will be fair to say that we replace 20% of the team with AI. If that happens, it will have been a thoughtful process focused on upskilling willing employees, and not a boneheaded hype-driven decision. But it will be judged on the summary and not the process that went into it.
CEOs that look at that and think they need to reduce headcount seem to also be signaling they don’t know what to do with increased resources
Counting token usage as a productivity metric is completely counterproductive. I believe that effectively leveraging AI means reducing wasted tokens, not increasing them.
The visibility gap is serious. I create local activity logs for Claude Code, but most developers have no idea what the AI is actually doing at the file or command level until they look at the logs.
The solution - linux has utility called piper. I downloaded the repo and just told codex - figure out what piper is doing and create me a small utility to do it under windows. So the jolly critter started experimenting with hex commands, then pulled some other repo on which piper depended figured out how to enable said onboard mode and 10-sh minutes later I had small python script that did what i needed to do.
That would have taken probably half a day of work for a human.
There are many stupid CEO and organizations which are not committed to quality. And a lot of employees that are too set in their ways. But the instinct that underinvesting in AI is more dangerous than overinvesting is right. Doomed if you do, doomed if you don't
"To err is human, but to really foul things up requires a computer" - this is from the 60, but right now is turned into overdrive.
This is what layoffs have been about since the pandemic. People in fear of losing their jobs do extra unpaid work and aren't asking for raises. The theoretical potential of AI gives companies the excuse to fire more people. The investment itself is directly used as a reason of why they need to cut back on labor.
Any sufficiently sized business can only feed the insatiable hunger for ever-increasing profits ultimately by cutting costs and raising prices. And what do we have now? High inflation and a decline in real wages. CEOs are just following this playbook.
And the result is that society is bouldering towards collapse. We're seeing the first hints of this with the youth unemployment crisis [1][2][3].
Also, who is going to buy anything when nobody has any money?
[1]: https://www.americanprogress.org/article/americas-10-million...
[2]: https://www.brookings.edu/articles/twelve-ways-to-fix-the-yo...
This assumes that a mass consumer economy is necessary, when it isn't. Mass consumption is relatively new, for most of history economies functioned with just a small consuming elite and large underclass that consumed very little. We are already approaching that again in the states given that the top 10% of earners are already responsible for nearly half of all consumer spending.
There's a floor even in a mostly automated economy where some services are resistant to automation simply because the human element is the product. Luxury hospitality, personal care, etc. That billionaire is going to want a human masseuse, not a robot.
A highly automated economy could stabilize like this with a small elite population consuming luxury goods & services, served by a low-wage economic underclass human workforce.
Its certainly not a pleasant society, but its also not unsustainable given enough oppression or pacification (bread and circuses anyone?)
As for services increasingly unaffordable by the workers providing them, that's Baumol's cost disease (https://en.wikipedia.org/wiki/Baumol_effect)
I don't have any sources regarding someone preferring humans for certain services over robots, just intuition there, and the fact that consuming human labor and time is itself a status signal of wealth, and the current growth of personal services.
As for connecting the dots, look at Brazil, one of the world's most unequal economies having a small consuming elite and a much, much larger low-wage service underclass. The gulf states as well. Granted, their circumstances don't map cleanly to a post-automation Western economy, but it does demonstrate that a largely bifurcated consumption based economy can exist and can be mildly stable.
Whether the US falls into that direction too will depending on politics. A bunch of mid-career knowledge workers aren't going to willingly to flip burgers in a service economy without some serious surveillance and oppression. But when thinking about it in those terms, the recent push for mass surveillance laws and tech along with the increasingly dangerous rhetoric around protests and "domestic terrorism" start to make sense.
This is not the case. These countries don’t operate/exist in isolation. They are part of global economy. But if this tech has a global scale effect, then the dots are not really connecting. You’re also forgetting the “revolt” factor.
Next, comes natural attrition in a company where a certain percentage will leave every year. Will they get replaced with a human or their budget goes into tokens?
Only when these 2 angles are exhausted, a typical company will start thinking about layoffs.
Now, some companies are already stressed: customer buy AI products instead of theirs, AI makes it easier to build what they offer, customers believe they can vibe code things. These companies will layoff first, because of AI. Not because AI will do the persons job but because the money gets spend differently.
Problem is, a CEO can fire employees, find out it was a dumb decision, then leave with a million dollar severance package. So they don't really care when they're wrong.
Astronaut holding up gun to other astronaut
Always have been.
I wrote about it here too:
https://blog.nilesh.io/post/llms-and-jobs
Just because people have a vague idea of what someone's job is and a deep understanding of their own job, it feels like AI can replace everyone but you.
The problem is that the wrong eyes are seeing it.
We need these kinds of articles to be published in places that executives read, and tailored to their audience.
AI recovery is going to be a big wave of consulting over the next several years, maybe very publicly or maybe quietly, but it's going to be a thing. That doesn't mean "all AI is bad" or any other such nonsense, it means that there are a lot of companies out there right now that are doing it wrong and will need help.
The executives that get ahead of this are going to be the winners.
We're all now on this and we will go together in it till the very end, whatever it maybe.
Look around: lots of places ressurected Lines of Code as a productivity metric for Software Teams. Companies that should have known better, as they are supposedly led by the Elite Human Capital, instituded token usage leaderboards.
We can't stop that thing. It has too much momentum. Sooner or later we would have to pay for our culture of anti-intelectualism in business anyway. If it was not this, it would be another thing.
It's getting exhausting how x field of experts constantly bemoan the coining of one term or another, rather than provide a decent alternative. It's not very goal-oriented thinking. Just empty complaining.
"AI psychosis" tries to group together the phenomenon where people fall in love with an LLM-generated character, the phenomenon where people spend too much time talking philosophy with LLMs and stop expressing coherent thoughts, and the phenomenon where tech evangelists say "AI can do all of these 5 million things" when actually it can't do all of them. But what if these are all different phenomena with different causes and solutions?
This is a broad generalization of employees. There will be some "routine tasks" that can be done by AI, now that is a lot more powerful.
There won't be as many employees needed for routine work - for example L1 and L2 support work. For example, many companies had ML engineers building models for various models. Companies can get that off the shelf from AI companies. They don't need a big team of model builders now.
L2 issues are already involved in some way often revealing some kind of system failure, requiring context and exploration to understand, and judgement (and perhaps even system overrides) to fix.
I could see “automated L2 is the new L1” improvements, but without a big capability jump and/or a resource bonfire, I don’t think even frontier models would effectively replace good L2 staff.
They might magnify good L2 staff so fewer are needed (and maybe even help L1 staff become L2).
This is at a well-known tech company operating at massive scale (and resulting complexity).
L1/L2 tech support is completely dead within a couple years. The delay is only around how long it takes people to realize.
You know who can't do that? People who call L1 support.
The point of a human being on the board is that they can be made to suffer the consequences of bad decisions. Executive pay might seem astronomical, but it is often commensurate with the level of stress and responsibility involved. It's easy to look at the perks and not see the struggle behind them. No one in media is going to get a lot of clicks if they publish articles about how being a CEO is actually really hard and maybe some of what they're doing is actually justified once you assume all of the same context and stress they have.
If we want to do to the executive staff what is being done to the technical staff, I'm afraid we will need to first figure out a way to make the AI experience human emotions as strongly as we do. It often sounds fun in first order terms to threaten to fire a CEO and replace them with a clanker, but have we considered the consequences of this? What would it be like to be under the management of an emotionless robot? Being managed by a robot vs managing robots are wildly different things to me.
I call bull on that. Employees often have just as much stress, often imposed on them from those higher up, where if they don't do well they could get fired and it could mean they can't put food on the table.
Several times I've worked in environments where the stress was incredibly high, and once it even put me in the hospital after a long stretch of working 70 hour weeks to satisfy the insane deadlines my CEO boss wanted (this was at a startup).
Whereas if an executive screws up they just golden parachute to another cushy gig elsewhere, oftentimes, because even if they screw up, they're still valued as having experience running companies by other companies. And even if they cannot, they still likely got paid enough that they won't be struggling financially if they go through a period without a job.
Depends. Is the robot looking out for our best interests? Or is the robot looking out for the shareholders?
I already ask AI to manage a lot of things, including my own activities. It all depends on whether the model can be trusted to act in our best interests.
Which indicates: the management believes there are productivity gains from AI use, but adoption lags due to inertia and reluctance to change existing workflows.
Methinks adoption lags due to management's inability to align incentives such that productivity gains are rewarded.
"If you do something that causes a productivity gain worth X, I will give you some reward with a value Y where Y is less than X but greater than the cost Z of the effort you needed to put in to generate the productivity gain. If the cost Z would be equal to or greater than X then don't do it."
Managers make their work immensely harder on themselves by unnecessarily adding the constraint that they can't get people to do things by paying them fair amounts to do them. Now certainly there are some highly skilled managers out there who can still succeed despite this handicap, and if that earns them a fat paycheck then good for them. But if you don't have those skills you don't get to excuse your failures with an inefficiency you created for yourself.
Due diligence, judgement, and ability to know what the hell is going on are essential skills for management. The token metrics are a complete abdication of all of the above. It isn't a cream you just slather on to boost productivity.
Modern first and second tier software management seems less professional, is contributing less and is generally worse than it was twenty years ago. The quality of the engineering and program managers, their training and commitment to their craft seems really low and is not generally valued. On average team level software management has gotten worse rather than better and, given what is expected and how it is valued, this shouldn't be much of a surprise. It is truly disappointing that what could have been a valuable and productivity enhancing role became so useless.
Things aren't going to change for the better though until the dust settles somewhat on the role of AI in software and systems development and we start again to consider how software should be developed in the 21st century. Maybe it is possible that with AI doing most of the low-level work that the focus will change to building and maintaining architecture and systems. Many programmers might become more like traditional engineers doing a lot more systems work than they do today and continuing to solve problems. Lord knows though it won't be today's software management doing this work; they have nothing in the way of skills to offer to the problem.
Ideally contractors that benefit you personally (eg: your buddy who now owes you one), but definitely contractors that let you outsource the responsibility.
Even better if you get some management consultant to suggest the idea and/or do the subcontracting.
Definitely buys you a few quarters of bonus and some time to land your next gig.
Tech CEOs are apparently suffering from AI psychosis
https://news.ycombinator.com/item?id=48295679
I believe there are entire companies right now under AI psychosis
A* search -> AI
Backtracking -> AI
Neural Networks -> AI
Fuzzy Logic -> AI
Genetic Algorithm -> AI
Deep Learning -> AI
Generative "AI" -> AI
Similar to Tesla naming it's driver assistant "auto-pilot" in 2015 and your average Joe thought he would be able to sleep while the car would drive him to work.
The CEO just hear AI and think of AGI. They expect Skynet.
It's a bad analogy. Autopilot just maintains the aircraft in some state, then there's the flight director which maintains the flight path, and you can connect or disconnect the two at will. When connected the director can change the autopilot state.
To use the flight director you must fully specify your flight. The weight, the fuel, the weather, expected winds, takeoff and landing runway length, runway conditions, expected brake demand, as well as every single waypoint you're going to cross and the expected state at that crossing.
> what the human metaphor means
We learned after high levels of cockpit automation that maintaining situational awareness was still required. Pilots are freed of some stress during high workload portions of the flight, provided they planned correctly in advance, and that zero changes to their flight plan (not likely) occur.
As a result pilots are mostly told and trained to hand fly the plane during take offs and landings if the weather allows for it. You should only use high levels of automation if the situation demands it.
You are arguing the dictionary while I’m arguing the predictable, if not very well calculated and purposeful, misunderstanding.
Cost-saving is quite an easy idea to sell.
https://tomtunguz.com/spacex-openai-anthropic-ipo-2026/
and I don't know what worries me more - a burst in this bubble (and maybe some other tech stocks), or a failure of these valuations to be burst somehow, and even more concentration of capital and power around those corporations.
> This is a bad CEO.
There is one and only one measure of whether a CEO is good or bad:
Does the CEO keep the majority of shareholders happy?
Since they are more often than not kept happy with money, if the AI makes the CEO ask the question above and the result is a larger return on the shareholders' investment, then that is a good CEO.
When your domain of knowledge considers Jack Welch to be a genius, there is no floor.
Cue rationalizations claiming that it isn't:
My company does something dumber now. A leaderboard of how many lines of code you shipped, weighted by how complex they were (assigned by a heuristic). You can imagine the incentive this creates. I wish we just measured tokens
> The problem tends to show up when a CEO is handed an agentic tool like Claude Code, and has it create something, which will work just fine, and thinks “oh, wait, why do we need so many people, when I can just sit here and make things work?”
> This is a bad CEO.
As described, this seems to me more like a lack of reasoning/critical thinking ability, and it's not unique to CEOs. Tracks more with a combo of "Gell-Mann Amnesia" and automation bias IMO.
> This all reminds me of cargo cult thinking: The CEO knows that somewhere in the org, employees are pecking away at computers and work gets done. So they figure that themselves pecking away with Claude Code and seeing work get done is the same thing. It’s not. All those other steps those people are handling — the ones the CEO never sees — still need to happen.
"Cargo culting" as described here by the author may be happening. But, I think it's CEOs seeing other CEOs doing layoffs and claiming it's because of AI efficiency gains. They see the other CEO's stock go up/get hyped/etc, so they decide to do it. I think it's the same thing that happens inside companies IE people see how others behave and it works, so they do the same. Effectiveness aside because that's not at all what I'm arguing, AI is just the current flavor; it is a very safe thing to "cargo cult" at the moment.
I'll say this, laws and regulation are sorely needed. all this hate against billionaires, ceos, ai-bros, whatever... might or might not be warranted, but it is fruitless. Redirect this energy to your law makers.
In China for example, they made it illegal to use AI for the sole purpose of replacing human workers. The CEOs aren't bad CEOs, they aren't great either, it depends on the outcome. There are scenarios where entire job roles can be replaced by LLMs, but for complex roles like developers, you always need some human devs still, but likewise, almost always less of them than before. However, although less devs might be needed to do the same work, in some cases LLMs open up possibilities that weren't there before, so more devs babysitting LLMs or working on designing/shipping more features is also a strong possibility.
I mean, companies aren't trying to simply save cost on employees, they also want to maximize profits. Less devs per feature isn't the same as less devs period.
Overall, I'll say that demand creates its own supply. The internet itself killed many job roles and reduced the number of people you needed for many others, but it's not like we have the huge unemployment many were afraid of decades ago, if anything it created lots of more jobs. LLMs simply can't do everything people can, so they're not a drop-in replacement, that alone should mean a lot in terms of supply/demand economics.
You mean, this is an entirely made-up figure.
A "unit of work" that required X people to complete in Y time can now be done by X/Z people in Y time, where Z is whatever efficiency you are able to get out of applying AI tooling to your business.
For some companies, Z might be less than 1 though. ;-)
So you still need skilled people, just not the same amount as before, because you have different tools available to you.
This has happened before with other advancements in industrial/technological automation. It's not a new concept.
I did try to account for that with this line:
> For some companies, Z might be less than 1 though. ;-)
What you describe makes sense and has always been the case with new technology overall
When the person who knows what's needed can handle the technical execution themselves, you no longer need that second person.
I certainly wouldn't say you need "more humans"
For who? Will it ever be read? I’m bias on good documentation and I think AI is better at publishing documents for machines, for now.