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on Gopher (inofficial)
URI Visit Hacker News on the Web
COMMENT PAGE FOR:
URI McKinsey wonders how to sell AI apps with no measurable benefits
rchaud wrote 2 min ago:
McKinsey 2 years ago:
> The firmâs earlier research suggested that 2027 would be the first
year when AI technology would be able to match the typical humanâs
performance in tasks that involve ânatural-language understanding.â
Now, McKinsey reckons it will happen this year."
> "Generative AI will give humans a new âsuperpowerâ, and the
economy a much-needed productivity injection, said Lareina Yee, a
senior partner at the firm and chair of McKinsey Technology, in the
report.
-
URI [1]: https://archive.is/mhYIn
rsynnott wrote 41 min ago:
> Software vendors keen to monetize AI should tread cautiously, since
they risk inflating costs for their customers without delivering any
promised benefits such as reducing employee head count.
... Wait, why would the _vendor_ care about that? It's the customers
who should be cautious; unscrupulous vendors will absolutely sell them
useless snake oil with no qualms, if they're willing to buy it.
> These leaders are increasingly making budget trade-offs between head
count investment and AI deployment, and expect vendors to engage them
on value and outcomes, not just features.
The cheek of them! Actually demanding that the product be useful!
capestart wrote 43 min ago:
the hype surrounding AI is exaggerated, but a good deal of the tools is
not providing real value. Customers are observing that their costs are
increasing without the expected productivity gains or layoffs. The
absence of quantifiable ROI and obscure pricing structures are major
deterrents. It will be difficult to convince people about the real
potential of AI until the sellers establish unmistakable advantages and
fix the pricing.
silexia wrote 51 min ago:
Did McKinsey write this with AI?
afavour wrote 51 min ago:
Occurs to me that AI is a fundamental threat to the likes of McKinsey.
You bring in the consultants when you want to make a decision but don't
want any of the responsibility for making it. In the future they'll
just give that task to an anonymous AI. "Nothing we can do!"
_fizz_buzz_ wrote 56 min ago:
I recently talked to someone who works at a company that builds fairly
complicated machinery (induction heating for a certain material
processing). He works in management and they did a week long workshop
with a bunch of the managers to figure out where AI will make their
company more efficient. What they came up with was that they could feed
a spec from a customer into an AI and the AI will create the CAD
drawings, wiring diagrams, software etc. by itself. And they wrote a
report on it. And I just had to break it to him: The thing that AI is
actually best at, is replacing these week-long workshop where managers
are bs-ing around to write reports. Also, it shouldn't be the managers
doing a top down approach where to deploy AI. Get the engineers,
technicians, programmers etc. and they should have a workshop to make
plans where to use AI, because they probably already are experimenting
with it and understand where it works well and where it doesn't quite
cut it yet.
npilk wrote 1 hour 4 min ago:
> For every $1 spent on model development, firms should expect to have
to spend $3 on change management, which means user training and
performance monitoring
I think the general point here is true, but it's also brilliant framing
from a company selling consulting services.
caminante wrote 51 min ago:
It couldn't get sillier. Oh wait!
> Price levels: How should vendors set price levels when the cost of
inferencing is dropping rapidly? How should they balance value
capture with scaling adoption?
This is written for B2B target clients as if it's pulling back the
veil on pricing strategy and negotiating. Hire McKinsey to get you
the BEST⢠deal in town.
btbuildem wrote 1 hour 16 min ago:
This is because they're trying to reduce the wrong headcount. The
largest inefficiencies in corpo orgs lie in the ways they organize
their knowledge and information stores, and in how they manage decision
making.
The rank and file generally have a really good grasp on their subset of
the domain -- they have expertise and experience, as well as local
context. Small teams, their managers -- those are the ones who actually
perform, and deliver value.
As you move up the hierarchy, access to information does not scale.
People in the middle are generally mediocre performers, buried in
process, ritual and politic. In addition to these burdens, the
information systems do their best to obscure knowledge, with the usual
excuses of Safe and Secure (tm) -- things are siloed, search does not
work, archives are sunsetted, etc.
In some orgs tribalism also plays an outsized role, with teams acting
competitive, which largely results in wasted resources and seven
versions of the same failed attempt at New Shiny Thing.
Then as we look higher yet in the hierarchy, the so-called decision
makers don't really do anything that cannot be described as "maximize
profit" or "cut costs", all while fighting not to get pulled down by
the Lord of the Flies shenanigans of their underlings. They are the
most replaceable.
A successful "AI Transformation" would come in top-down, going after
the most expensive headcount first. Only truly valuable contributors
would remain at that level. Organizational knowledge bases would allow
to search, analyze and reason about the institutional knowledge accrued
in corporate archives over the years, enabling much more effective
decision making. Meanwhile, the ICs would benefit from the AI boost,
outsourcing some menial tasks to the machine, with the dual benefit of
levelling up their roles, and feeding the machine more context about
the lower-level work done across the org.
fluidcruft wrote 8 min ago:
I think another barrier is that end users don't trust IT to not pull
the rug out from under us. It's quite a bit of effort to learn and
figure out workflows for actually getting work done and IT doesn't
tend to give a shit about that. Particularly enterprise IT's attitude
about trials can kiss my ass. Enterprise IT has their timeline, and I
have my deadlines. I'll get to it when I have time.
But particularly we're always dealing with IT security "experts"
taking things away and breaking everything and never bothering figure
out how we're supposed to use computers to actually get any work done
("hmmm. we didn't think about that... we'll get back to you" is a
common response from these certified goons). Apparently the security
gods have decided we can't have department file servers anymore
because backups are too difficult to protect against ransomware or
something so we're all distracted with that pronouncement from the
mountain trying to figure out how to get anything done at the moment.
josefritzishere wrote 19 min ago:
Management will not volunteer to replace themselves. So that would
mean that if that's all that Ai is trully good at... the product is
unsalable.
apwell23 wrote 1 min ago:
do you mean a VP laying off a middle manager would send a signal
that he can be similarly replaced?
tempodox wrote 35 min ago:
Logically youâre right, but power does not follow logic. And so
itâs the lowest levels that get replaced by âAIâ.
re-thc wrote 42 min ago:
> A successful "AI Transformation" would come in top-down, going
after the most expensive headcount first.
Do you still need an "AI Transformation" then? Sounds like just axe
the CEO or cut their enormous salary = profit?
nostrademons wrote 53 min ago:
I've wondered sometimes what the root of this dynamic is, and why
corporations are as inefficient as they are. I've come to the
conclusion that it's deliberate.
When I look at top-level decision-makers at my Mag-7 employer, they
are smart people. Many of them were go-getters in their earlier
career, responsible for driving some very successful initiatives, and
that's why they're at the top of the company. And they're very
intentional about team structure: being close enough to senior
directors and VPs to see some of their thinking, I can tell that they
understand exactly who the competent people are, who gets things
done, who likes to work on what, and then they put those people at
the bottom of the hierarchy with incompetent risk-averse people above
them. Then they'll pull them out and have them report directly to a
senior person when there's a strategic initiative that needs doing,
complete it, and then re-org them back under a middle-manager that
ensures nothing gets done.
I think the reason for this is that if you have a wildly successful
company, the last thing you want to do is screw it up. You're on top
of the world, money is raking in from your monopoly - and you're in
zugzwang. Your best move is not to play, because any substantive
shift in your product or marketplace risks moving you to a position
where you aren't so advantaged. So CEOs of successful companies have
a job to do, and that job is to ensure that nothing happens. But
people's natural inclination is to do things, and if they aren't
doing things inside your company they will probably be doing things
outside your company that risk toppling it. So you put one section
of the company to work digging holes, and put the other section to
work filling them in, and now everybody is happy and productive and
yet there's no net external change to your company's position.
Why even have employees then? Why not just milk your monopoly, keep
the team lean, and let everybody involved have a big share of the
profits? Some companies do actually function like this, eg. Nintendo
and Valve famously run with fairly small employee counts and just
milk their profits, some HFT trading shops like RennTech just give
huge employee dividends and milk their position.
But the problem is largely politics. For one, owning a monopoly
invites scrutiny; there are a lot of things that are illegal, and if
you're not very careful, you can end up on the wrong side of them.
Two, owning an incredibly lucrative business makes you a target for
competition, and for rule-changes or political action that affect
your incredibly lucrative business. Perhaps that's why examples of
highly-profitable businesses that stay small often involve staying
secret (eg. HFT) or being in an industry that everybody else
dismisses as inconsequential (eg. gaming or dating).
By having the huge org that does nothing, the CEO can say "Look, I
provide jobs. We're not a monopoly because we have an unfair
advantage, we compete fairly and just have a lot of people working
very hard." And they can devote a bunch of people to that legal
compliance and PR to make sure they stay on the right side of the
government, and it also gives them the optionality to pull all those
talented people out and unmuzzle them when there actually is a
competitive threat.
apwell23 wrote 8 min ago:
> So CEOs of successful companies have a job to do, and that job
is to ensure that nothing happens. But people's natural inclination
is to do things, and if they aren't doing things inside your
company they will probably be doing things outside your company
that risk toppling it. So you put one section of the company to
work digging holes, and put the other section to work filling them
in, and now everybody is happy and productive and yet there's no
net external change to your company's position.
i work at a large music streamer and this perfectly describes my
workplace. when i was outside i never understood why that company
needs thousands and thousands of ppl to run what looks like
stagnant product that hasn't changed much in years.
potatolicious wrote 40 min ago:
> "Why even have employees then? Why not just milk your monopoly,
keep the team lean, and let everybody involved have a big share of
the profits?"
So we're seeing this play out. There are two factors that exist in
tension here:
- The valuation of many of these companies depend on the perception
that they are The Future. Part of that is heavy R&D spending and
the reputation that they hire The Best. Even if the company mostly
just wants to sit and milk its market position, keeping the stock
price afloat requires looking like they're also innovative and
forging the future.
- Some companies are embracing the milk-it-for-all-its-worth life
stage of their company. You see this in some of the Mag-7 where
compensation targets are scaling down, explicit and implicit
layoffs, etc. This gear-shifting takes time but IMO is in fact
happening.
The tightrope they're all trying to walk is how to do the latter
without risking their reputation as the former, because the mythos
that they are the engines of future growth is what keeps the stock
price ticking.
arethuza wrote 45 min ago:
Have you seen the "sociopath, clueless, loser" model?
URI [1]: https://www.ribbonfarm.com/2009/10/07/the-gervais-principl...
apwell23 wrote 7 min ago:
these articles uses to be so popular in HN back in the day. now
its back to "let pretend we are meritocracy. politics is just
learning how to work with other ppl" .
nostrademons wrote 41 min ago:
Yeah I have. Was a major influence on my thinking, though like
all models, it's incomplete. A lot of my comment is filling in
the holes in that series - what are the mechanisms by which
sociopaths make the organization function? Why does the system
as a whole function like this?
lenerdenator wrote 1 hour 1 min ago:
> This is because they're trying to reduce the wrong headcount.
> A successful "AI Transformation" would come in top-down, going
after the most expensive headcount first.
This isn't a mistake. McKinsey consultants and their executives at
their clients are a part of the same clique. You don't get into
either without going to the right schools, being in the right
fraternities, and knowing the right people. "Maximize profit" and
"cut costs" are to be read as "keep the most money for ourselves in
the form of earnings per share and dividends" and "pay fewer people".
And since you can convert shares to money by gutting companies,
there's no real incentive to remain competitive in the greater
marketplace.
daft_pink wrote 1 hour 16 min ago:
I definitely find some of the features AI is going into like my PDF
reader are useless and troubling
harvey9 wrote 1 hour 1 min ago:
Adobe Reader on my work pc doesn't even do ctrl-f very well.
luciferin wrote 1 hour 18 min ago:
I am curious if the timing have impacted the inability to measure a
benefit. AI is rolling out at the same time as widespread return to
office campaigns. Remote work was widely studied and touted as
improving efficiency, but no one is showing the drop for RTO. Is AI in
part just balancing it out? There's also an ongoing massive brain
drain. Many companies are either laying off their most tenured and
competent employees, or they are making life miserable for them in the
hopes that they quit.
All of this said, using AI in your back end takes a huge amount of time
from your users and employees. You have to vary multiple prompts, you
have to make the output sane, touch it up, etc. The most useful part of
AI for me has been using it to learn something new, or push through a
task that I otherwise couldn't do. I was able to partially rewrite a
logging window to reduce CPU use significantly. It took me over two
weeks of back and forth with AI to figure out a workable solution and
implement it into the software. I competent programmer probably could
have done it better than I did in less than an hour. There's no
business benefit to a help desk person being able to spend 2 weeks
writing code that an engineer would be much better suited to handling.
But maybe that engineer could write it in 10 minutes instead of an hour
if they used AI to understand the software first.
SecretDreams wrote 1 hour 13 min ago:
> Is AI in part just balancing it out?
Likely, no. In my industry, I see a fraction of ICs using it well, a
fraction of leadership using it for absolute dog shit idea
generation, and the remainder using it to make their jobs easier in
the short run, while incurring debt in the long run since nobody is
"learning" from AI summaries and most people don't seem to be reading
the generated "AI notes" sent in emails.
By and large, I think AI is going to hurt my workplace based on the
current trajectory, but it won't be realized until we are in a hard
hole to dig out of.
its-kostya wrote 1 hour 19 min ago:
We have to accept that sometimes technology that was envisioned to
change the future one way, may be beneficial in other ways instead -
and that's okay. We are very clearly still in the phase of "throw AI at
everything and see where it is useful." For example, just yesterday I
was sent a contract to sign via DigiSign. There was a "Summarize
contract with AI" button. Having read the contract in full, I was
curious how good the summary would be. The summary was very low
fidelity and did not go into the weeds of the contract and I would be
essentially signing the contract blind. Although AI is pretty good at
summarizing key point of things like articles and conversations, this
was a very poor use case imho. But hey, they tried it and hopefully see
it is a waste. Nothing wrong with iterating we just have to converge on
acceptable use cases.
cozzyd wrote 1 hour 18 min ago:
I wonder if the AI summary could be legally perilous in this case
rsynnott wrote 33 min ago:
I assume it had the usual "this is AI, and thus probably bullshit"
disclaimers that one finds on such things.
HelloMcFly wrote 48 min ago:
Easy to imagine that many organizations using it don't necessarily
want the signees to really read the document in full anyway, much
less get an informative summary with Reasons To Be Cautious of
Signing as one of the summary categories.
rybosworld wrote 1 hour 19 min ago:
Looking at this from a software dev perspective:
- The moment AI is actually good enough to replace us, it will also be
incredibly easy to create new software/apps/whatever. There could/would
be a billion solo dev SAAS companies eating the lunch of every
traditional tech org.
- People (Executives) seem to underestimate just how much of the work
is iterating and refining a product over a long time. Getting an LLM
good enough to complete a Jira task is missing the point.
- IMO LLM's are also completely draining the motivation of workers. A
lot of software devs are intrinsically motivated by solving the
problem. If your role is being watered down to "prompt the chat bot and
baby sit what comes out", the motivation disappears. This also
absolutely destroys any of the creativity/discovery that comes out of
solving the task hands-on.
resolutefunctor wrote 55 min ago:
Your perspective on your last point is interesting. I actually feel
the opposite, its become a motivator for me.
I used to love coding, and did it a ton. Then it became less and less
part of my job, and I started hating coding. It was so frustrating
when I knew exactly what needed to be done in the code, but had to
spend the time doing low value stuff like typing syntax, tracing
through the code to find the right file to edit, etc when I'm already
strapped for time.
LLMs and agentic coding tools have allowed me to not spend time on
the low-value tasks of typing, but instead on the high-value tasks of
solving problems like you mentioned. Just interesting the different
perspectives we have.
rybosworld wrote 23 min ago:
That's a fair point and I actually agree with you. A large part of
writing code is doing something menial as you said.
I think both of the viewpoints are valid depending on where you're
at in your career.
We can imagine a junior developer who isn't quite bored with those
low-value tasks just yet.
As you grow more senior/experienced, the novel problems become
harder to find - and those are the one's you want to work on. AI
can certainly help you cut through the chaff so you have more time
to focus on those.
But trends are trends and AI is increasingly getting better at
solving the novel/interesting problems that I think you're
referring to.
Everyone's different and I know there are folks who are excited to
not have to write a single line of code. I'd wager that's not
actually most engineers/developers though.
People still garden by hand because it's innately satisfying.
alberth wrote 1 hour 21 min ago:
McKinsey has pitched my company on projects where their compensation is
entirely outcome-based â for example, if a project generates $20
million in incremental revenue, they would earn 10% of that amount.
I have to admit, the results they demonstrated â which we validated
using our own data â were impressive.
The challenge, however, is that outcome-based contracts are hard for
companies to manage, since they still need to plan and budget for
potential costs upfront.
So while even when you have measurable benefits - it's still not so
easy either.
EDIT:
To clarify the issue â companies are used to budgeting for
initiatives with fixed costs. But in an outcome-based contract, the
cost is variable.
As a result, finance teams struggle to plan or allocate budgets because
the final amount could range widely â for example, $200K, $2M, or
even $20M â depending on the results achieved.
Additionally, you almost then need a partial FTE just to manage these
contracts to ensure you don't overpay because the results are wrongly
measured, etc.
dahcryn wrote 16 min ago:
that's usually in areas where they are very certain.
I'd be surprised if they'd do that for GenAI projects, maybe only for
really good clients that pay them 50mln+ a year anyway
athrowaway3z wrote 48 min ago:
Well, that's fucking scary. I'd be digging deep if I was on the
board.
Either
- the execs are leaving a laughably easy 20m on the table McKinsey
knew they'd make (how did they know, and why didn't we)
- they're dealing with insider information - especially dangerous if
McKinsey is changing dependencies around.
- they're doing some creative accounting
halper wrote 55 min ago:
How is that hard? They put 90% of their estimated revenue as net
revenue (post-McK tax) in the budget? Seems about as hard as the
underlying problem, which is guessing ("forecasting") the revenue.
caminante wrote 1 hour 2 min ago:
What's upfront about a backloaded earnout?
You model it as a fixed %, variable cost and run revenue
sensitivities. It either meets your investment criteria or doesn't.
mschild wrote 55 min ago:
I'd imagine the opportunity cost and man power. Even though
McKinsey should do the work they will need access to people and
information to accomplish it.
caminante wrote 28 min ago:
Parent said McK's fee is 100% contingent.
If the company doesn't have the resources available to execute
something they've validated, then that's a funding issue that can
be solved.
Either way, McK's structure doesn't make it "hard for a company
to manage." The investment committee approves or rejects.
jstummbillig wrote 1 hour 29 min ago:
> Many software firms trumpet potential use cases for AI, but only 30
percent have published quantifiable return on investment from real
customer deployments.
"Only" 30%. Interesting framing.
rsynnott wrote 35 min ago:
This means that only 30% are even _claiming_ to have shown anything
quantifiable. Given that such claims tend to be essentially puffery,
the _real_ rate is presumably far lower.
walkabout wrote 1 hour 13 min ago:
This kind of "data driven" corporate stuff is, IME, so bullshitty and
hand-wavy that I'd assume if only 30% are able to claim to have found
quantifiable ROI (most of them with laughably bad methodology a
slightly-clever 10th grader who half paid attention in their science
and/or stats classes could spot) it means that only 5% or fewer
actually found ROI.
rubzah wrote 1 hour 30 min ago:
Dot-bomb 2.0.
croes wrote 1 hour 31 min ago:
Quite ironic that that comes from McKinsey because their service also
rarely has a measurable benefit
walkabout wrote 1 hour 21 min ago:
Our ability to measure management productivity in general is
basically nonexistent. It's an area of academic study and AFAIK the
state-of-the-art remains not much better than [shrug emoji].
Remember that when they're wrecking your productivity by trying to
twist your job into something they can measure in a spreadsheet.
fuzzfactor wrote 1 hour 32 min ago:
>Consultant says software vendors risk hiking prices without cutting
costs or boosting productivity
From what I know of the firm, it looks like clients have come to the
right place if they want a consultant with great experience at hiking
prices without cutting costs or boosting productivity.
add-sub-mul-div wrote 1 hour 33 min ago:
It has to be tough for them. They can't not be in on the grift, it's
too big and they're too big. But the grift doesn't really benefit them.
walkabout wrote 1 hour 18 min ago:
They're probably salty that the only jobs of theirs they can figure
out how to automate away with AI are the
too-cheap-to-bother-automating Indian workers who author their
PowerPoint decks.
jncfhnb wrote 56 min ago:
the people in India donât author the slides. They just make them
look nice. We have some AI for it.
hansmayer wrote 1 hour 38 min ago:
Did the report from Deloitte come in yet ? :)
oytis wrote 1 hour 39 min ago:
Next they should start wondering why to sell AI apps with no measurable
benefits
jncfhnb wrote 1 hour 0 min ago:
Because you want to sell what people want to buy
oytis wrote 9 min ago:
If people wanted to buy it, then "how" wouldn't be a difficulty
joelthelion wrote 1 hour 21 min ago:
That one is easy to answer from their perspective :)
richardw wrote 1 hour 47 min ago:
Suggest posting the original:
URI [1]: https://www.mckinsey.com/industries/technology-media-and-telec...
jmuguy wrote 1 hour 47 min ago:
I hadn't ever tried Notion before but I sort of vaguely understood it
was a nice way to make some documentation and wiki type content. I had
a need for something like a table that I could filter that I would
normally just do in Google Sheets. So I go check out Notion and their
entire site is focused on AI. Look at what this agent can do, or that.
I signed up and the entire signup flow is also focused on AI. Finally
I was able to locate what I thought was their core offering - the wikis
etc. And ended up pretty impressed with the features they have for all
of that.
Now maybe Notion customers love all these AI features but it was super
weird to see that stuff so prominently given my understanding of what
the company was all about.
ozgrakkurt wrote 37 min ago:
Would strongly recommend avoiding notion. They have super scummy
practices for billing, removing users from company account etc.
throwaway0123_5 wrote 42 min ago:
I'm a heavy Notion user and haven't once used the AI features. I use
AI on a near-daily basis outside Notion, but it just isn't something
I need from Notion. On the other hand at least it isn't that
intrusive in Notion unlike in some other apps.
walkabout wrote 1 hour 23 min ago:
Approximately 95% of my experience using "AI" so far is as something
I accidentally activate then waste a few seconds figuring out how to
make it stop. What little I've seen of other people's experiences
with it on e.g. screen sharing calls mirrors my own. I saw someone
the other day wrestling with Microsoft's AI stuff while editing a
document and it was comically similar to Clippy trying to help but
just fucking things up, except kinda worse because it was a lot less
polite about it.
(And I develop "AI" tools at my day job right now...)
tveita wrote 1 hour 24 min ago:
It's for investors AFAICT. When Masayoshi Son opens your home page it
better say 'AI' in big bold letters.
Is your product a search engine? It's AI now. [1][2]
Is it a cache? Actually, it's AI. [3] A load balancer? Believe it or
not, AI. [4] [1] [2] [3] [4]
URI [1]: https://www.elastic.co/
URI [2]: https://vespa.ai/
URI [3]: https://redis.io/
URI [4]: https://www.f5.com/
rkachowski wrote 1 hour 2 min ago:
whoa I'm out of the loop, what the fuck happened to redis?
afavour wrote 47 min ago:
Venture capital
an0malous wrote 1 hour 25 min ago:
The startup I work at is doing the same strategy pivot, weâre
integrating AI into every feature of the platform. Every textbox or
input field has the option to generate the value from AI. Feature
that no one used when it was a simple form with a button can now be
done through our chatbot. We have two key product metrics for the
entire company and one of them is how many AI tokens our users are
generating.
Aperocky wrote 8 min ago:
AI tokens that you pay for?
liveoneggs wrote 46 min ago:
My job is talking like this to but I don't understand why we need
to keep any of the textboxes at all if the bot is populating
everything.
mountainriver wrote 1 hour 35 min ago:
You kind of have to be or a competitor will come out being AI first
and may get a bunch of funding
wintermutestwin wrote 1 hour 38 min ago:
Notion customer here and their AI crap keeps interrupting my
workflow. Pretty stupid move on their part because they have
motivated me to ditch the subscription.
geerlingguy wrote 1 hour 40 min ago:
They used to be like a really easy to use collaborative wiki. And I
used it for a couple distributed projects and loved that aspect.
But I'm guessing their growth was linear, and hard fought, after
initial success over tools like Atlassian's which are annoying and
expensive.
So to get back to hypergrowth, they had to stuff AI in every nook and
cranny.
pydry wrote 1 hour 29 min ago:
the sad part is that it wasnt entirely nonsensical to use AI to
improve notion's use as a knowledge base but the way they actually
used it was in the most hamfisted ways possible.
inquirerGeneral wrote 1 hour 45 min ago:
Just read a single interview by the CEO etc, they are all in on AI
richardw wrote 1 hour 50 min ago:
First AI came for the artists
And I did not speak out
Because I was not an artist
jncfhnb wrote 1 hour 3 min ago:
Kind of the opposite of the articleâs sentiment
bluefirebrand wrote 1 hour 23 min ago:
Speak for yourself. I've been shouting against AI from minute 1, in
defense of artists and anyone else
It doesn't matter. People are convinced it's a miracle technology, so
I'm just a backwards luddite resisting progress
mojuba wrote 1 hour 52 min ago:
AI in its present form is probably the strangest and the most
paradoxical tech ever invented.
These things are clearly useful once you know where they excel and
where they will likely complicate things for you. And even then,
there's a lot of trial and error involved and that's due to the
non-deterministic nature of these systems.
On the one hand it's impressive that I can spawn a task in Claude's app
"what are my options for a flight from X to Y [+ a bunch of additional
requirements]" while doing groceries, then receive a pretty good
answer.
Isn't it magic? (if you forget about the necessity of adding "keep it
short" all the time). Pretty much a personal assistant without the
ability of performing actions on my behalf, like booking tickets - a
bit too early for that.
Then there's coding. My Copilot has helped me dive into a gigantic
pre-existing project in an unfamiliar programming language pretty fast
and yet I have to correct and babysit it all the time by intuition. Did
it save me time? Probably, but I'm not 100% sure!
The paradoxicality is in that there's probably no going back from AI
where it already kind of works for us individually or at org levels,
but most of us don't seem to be fully satisfied with it.
The article here pretty much confirms the paradox of AI: yes, orgs
implement it, can't go back from it and yet can't reduce the headcount
either.
My prediction at the moment is that AI is indeed a bubble but we will
probably go through a series of micro-bursts instead of one gigantic
burst. AI is here to stay almost like a drug that we will be willing to
pay for without seeing clear quantifiable benefits.
johndhi wrote 1 hour 27 min ago:
I feel like one benefit of humans is you can find someone you can
truly trust under almost all circumstances and delegate to them.
With AI you have a thing you can't quite trust under any circumstance
even if it's pretty good at everything.
mojuba wrote 44 min ago:
A hammer doesn't always work as desired, it depends on your skills
plus some random failures. When it works however, you can see the
result and are satisfied with it - congratulations, you saved some
time by not using a rock for the same task.
johndhi wrote 18 min ago:
I can trust a hammer will be a hammer, though.
deepsquirrelnet wrote 1 hour 28 min ago:
Itâs a result of the lack of rigor in how itâs being used.
Machine learning has been useful for years despite less than 100%
accuracy, and the way you trust it is through measurement. Most
people using or developing with AI today have punted on that because
itâs hard or time consuming. Even people who hold titles of machine
learning engineer seem to have forgotten.
We will eventually reach a point where people are teaching each other
how to perform evaluation. And then weâll probably realize that it
was being avoided because itâs expense to even get to the point
where you can take a measurement and perhaps you didnât want to
know the answer.
Printerisreal wrote 1 hour 54 min ago:
Truth is out people. They are confessing it now.
JCM9 wrote 1 hour 57 min ago:
What most companies and CEOs fail to grasp is that with all the talk of
headcount cuts from AI customers are expecting that AI will LOWER
pricing and costs, not raise it. Challenge is that the cost cutting
story is mostly vaporware (as many other studies have shown) so CEOs
are in a tough spot. They canât both boast to shareholders at how
much cost savings they got from rolling out AI and then charge
customers more.
All this is pretty textbook setup for how this bubble finally implodes
as companies fail to deliver on their AI investments and come under
fire from shareholders for spending a ton with little return to show
for it.
gorbachev wrote 1 hour 50 min ago:
I can't wait until the AI vendors start charging according to the
true costs of their tools (+ profit margin). Let's see what the cost
savings are then.
Additionally once the AI vendors have locked these companies to their
ecosystem, the enshittification will start and the companies who
reduced their headcount to bare minimum will start to see why that
was a really, really bad idea.
givemeethekeys wrote 2 hours 2 min ago:
> Software vendors keen to monetize AI should tread cautiously, since
they risk inflating costs for their customers without delivering any
promised benefits such as reducing employee head count.
That's easy. Reduce the headcount first, and then let the remaining
team of poor and desperate, I mean, elite engineers and support teams
AI for /s.
When will boards replace executive leadership with AI? If Return to
Office taught us anything, it was that we already need a couple, and
the rest of them copy and paste. Well, AI can do that! Also /s, but
maybe just 50%.
StableAlkyne wrote 2 hours 4 min ago:
> while quoting an HR executive at a Fortune 100 company griping: "All
of these copilots are supposed to make work more efficient with fewer
people, but my business leaders are also saying they can't reduce head
count yet."
I'm surprised McKinsey convinced someone to say the quiet part out loud
dahcryn wrote 21 min ago:
both make a lot of sense, but the biggest mistake they make is to see
people as capacity, or as a counter.
Each human can be a bit more productive, I fully believe 10-15% is
possible with today's tools if we do it right. But each human has it
unique set of experience and knowledge. If I do my job a bit faster,
and you do your job a bit faster. But if we are a team of 10, and we
do all our job 10% faster, doesn't mean you can let one of us go. It
just means, we all do our job 10% faster, which we probably waste by
drinking more coffee or taking longer lunch breaks
loudmax wrote 59 min ago:
Organizations that successfully adapt are those that use new
technology to empower their existing workers to become more
productive. Organizations looking to replace humans with robots are
run by idiots and they will fail.
jf22 wrote 1 hour 0 min ago:
This part was never quiet...
The quiet part out loud phrase is overused.
treis wrote 1 hour 5 min ago:
I think they can. IME LLMs have me working somewhat less and doing
somewhat more. It's not a tidal wave but I'm stuck a little bit less
on bugs and some things like regex or sql I'm much faster. It's
something like 5-10% more productive. That level of slack is easy to
take up by doing more but theoretically it means being able to lose 1
out of every 10-20 devs.
iamleppert wrote 1 hour 50 min ago:
How does it make sense to trade one group of labor (human) who are
generally loosely connected, having little collective power for
another (AI)? What you're really doing isn't making work more
"efficient", you're just outsourcing work to another party -- one who
you have very little control over. A party that is very well
capitalized, who is probably interested in taking more and more of
your margin once they figure out how your business works (and that's
going to be really easy because you help them train AI models to do
your business).
newsclues wrote 1 hour 45 min ago:
Itâs the same as robots in a factory.
rswail wrote 1 hour 16 min ago:
Except that the people that make robots for factories, aren't
interested in making whatever that factory is making.
iamleppert wrote 45 min ago:
That's not required. All that is required is becoming a sole
source of labor, or a source that is the only realistic choice
economically.
If you ask me, that's the real long game on AI. That is exactly
why all these billionaires keep pouring money in. They know
it's the only way to continue growth is to start taking over
large sections of the economy.
_fat_santa wrote 1 hour 53 min ago:
I find it all quite strange:
- AI companies of course will try and sell you that you can reduce
headcount with AI
- CEO's will parrot this talking point without ever talking a closer
look.
- Everyone lower down on the org chart minus the engineers are
wondering why the change hasn't started yet.
- Meanwhile engineers are ripping their hair out cause they know that
AI in it's current state will likely not replace any workers.
Pretty soon we will have articles like "That time that CEO's thought
that AI could replace workers".
rsynnott wrote 37 min ago:
> Pretty soon we will have articles like "That time that CEO's
thought that AI could replace workers".
Yup, it's just the latest management fad. Remember Six Sigma? Or
Agile (in its full-blown cultish form; some aspects can be mildly
useful)? Or matrix management? Business leaders, as a class, seem
almost uniquely susceptible to fads. There is always _some_ magic
which is going to radically increase productivity, if everyone just
believes hard enough.
parliament32 wrote 1 hour 17 min ago:
> ripping their hair out
I mean, nah, we've seen enough to these cycles to know exactly how
this will end.. with a sigh and a whimper and the Next Big Thing
taking the spotlight. After all, where are all the articles about
how "that time that CEOs thought blockchain could replace
databases" etc?
itake wrote 1 hour 38 min ago:
The incentive structure for managers (and literally everyone up the
chain) is to maximize headcount. More people you managed, the more
power you have within the organization.
No one wants to say on their resume, "I manage 5 people, but trust
me, with AI, its like managing 20 people!"
Managers also don't pay people's salaries. The Tech Tools budget is
a different budget than People salaries.
Also keep in mind, for any problem space, there is an unlimited
number of things to do. 20 people working 20% more efficiently wont
reach infinity any faster than 10 people.
deaux wrote 1 hour 18 min ago:
> The incentive structure for managers (and literally everyone up
the chain) is to maximize headcount. More people you managed, the
more power you have within the organization
Ding ding ding!
AI can absolutely reduce headcount. It already could 2 years ago,
when we were just getting started. At the time I worked at a
company that did just that, succesfully automating away thousands
of jobs which couldn't pre-LLMs. The reason it ""worked"" was
because it was outsourced headcount, so there was very limited
political incentive to keep them if they were replaceable.
The bigger and older the company, the more ossified the
structures are that have a want to keep headcount equal, and
ideally grow it. This is by far the biggest cause of all these
"failed" AI projects. It's super obvious when you start noticing
that for jobs that were being outsourced, or done by
temp/contracted workers, those are much more rapidly being
replaced. As well as the fact that tech startups are hiring much
less than before. Not talking about YC-and-co startups here,
those are global exceptions indeed affected a lot by ZIRP and
what not. I'm talking about the 99.9% of startups that don't get
big VC funds.
A lot of the narrative on HN that it isn't happening and AI is
all a scam is IMO out of reasonable fear.
If you're still not convinced, think about it this way. Before
LLMs were a thing, if I asked you what the success rate of
software projects at non-tech companies was, what would you have
said? 90% failure rate? To my knowledge, the numbers are indeed
close. And what's the biggest reason? Almost never "this problem
cannot be technically solved". You'd probably name other, more
common reasons.
Why would this be any different for AI? Why would those same
reasons suddenly disappear? They don't. All the politics, all the
enterprise salesmen, the lack of understanding of actual needs,
the personal KPIs to hit - they're all still there. And the
politics are even worse than with trad. enterprise software now
that the premise of headcount reduction looms larger than ever.
sofixa wrote 34 min ago:
> The bigger and older the company, the more ossified the
structures are that have a want to keep headcount equal, and
ideally grow it.
I don't know, most of the companies doing regular layoffs
wheneveer they can get away with it are pretty big and old. Be
it in tech - IBM/Meta/Google/Microsoft, or in physical things -
car manufacturers, shipyards, etc.
ckcheng wrote 1 hour 0 min ago:
Yes, and itâs instructive to see how automation has reduced
head count in oil and gas majors. The reduction comes when
thereâs a shock financially or economically and layoffs are
needed for survival. Until then, head count will be stable.
Trucks in the oil sands can already operate autonomously in
controlled mining sites, but wide adoption is happening slowly,
waiting for driver turnover and equipment replacement cycles.
2OEH8eoCRo0 wrote 1 hour 18 min ago:
> for any problem space, there is an unlimited number of things
to do.
That's what I've wondered. We don't just run out of work,
products, features, etc. We can just build more but so can the
competition right?
skeeter2020 wrote 1 hour 20 min ago:
Maybe 40 years ago or in some cultures, but I've always focused
on $ / person. If we have a smaller team that can generate $2M in
ARR per developer that's far superior to $200K. The problem is
once you have 20 people doing the job nobody thinks it's possible
to do it with 10. You're right that "there is an unlimited number
of things to do" and there's really obvious things that must be
done and must not be done, but the majority IME are should or
could be done, and in every org I've experienced it's a challenge
to constrain the # of parallel initiatives, which is the
necessary first step to reducing active headcount.
paulsutter wrote 1 hour 16 min ago:
Exactly, itâs much easier with a new organization.
In my previous company, we would speculate about where to use
AI and we were never sure.
In the new company we use AI for everything and produce more
with substantially fewer people
ToucanLoucan wrote 1 hour 1 min ago:
Does anyone want what you're producing though?
I don't mean to be dismissive and crappy right out of the
gate with that question, I'm merely drawing on my experience
with AI and the broader trends I see emerging: AI is
leveraged when you need knowledge products for the sake of
having products, not when they're particularly for something.
I've noticed a very strange phenomenon where middle managers
will generate long, meandering report emails to communicate
what is, frankly, not complicated or terribly deep
information, and send them to other people, who then
paradoxically use AI to summarize those emails, likely into
something quite similar to what was prompted to be generated
in the first place.
I've also noticed it being leveraged heavily in spaces where
a product existing, like a news release, article, social
media post, etc. is in itself the point, and the quality of
it is a highly secondary notion.
This has led me to conclude that AI is best leveraged in such
cases where nobody including the creator of a given thing
really... cares much what the thing is, if it's good, or does
it's job well? It exists because it should exist and it's
existence performs the function far more than anything to do
with the actual thing that exists.
And in my organization at least, our "cultural opinion" on
such things would be... well if nobody cares what it says,
and nobody is actually reading it... then why the hell are we
generating it and then summarizing it? Just skip the whole
damn thing and send a short, list email of what needs
communicating and be done.
delusional wrote 18 min ago:
> Does anyone want what you're producing though?
He's either lying or hard-selling. The company in his
profile "neofactory.ai" says they "will build our first
production line in Dallas, TX in Q3." well, we just entered
Q4, so not that. Despite that it has no mentions online and
the website is just a "contact us" form.
silverquiet wrote 52 min ago:
The anthropologist David Graeber wrote a book called
"Bullshit Jobs" that explored the subject. It shouldn't be
surprising that a prodigious bullshit generator could find
a use in those roles.
ipython wrote 1 hour 8 min ago:
Do you have any examples of the types of tasks youâve found
the most success with using ai ?
btbuildem wrote 1 hour 39 min ago:
I am still of the conviction that "reducing employee head count"
with AI should start at the top of the org chart. The current
iterations of AI already talk like the C-suites, and deliver
approximately same value. It would provide additional benefits, in
that AIs refuse to do unethical things and generally reason
acceptably well. The cost cutting would be immense!
I am not kidding. In any large corps, the decision makers refuse to
take any risks, show no creativity, move as a flock with other
orgs, and stay middle-of-the-road, boring, beige khaki. The current
AIs are perfect for this.
visarga wrote 3 min ago:
> I am still of the conviction that "reducing employee head
count" with AI should start at the top of the org chart. The
current iterations of AI already talk like the C-suites
That is exactly what it can't do. We need someone to hold liable
in key decisions.
mbesto wrote 34 min ago:
> In any large corps, the decision makers refuse to take any
risks, show no creativity, move as a flock with other orgs, and
stay middle-of-the-road, boring, beige khaki.
It's hard to take this sentiment seriously from a source that
doesn't have direct experience with the c-suite. The average
person only gets to see the "public relations" view of the
c-suite (mostly the CEO) so I can certainly see why a "LLM based
mouthpiece" might be better.
The c-suite is involved in thousands of decisions that 90% of the
rest of the world is not privy to.
FWIW - As a consumer, I'm highly critical of the robotic-like
external personas the c-suite take on so I can appreciate the
sentiment, but it's simply not rooted in any real experience.
skeeter2020 wrote 1 hour 17 min ago:
It's not the top IME, but the big fat middle of the org chart
(company age seems to mirror physical age maybe?) where middle to
senior managers can hide out, deliver little demonstratable value
and ride with the tides. Some of these people are far better at
surfing the waves than they are at performing the tasks of their
job title, and they will outlast you, both your political skills
and your tolerance for BS.
A4ET8a8uTh0_v2 wrote 1 hour 22 min ago:
One could argue that they deliver a better value than meat
leaders.
jordanb wrote 1 hour 33 min ago:
"Wow this AI both writes and reads email? That's about 90 percent
of my job and -- I presume -- 90 percent of what happens around
here!"
imglorp wrote 1 hour 25 min ago:
AND it can sit meetings all day and not forget any decisions;
that's the other 90 percent of a manager's day.
rwmj wrote 1 hour 14 min ago:
And just like senior managers, every time you ask it a
question, it starts a new context.
walkabout wrote 59 min ago:
Can it turn simple yes-or-no questions, or "hey who's the
person I need to ask about X?" into scheduled phone calls
that inexplicably invite two or three other people as an
excuse to fill up its calendar so it looks very busy?
johndhi wrote 1 hour 37 min ago:
Not a crazy idea. Sergey at Google said it's best at replacing
managers fwiw
newsclues wrote 1 hour 46 min ago:
AI is most capable of replacing the humans who have the power to
decide or influence the choice to replace humans with AI.
But managers will not obsolete themselves.
So right now AI should be used to monitor and analyze the workforce
and find the efficiency that can be achieved with AI.
jordanb wrote 2 hours 2 min ago:
Also strange that this executive is worried about how the business
continues to function after the people are gone. That's not the
McKinsey Way!
bgwalter wrote 2 hours 5 min ago:
That is good news for once. If McKinsey is on the case, "AI" will soon
fail (after McKinsey has raked in consultancy fees).
jordanb wrote 2 hours 5 min ago:
Maybe they could send them to Harvard Business School?
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