If you read the footnote, they follow up to say they've rejected 100% of the AI projects brought to them.
Go to their home page and one of their consulting selling points is recovering struggling projects.
One of their front-page selling points is that they use "ancient techniques" from books written prior to the year 2000, because presumably everything newer than that is bad?
> For non-executive management who might be struggling to deliver things that feel beyond their control, we have ancient techniques (see: books written between 1986 and 1999) to turn your team into the envy of the organisation, and we can drop in directly to get your team the resources it needs to save a struggling project.
This is entirely a selection bias issue that they've created for themselves: Advertise a consulting service for saving failing projects to companies that don't have internal expertise to handle it, then write blog posts that 100% of the projects you see are failing. Also refuse to help them, to guarantee they can't be converted to successful projects to keep the success number at 0%.
> One of their front-page selling points is that they use "ancient techniques" from books written prior to the year 2000, because presumably everything newer than that is bad?
I get what you are saying here.
At the same time, was reading Deming's last book [0] and there is a great line that I have never seen in any recent business books:
"The organizational chart is usually a pyramid. The main benefit of this style of chart is to clarify who reports to whom. Notably absent from this chart: the customer."
I've also worked at firms filled with very smart people who had no concept (or were not incentivized) to think about the Theory of Constraints, Total Quality Management or that the firm is supposed to work as a team and not a collection of fiefdoms.
What I'm saying is: just because a book was written before 2000 doesn't make it irrelevant.
There’s some selection bias involved especially based on their marking, but you’re misreading what they are saying.
> even within projects that we have observed in passing while doing totally unrelated work.
The kind of companies with failing projects seem to be very bad at using AI. That’s different from the normal mix of success and failures at most large companies.
Companies with projects that are doing well don't try to hire consultants who specialized in saving failing projects.
No company with a good AI strategy is going to go to the Hermit Tech website where text written in Ye Olde Font explains that they'll use ancient techniques from the 80s and 90s to make your software work and thinks, "These are the right people for our AI job!"
These people are trying to carve out a niche for themselves as being anti-modern, anti-AI, and being contrarian consultants that you can bring in when you want some external consultants to agree with you in a very specific way.
I think you are right on target. I’ve seen this pattern:
Company does x. X sucks, and is largely derided as being a bad idea, but it’s important-employee-bobs baby. No one wants to be the guy that tells bob that x is killing the company in some small or large way, because bob can get them fired or is protected by someone who can, so you hire consultants xyz who specialize in “transforming productivity through x management” and they come in and “transform” x into something less lovecraftian, or just explain why it’s bad in a way that makes bob look like a genius.
> Companies with projects that are doing well don't try to hire consultants who specialized in saving failing projects.
Large companies where every project is going well are rare.
I agree companies with good AI strategies are unlikely to use these people, but excluding failures is just as much a bias as excluding winners. AI lets you shoot your sold in the foot even faster shouldn’t be surprising, but it’s still something to consider.
Tale as old as time. Revolution has been merchandised. The action and the reaction, they all have suppliers, which often turn out to be the same entities supplying to both sides.
Perhaps I should have specified Anti-AI. Its just the thing that upsets me the most about your everyday liberal professional, how much they hate AI just because Trump is pro AI
I think "your everyday liberal professional" is more likely to be anti-AI because it is being advertised as a direct threat to their livelihoods, rather than for any more abstract reason. The latter includes both political allegiance stuff and the reasons those professionals would likely cite, like its energy requirements or the economic damage if the bubble bursts.
Whether or not you think it likely that this threat will materialize is beside the point. Workers never like it when someone is advertising that they will put you out of work.
No, because most people in say, California, which is very pro-tech, are perfectly fine with AI. But people in the Northeast are angry at it. It’s entirely cultural.
That observation[0] isn't particularly useful for arguing that it's a political allegiance thing. A lower fraction of voters in the pro-tech part of California (SFO, roughly) voted for Trump than, say, in NYC. Your observation cuts against the argument that political allegiance is the main driver, not in favor of it.
[0]- Assuming it's true, which in my experience it isn't especially, but this isn't the best argument.
You have no idea, you must not know that they are afraid of Waymos out in the northeast, they think they are evil or something, I'm not even joking.
Anyway, I didn't say it was a political thing I said it was a cultural thing. The average liberal is not someone who thinks primarily in political terms, they are just going about their lives unreflectively and they genuinely believe in the moral weight of their feelings, which are their primary guide. Now, I'm not saying that human life is not generally composed of its daily concerns, which tend to rule us, but for the average liberal politics is no different from acting on basic urges; like a mouse chasing the next piece of cheese in a maze, they cannot see that no turn will ever lead to their escape; that so long as they continue to chase the very next thing, they are trapped in constraints that have been laid out for them in advance. Like the conservatives of the 80s, there is always one more moral panic, one more thing that you're supposed to be upset about, one more cause to fight for. There is no stopping to think why this is something that is supposed to upset me, why is this something that needs to change. They are not able to go just one step beyond common opinion and wonder why there are so few avenues for them in the first place, they are not able to question why the maximum content of their decisions is good or evil, just or unjust, left or right. Yes any decision is binary, but one must be able to choose that for themselves, be able to consider the decision to leave the maze, even if they are, in the end, no more powerful than all the other rats, and there might not be any cheese outside of it; and there might be no end to the maze, and even very far from what you thought was the exit lay the bodies of those who attempted to leave before.
But anyway this is what I mean by primarily cultural. Liberals "drink matcha," go to running clubs, obsess over "consent" (they now have a term "weaponized consent," how absurd! that they are just realizing now that consent is always given within certain relations of power...) Whatever politics they have is on the same plane, they are doing it because its something to be done. Someone who thinks primarily in terms of politics, that is, in terms of the social dynamics of power, would never call themselves a liberal.
> Its just the thing that upsets me the most about your everyday liberal professional, how much they hate AI just because Trump is pro AI
That's what I'm refuting here -- that people here dislike AI just to be contrary to Trump. This is implausible.
And trying to lecture a life long New Englander who currently lives within the MBTA zone on what the culture is like in the northeast is maybe not the best look. We aren't afraid of Waymos here; the only people I've met who weren't jealous of them were taxi or Uber drivers. That supports my hypothesis, not yours.
I'm not sure why my experience differs from yours. When I was in the northeast recently I got into heated arguments with people, one person said they "hated Waymo" and refused to elaborate (but also said they used AI everyday for work), another said flat out that technology is evil, so I asked them if poor people should go without electricity. Then they restricted their argument to AI is evil, and that was a more nuanced (if not trite) debate, which they eventually conceded. But not without some gnawing and thrashing!
But I don't think that hating AI or technology or whatever to be contrary to Trump is a genuine political statement, its just reaction. It involves politics in the same way that everything we do involves politics, but it is not "consciously" political in the same way that a baby demanding care from an overworked mother is also not consciously political. Baby wants milk, your average liberal wants to feel self-righteous (they would honestly do better with the milk). Someone can claim anything they want is political, it does not mean they are doing it for genuinely political reasons, they are probably just doing it because they fear the censure of their friends and the dissolution of their social life. Not engaging with something because you are afraid of how it could harm you personally, consciously or no, is not an objective way of making a decision that effects society more broadly. Like, a baby will just die if it doesn't get milk, you won't necessarily die because some of your friends stop talking to you.
If you were in NYC, some of this may be a Boston/NYC difference. NYC is much more anti-Waymo (which I interpret mostly as an extension of being much more anti-car in general). There are also substantially different cultures between the two re: art and finance, which may have reflected on the AI questions.
I don't think you can decouple Trump from himself in this way without a concrete explanation. If some factor causes one to dislike something just because Trump likes it, then that same factor would influence voting. We have numbers for voting. When there are lots of other plausible explanations than Trump, the onus would be on you to demonstrate why more people are taking reverse-psychological cues from Trump in a place where more people also voted for him. Gesturing at "culture" doesn't do that.
I’m not sure I understand your point. Its not the case that more people voted for Trump in a place where more people are taking reverse psychological cues from him, but precisely the opposite case, the more people take reverse cues the less vote for him, which implies their positions are on account of reaction and not because they are genuinely reflecting on their social and political condition, which would elevate them to conscious political actors rather than people following a trend because they are afraid of going against it.
You are simply incorrect about that. More people voted for Trump in NYC (the typical exemplar of "the northeast") than in SFO (the exemplar of the part of California that is more pro-AI than NYC).
I think that absolute numbers in specific cities don't tell the full story. NYC also has far fewer people with college degrees than SFO, which would correlate more strongly with Trump supporters. I think that if you polled those who voted against Trump in NYC now, and asked them about their opinions on AI, you'd find they diverge significantly from those who did vote for him, whereas if you asked the same question to Trump voters and non Trump voters in SFO they would answer pretty much the same. SFO is also in California which does not have the same cultural relationship with technology as NYC or much of the Northeast, although the culture I'm describing stretches basically all over the east coast.
So, you're postulating that there is something of a Simpson's paradox going on in NYC between two largely separate cultures -- that of people with college degrees, and that without? This is theoretically possible, but conveniently not directly testable due to secret ballots. It is however indirectly testable in two different ways -- and the numbers still don't back you up.
2) Middlesex County, Massachusetts (roughly, the north half of greater Boston) is an alternative example to NYC that has a very similar proportion of college degrees compared to SFO (about 1% less). Middlesex County is in the northeast. About 42% of those voters voted for Trump, which is more than New York and more than double SFO. Suffolk County (with Boston proper) has very similar numbers to NYC for both college education and voting for Trump. This can't be explained as a cultural difference between NYC and Boston because the Suffolk ratios are so similar. It can't be explained as an educational difference between SFO and Boston because the Middlesex educational numbers are so similar but there are proportionally more Trump voters than NYC. It can't be explained as a cultural difference between Suffolk and Middlesex because first, they are direct neighbors sharing a public transit system, and second, Middlesex is considerably more traditionally leftist than Suffolk (leaning on that cultural difference would undermine your original argument).
it's not surprising as LLM's will generally fail you when you yourself don't know what you want. it's surprising how many people and organizations just blunder around scribbling code without clear goals in mind - for such people LLM's are a net negative as they will just end up with even more scribbles and no hope to make sense of it all.
> Supposedly 70% of software projects failed even before AI.
Given the way LLMs are marketed, we should expect a vastly more favorable project success rate, not simply a close parity, and definitely not a decreased rate.
Even if we consider that the number of attempts will rise if development becomes faster, we're told to expect a greater number of projects should also succeed because they're easier. They're supposed to justify the higher costs.
> Given the way LLMs are marketed, we should expect a vastly more favorable project success rate, not simply a close parity, and definitely not a decreased rate.
> Even if we consider that the number of attempts will rise if development becomes faster, we're told to expect a greater number of projects should also succeed because they're easier.
I'm not sure I follow why you would think this. Prior to AI was the reason most projects failed because generating the code was too slow or too labor intensive? That would be surprising to me if it was true.
Generating code is not, and never was, a bottleneck to projects. Understanding the problem, designing a solution, organizing resources, testing, and customer buy-in and moving targets have always represented the real issues.
Now, with LLMs, we're supposed to be able to paper over some or all of these problems.
They're supposed to be able to understand and intuitively fill the assumptions present in vague requirements, then produce working applications. They're supposed to shrink the timelines from years and months to weeks and days. They're supposed to replace human expertise with a reliable service.
Why else would I hire an LLM service over a team of humans?
> They're supposed to be able to understand and intuitively fill the assumptions present in vague requirements, then produce working applications. They're supposed to shrink the timelines from years and months to weeks and days. They're supposed to replace human expertise with a reliable service.
But none of those sound like things that would change how likely any given project is to succeed. Shrinking timelines from years and months to weeks and days just means that you can fail faster and try again sooner (hopefully with lest costs), but nothing about that implies your rate of success is going to get better.
I think the point is that using an LLM is not really going to shrink project timelines by that degree.
Most large software projects I've worked on in a professional environment, "writing the code" was one of the fastest and smallest parts of the project. Maybe 10% of the overall calendar time of any given project was "designing and typing in software." The bulk of time spent tends to be working with customers, researching and refining requirements, reviewing the requirements with execs and leads to get their buy-in and support for staffing the project, performing various non-engineering reviews like legal and privacy, aligning timeframes among multiple contributing teams, seeking approval from Director X to move on to the next project phase, waiting for Key Team Member Y to get back from vacation, conducting QA and field testing, soaking the software through various rollout stages like internal, dogfood, internal staging, external beta, and then incremental percentages in prod, while watching and waiting for any regressions or failures. On a project that takes 6 months from idea to 100% in-production, writing the code might take a few weeks of that.
So why are we so focused on a tool that speeds up the smallest part of this process?
The article is a fun read. There's a certain amount of hyperbole and subtext which may perhaps be unfamiliar to some readers.
But the point is fair. Where are the huge AI wins? Why haven't Anthropic and OpenAI produced a regular series of case studies where Company X did Fun AI Thing and incredible success ensued?
Why do these conversations always end up mentioning chat bots?
Why do c-suites seem to be full of people chasing trends instead of leading?
Does anyone remember what customers are, or are corporations aiming for Platonic abstraction, where business activities become ends in themselves, with no useful output?
Yeah, and how and what someone jokes about will often tell you something about what and how they think. I don't think they'll literally just ignore everything after that point, but I do expect that they are going to tend towards an old-school approach.
To be completely fair, most software projects fail, AI or not, and we've known that since before the 2000s. I'm not saying everything post-2000s is bad, but just that the core is unchanged: most software projects fail, you should expect failure, and there is no magic silver-bullet process to either anticipate or prevent failure. Agile (big A) is certainly not that process.
I mean, that line regarding ancient techniques is very obviously written as satirical. I read it as „we are serious professionals, not young trend following folks“
The prominent "Business Owners" link on this company's website is broken. "Not Found".
Perhaps this will get downvoted but I personally take with a grain of salt anything written/stated by a company that can't even get the most basic functions (like running a simple website) correct.
And the even bigger irony here is that the author has a ranty blog post in which he claims he saved his employer $500,000 by clicking a button. "[It] is fucking wild that an inefficiency that took me five minutes to solve in a GUI configuration panel was allowed to persist," he wrote.
I don't think this is surprising at all. I'm pretty sure I've saved my employers similar amounts in the past, because what happens is something gets configured months or years ago, the dev leaves, everyone forgets and assumes things are how they are.
I've had to delete some really silly code that would slow things down or just force waits as a result of either dealing with legacy APIs or some other arcane reason. Not without testing or making sure it wasn't there for a reason mind you, but these inefficiencies can sometimes be hidden big problems.
The point isn't that this stuff happens. It's that a person who is trying to sell consulting services with ranty "this industry is a sham" and "it's a disgrace that it was even possible" blog posts has a website with just 5 major navigation links...and one of them is 404.
Go to their home page and one of their consulting selling points is recovering struggling projects.
One of their front-page selling points is that they use "ancient techniques" from books written prior to the year 2000, because presumably everything newer than that is bad?
> For non-executive management who might be struggling to deliver things that feel beyond their control, we have ancient techniques (see: books written between 1986 and 1999) to turn your team into the envy of the organisation, and we can drop in directly to get your team the resources it needs to save a struggling project.
This is entirely a selection bias issue that they've created for themselves: Advertise a consulting service for saving failing projects to companies that don't have internal expertise to handle it, then write blog posts that 100% of the projects you see are failing. Also refuse to help them, to guarantee they can't be converted to successful projects to keep the success number at 0%.