It's kind of a mirror image of the global AI marketing hype-factory: Always pump/promote the ways it works well, and ignore/downplay when it works poorly.
It's kind of a mirror image of the global AI marketing hype-factory: Always pump/promote the ways it works well, and ignore/downplay when it works poorly.
Like I use AI tools, I even like using them, but saying "this tool is so good it will cut our dev time by 30%" should be coming from the developers themselves or their direct manager. Otherwise they are just making figures up and forcing them onto their teams.
And, crickets. In practice I haven't seen any efficiencies despite my teams using AI in their work. I am not seeing delivery coming in under estimates, work costs what it always cost, we're not doing more stuff or better stuff, and my margins are the same. The only difference I can see is that I've had to negotiate a crapton of contractual amendments to allow my teams to use AI in their work.
I still think it's only good for demos and getting a prototype up and running which is like 5% of any project. Most technical work in enterprise isn't going from zero to something, it's maintaining something, or extending a big, old thing. AI stinks at that (today). You startup people with clean slates may have a different perspective.
It'd mean that hundreds of people would all be goofing off silently. I'd expect at least overtime bookings to decrease and they haven't - even with our strong incentives to not book o/t.
Have you actually tried that? Because my bet is that if your "prototype" is a anything that is very VERY traditional, e.g. a CMS, online shop, or anything that has examples online, yes it will be quick, but if it's genuinely new, namely something NOT available out there, maybe because it is relying on the latest stack that is not yet well documented, then I bet it will also fail terribly.
Edit: I personally did, namely using LLMs to make XR demos relying on a now relatively popular framework https://aframe.io and basically it fails most of the time by proposing "traditional" HTML/CSS, missing entirely that it's 3D. Anyway, long story short, didn't work for me so curious to know if the "getting a prototype" (a genuine prototype, not a codebase starting from scratch because IMHO that's different) part is validated or just an idea.
Never seen it used for anything novel so I can't refute you.
I would have thought that in a fight between "fooling ourselves with a story" and "metrics go up" that the metrics would win, but it seems to not be the case.
Also, the RTO mandate can serve as a basis/pretext for layoffs and cost consolidation, although CXOs tend not to admit that directly.
The promise of replacing your expensive staff who talk back with cheap malleable AI is just too tempting.
Lionizes the worker for their output. Just the same as quota or target driven systems. It's the same kind of lionization as "employee of the month" schemes, i.e. a sham to encourage people to work harder.
https://en.wikipedia.org/wiki/Stakhanovite_movement
>In 1988, the Soviet newspaper Komsomolskaya Pravda stated that the widely propagandized personal achievements of Stakhanov actually were puffery. The paper insisted that Stakhanov had used a number of helpers on support work, while the output was tallied for him alone.
Bloody hell. That feels like getting into borderline religious territory.
> My management chain has recently mandated the use of AI during day-to-day work, but also went the extra step to mandate that it make us more productive, too.
Now they're on record as pro-AI while the zeitgeist is all about it, but simultaneously also having plausible deniability if the whole AI thing crumbles to ashes: "we only said to use it if it helped productivity!"
Do you see? They cannot be wrong.
Before you make any decision, ask yourself: "Is this good for the company?"
People making the decisions are 5%, they delegate to managers who delegate to their teams and all the way down.
Decision makers (not the guy who thinks corner radius should be 12 instead of 16, obviously) want higher ROI and they see AI working for them for high level stuff.
At low level things are never sane.
Before AI it was offshore. Now it’s offshore with AI.
Prepare for chaos, the machine priests have thrown open the warp gate. May the Emperor have mercy for us.
It seems to me like too many yearly bonuses are tied to AI implementation, due to FOMO amongst C-levels. The hype trickles down to developers afraid that they won't get hired in the new AI economy.
I don't think there's a conspiracy, just a storm front of perverse incentives.
I'm not normally on LinkedIn but recently was and with the AI stuff the "look at me" spam around AI seems like an order of magnitude more absurd than usual.
I suspect a lot of companies that go that route are pushing a marketing effort since they themselves have a stake in AI.
But I'd love to hear from truly customer only businesses, where AI is pure cost, with no upside, unless it truly pays for itself in business impact, and if they too are stuck in some justifying of their added cost loop to make their decision seem a good one no matter what, or if they are being more careful?
That is where the AI come into full use.
In fact, do it in parallel where one chatbot is adding another few pages here, and simultaneously and independently, another is adding different pages somewhere else and concatenate the results together.
Once you get about 25 pages of dense slop, just conclude that AI made writing this report 1000x more efficient.
Everything sounded very mandatory, but a couple of months later nobody was asking about reports anymore.
It is hardly feasible for an organization to budget time for replicating and validating results, form their own conclusions, for any employee form who wishes to question the effectiveness of the tool or the manner of deployment.
Presumably the organization has done that validation with reasonably sized sample of similar roles over significant period of time. It doesn't matter though, it would be also sound reasoning for leadership to take a strategic call even when such tests are not conducted or not applicable.
There are costs and time associated with accurate validation which they are unable / unwilling to wait or even pay for, even if they wish to. The competition is moving faster and not waiting, so deploying now rather than wait and validate is not necessarily even a poor decision.
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Having said that, they can articulate their intent better than "write about how it made you more productive", by adding more description along the lines of "if not then explain all the things you have tried to try and adopt the tool and what and how it did not go well for you/ your role"
Typically well structured organizations with in-house I/O psychologists would add this kind of additional language in the feedback tooling, line managers may not be as well trained to articulate it in informal conversations, which is whole different kind of problem.
My report was entirely unacknowledged along with other reports that had negative findings. The team in charge published a self-report about the success rate and claimed over 90% perfect results.
About a year later, upper management changed to this style of hard requiring LLM usage. To the point of associating LLM api calls from your intellij instance with the git branch you were on and requiring 50% llm usage on a per-pr basis otherwise you would be pip-ed.
This is abusive behavior aimed at generating a positive response the c suite can give to the board.
That said, I don't agree with or advocate the specific rollout methodology your company is using and agree that it feels more abusive and adversarial than helpful. That approach will certainly risk backfiring, even if they aren't wrong about the large-scale usefulness of the tools.
What you're experiencing is perhaps more poor change management than it is a fundamentally bad call about a toolset or technology. They are almost certainly right at scale more than they are wrong; what they're struggling with is how to rapidly re-skill their employee population when it contains many people resistant to change at this scale and pace.
I wasn't sanctimonious to you, don't be so to me please.
> you would genuinely need to
> look at the full dataset that
> team collected to draw any
> meaningful conclusion here
I compared notes with a couple friends on other teams and it was the same for each one. Yes it's anecdotes but when the same exact people that are producing/integrating the service are also grading its success AND combine this very argument while hiding any data that could be used against them, I know I am dealing with people who will not tell the truth about what the data actually says.