"Why aren't people more resentful that these companies have pushed this technology upon them and now everyone is feeling a tremendous amount of anxiety," - Chris Willis, chief design officer and futurist for data platform biz Domo
> Governed Data for AI Agents
> Built with trusted AI models in mind
> Enterprise AI for your business data
> Connect your business data. Build AI-powered dashboards, agents, and automations. Skip the roadblocks.
> Use the best from OpenAI, Anthropic, and more. Domo provides hosted models from the top providers, or you can access your own models inside of Domo through our AI connectors.
i have had domo pushed on me in a company and i did everything in my power to get us to cancel that subscription and we did. it was such a waste of money. If I was able to rebuild our entire reporting workflow in a month, imagine how fast it is to now do that with LLMs?
I don't believe LLMs make SAAS useless, but there are a subset of SAAS companies that AI truly does obviate. Among them are companies like DOMO, whose business model is best described as selling the fantasy of the "data-driven" org to leadership. They floated off the fumes of yesterday's hype. It's kind of painful to see how they're trying to inject themself into this cycle.
also what – chief design officer and futurist for DOMO?? what do they do? sorry to be a dick about it but a quote like "why aren't people more resentful that these companies have pushed this technology upon them" lacks a lot of self awareness lol.
Having used Domo in anger it is truly a terrible product with unclear edge cases and weird problems, it definitely feels its age at this point and for what it does using superset or some other oss tech would at least fail in ways you can debug.
Thing is, software isn't the issue when building a business - Dropbox being a great example because even now people are like "but that's just rsync-as-a-service". Software and making a business out of it are two different things.
Strong agree with the premises of the article: I like the framing that the AI hype-masters are successful because they instill a fear of missing out in corporate leaders.
I have worked with old fashioned neural networks, deep learning, and now LLM-specific deep learning: wonderful technology, but over hyped, and advice to go a little slowly, with firm use cases that are financially viable is great advice!
> "There will be a reckoning when it comes to budgets around these things," he said, "because CFOs are starting to as 'Why are we spending all this money and not gaining anything?'"
Yea, currently the thinking seems to be, if we're spending money on tokens, the work is inherently worth it. However, this clearly cannot always be the case - one of the more difficult things I've worked on lately is tracking token usage to measurable work outputs, but measuring work output reliably is a notoriously difficult problem historically in tech, and opens a lot of uncomfortable conversations.
> The result is a lot of proof-of-concept projects that lack what's required to make them durable, trustworthy, and deployable at scale. Starting with business needs first is essential.
A bunch of frivolous projects that fail sounds to me like a pretty good way to learn how far a new technology can be trusted.
If you're considering putting AI into something load bearing you either need a engineer who has not been participating so they can say "no" or one who has made 15 failed AI projects so they can say "maybe". The very worst case is to pressure somebody who doesn't know the technology very well into saying "yes".
The management is the team that wants it to go, so they do not enable anyone to say no.
I have been in meetings where the top item is ensuring security of XYZ llm component, and after we've shown its inherently not something secureable from what the product requirements are then those product requirements are discarded.
For many of these companies the entire thing is a smoke and mirrors game to just get more money, they have little to no commitment to ... anything really.
> ...learn how far a new technology can be trusted
I think you've missed the point of this statement:
> Starting with business needs first is essential
This is a negative shift I've seen in product now. Instead of emphasizing with the user and trying to understand the domain, processes, real-world usage scenarios, product teams are now building junk prototypes and throwing these over the wall at the user. Maybe this works for some spaces and domains.
But the reality is that for many end consumers of software, it's not a good experience to use janky software that changes behaviors, flows, and screens on a whim now because product can.
I think AI has had a negative effect on product teams; I can see all pretense of thoughtful design and execution after understanding the customer being thrown out the window and leaving a much worse end-user experience as designs and capabilities shift around without foresight and product teams "feel" their way through.
Perhaps I should have mentioned that if you built something in ignorance of the business' needs, you shouldn't then go exposing the business' customers to that thing.
If somebody is shipping the prototypes, that's a problem. I was just speaking up for the utility of playing around as a necessary part of learning your tools.
There is like 0 cost for distribution, switching and using LLMs "AI" and other tools. Whatever comes, comes to everybody. There is basically 0 first movers advantage, that cannot be overcome in couple of months when new usefull tools become available.
>>“… wonders why people aren't more annoyed with AI companies “
Outside a small bubble within Silicon Valley and the finance ecosystem funding it, I’d say most folks are increasingly fed up with AI.
It’s a very noticeable shift these last 6 months. The mood went from excited, to just annoyed at all the slop and folks using AI as a half-baked easy button vs doing real deep value-add thought.
Business is also noticing that the ROI simply isn’t there and a lot written about this. That doesn’t bode well for AI providers that need to massively increase prices to make the math work on their business models.
The world inside of the AI bubble seems largely ignorant of the mood shift underway, which suggests interesting times are ahead.
I think it's just hard to know this for the people working on it. AI radically changed my life. I'm doing at least 10 times more, more ambitious, higher quality work. I've been listening to people around me talking about alignment and the singularity for almost a decade. It's strange to imagine that people live in a world where this isn't and hasn't been happening for a while now. "Over-hyped" is not the word I would use if I take my daily experience as an example, nor when I consider even lower-bound projections.
It's actually not a bad comparison. You might feel like you're getting 10x more done with AI but it's going to be 10x more buggy and/or 10x missing the edge cases, in the way AI usually misses the mark. I don't do coke, but I know plenty of people who do, and I would not trust them with anything important.
I speak to people who work at the upper echelons across various industries regularly and whether you want to believe it or not idc - the management are desperately trying to push AI but it just doesn’t add much value to what they do. At best it’s just a really good search engine across internal data. Many of these places already had things called macros in place so there’s barely any value add.
Funny, I see HN as having a high concentration of anti-AI comments and general AI doubt. Yours included.
The vibe among less technical people I talk to has a negative sentiment about AI and AI companies, but largely because they see AI as more effective and capable. They think it’s coming for their job and way of life and they don’t like that.
If AI is coming for people’s jobs and it’s more effective, the management of firms across multiple industries should reflect that by firing lots of people right now. Why wait? Collect the extra cash flows today given future expectations of technological progress. Who says no to more money? Lmfao.
Or… perhaps they don’t quite stand all that much behind that claim.
Moreover ‘less technical’ means what exactly? I referenced people who are senior managers who are trying to wedge AI where they can. Who are you referencing?
We have a skewed-to-the-positive view about AI around here because we are the industry where it has turned out to work to a significant degree. We can argue about whether it lived up to the promises and the practical implications of using it and how much you can trust it, etc., but it's actually a debate in our space because there is enough value that it is worth debating. I think in a lot of other spaces it isn't working nearly as well. From my blog https://jerf.org/iri/post/2026/programming_is_engineering/ :
"It’s worth taking a moment to really watch how [AIs] work, as they are working on some relatively lengthy task for you. It reminds me of bumper bowling [1]; link to a short video showing what it is. The AIs bang along all our bumpers; failing compiles, failing tests, failing integrations, error messages, all the bumpers we’ve built into our engineering process, and in the end they get a good result. But that good result is as much a result of all the solid engineering processes we have installed as anything else, because the AI without those protections rolls into the gutter relatively quickly. In those fields where the bumpers can’t be built as easily or in as great a quantity as we can have them, that’s what happens with the AIs.
"... it’s not that “programmers are awesome”, it’s that our domain is amenable to having all these bumpers in the first place."
I can think of bumpers for other domains, but not in the quantity we have in our space. Plus there's things like accounting, where "accounting" already is the bumper, having an AI banging into the accounting bumpers is much more concerning than a syntax error on compile is for us. Coding AIs would be nearly useless if the bumpers weren't there, and I think that's where a lot of other domains end up with when it comes to AI.
If you want to see what I mean, watch a longer coding process in your AI, notice the first place it bangs into one of the bumpers I'm talking about, and then imagine how valuable the AI would be if instead it didn't realize that it banged into a bumper, continued on obliviously, and then went off into ever-more-fantastic flights of fancy with no connection to reality. Such an AI would be too hazardous to use. I think that's the experience of almost every other field right now.
Indeed, and HN also has a huge "pro-AI" bias... everytime you make a comment to point out that AI is first and foremost a political artefact, rather than a technology, and that it will be weaponized against people, they downvote...
Although they know perfectly well what happened to their search / personal data, but they still don't want to see the obvious
There's a lot of overlap between people who cannot stand the AI boosters, don't want a data center built anywhere near them, are sick of the slop, and still use a chatbot for some stuff.
I don't think this is hypocrisy. I don't think it's a contradiction at all.
It suggests that people actually like natural language interfaces where they make sense and the price is reasonable. What they don't like is the rhetoric, behavior, impact on electricity prices, insistence on cramming it into places where it doesn't belong, layoffs, threats, and general obnoxiousness of the people pushing it and their general milieu.
I think people have stopped giving tech companies the benefit of the doubt, unlike the start of the social media era and the smartphone era.
Both of those things did transform life & culture but mostly to the benefit of their makers. People now expect the same from AI and for better or worse most of the CEOs are not even pretending this time. The most they do is some vague hope that it'll all workout magically somehow.
the problem is that companies fundementally misunderstand what the true issue is at hand: companies should be afraid of what smaller groups of people can accomplish now.
mid to large sized companies always had to man-power to produce anything they could imagine and AI is not going to change that.
what will change is that your paid product will become free because someone got annoyed at a bug with your paid product, remade it with AI and made it opensource or for a fraction of the price.
the floor has been raised while the ceiling will stay relatively the same, most medium to large companies were already hovering around the ceiling so at the end of the day the framework that these companies were built on is crumbling and that's what should make them afraid, not the fact that they're 'missing out' on AI.
Domo is now apparently "Governed Data for AI Agents".
The desperation for commodity services and second-tier products to stay relevant is widespread. See also intercom.com "The only helpdesk designed for the AI Agent era".
There is kind of a spec - its capture knowledge work / thought so they can sell it back to you. Just how uber captured delivery/taxi making it all cheap and subsidised to start with the goal is to embed it everywhere and make people dependent. And then maybe some hope in the future they no longer have to pay anyone, or maybe pay people far less and devalue them.
"Why aren't people more resentful that these companies have pushed this technology upon them and now everyone is feeling a tremendous amount of anxiety," - Chris Willis, chief design officer and futurist for data platform biz Domo
> Governed Data for AI Agents
> Built with trusted AI models in mind
> Enterprise AI for your business data
> Connect your business data. Build AI-powered dashboards, agents, and automations. Skip the roadblocks.
> Use the best from OpenAI, Anthropic, and more. Domo provides hosted models from the top providers, or you can access your own models inside of Domo through our AI connectors.
https://www.domo.com
https://www.domo.com/ai
OK
i have had domo pushed on me in a company and i did everything in my power to get us to cancel that subscription and we did. it was such a waste of money. If I was able to rebuild our entire reporting workflow in a month, imagine how fast it is to now do that with LLMs?
I don't believe LLMs make SAAS useless, but there are a subset of SAAS companies that AI truly does obviate. Among them are companies like DOMO, whose business model is best described as selling the fantasy of the "data-driven" org to leadership. They floated off the fumes of yesterday's hype. It's kind of painful to see how they're trying to inject themself into this cycle.
also what – chief design officer and futurist for DOMO?? what do they do? sorry to be a dick about it but a quote like "why aren't people more resentful that these companies have pushed this technology upon them" lacks a lot of self awareness lol.
Having used Domo in anger it is truly a terrible product with unclear edge cases and weird problems, it definitely feels its age at this point and for what it does using superset or some other oss tech would at least fail in ways you can debug.
Is the CDOs statement to be read as "We have no moat."?
We have the infamous "Dropbox" is a weekend project, well now I'd say we are in the era of it.
And I bet I could build within 5 working day a Saas replacement of Domo.
There is no moat anymore.
Thing is, software isn't the issue when building a business - Dropbox being a great example because even now people are like "but that's just rsync-as-a-service". Software and making a business out of it are two different things.
>We have the infamous "Dropbox" is a weekend project...
Oh really? Then why is syncthing (for example), still so much harder to use than dropbox?
No comment on the content of the article, but I have to say bravo to whoever wrote that headline.
Reminds me of (though different wordplay) Foot heads arms body
[https://en.wikipedia.org/wiki/Talk:Michael_Foot#Foot_Heads_A...]
Knew immediately it would be the reg but think maybe they missed a trick:
No mo' AI FOMO, go slow-mo, crows Domo CDO
If anyone visited my blog I could say they were inspired by me: :) https://writing.unified-designs.com/ai-coding-fomo.html
Bravo to the Domo CDO, who's fomo won't stop slo-mo no-mo'
Yolo Domo Arigato
Mr. Roboto
Oh...
Another Chuck fan I see. I'm glad to see I'm not alone.
won't stop with no slop slo-mo no-mo'
Domo CDO says no mo slop yo
Reminds me of the Arrested Development scene: Bob Loblaw Lobs Law Bomb.
This scene nearly killed me, haha.
I’ll be working on my law blog. The Bob Loblaw Law Blog.
Also the tongue twisters from princess carolyn
> to whoever
Whomever.
Whomever gives a shit?
My favourite headline: Super Caley go ballistic, Celtic are atrocious
https://en.wikipedia.org/wiki/Super_Caley_go_ballistic%2C_Ce...
I was hoping for "CDOmo" at the end.
Not quite 'HEADLESS BODY IN TOPLESS BAR,' but damn close.
it is most excellent
Strong agree with the premises of the article: I like the framing that the AI hype-masters are successful because they instill a fear of missing out in corporate leaders.
I have worked with old fashioned neural networks, deep learning, and now LLM-specific deep learning: wonderful technology, but over hyped, and advice to go a little slowly, with firm use cases that are financially viable is great advice!
> "There will be a reckoning when it comes to budgets around these things," he said, "because CFOs are starting to as 'Why are we spending all this money and not gaining anything?'"
Yea, currently the thinking seems to be, if we're spending money on tokens, the work is inherently worth it. However, this clearly cannot always be the case - one of the more difficult things I've worked on lately is tracking token usage to measurable work outputs, but measuring work output reliably is a notoriously difficult problem historically in tech, and opens a lot of uncomfortable conversations.
> The result is a lot of proof-of-concept projects that lack what's required to make them durable, trustworthy, and deployable at scale. Starting with business needs first is essential.
A bunch of frivolous projects that fail sounds to me like a pretty good way to learn how far a new technology can be trusted.
If you're considering putting AI into something load bearing you either need a engineer who has not been participating so they can say "no" or one who has made 15 failed AI projects so they can say "maybe". The very worst case is to pressure somebody who doesn't know the technology very well into saying "yes".
The management is the team that wants it to go, so they do not enable anyone to say no.
I have been in meetings where the top item is ensuring security of XYZ llm component, and after we've shown its inherently not something secureable from what the product requirements are then those product requirements are discarded.
For many of these companies the entire thing is a smoke and mirrors game to just get more money, they have little to no commitment to ... anything really.
But the reality is that for many end consumers of software, it's not a good experience to use janky software that changes behaviors, flows, and screens on a whim now because product can.
I think AI has had a negative effect on product teams; I can see all pretense of thoughtful design and execution after understanding the customer being thrown out the window and leaving a much worse end-user experience as designs and capabilities shift around without foresight and product teams "feel" their way through.
Perhaps I should have mentioned that if you built something in ignorance of the business' needs, you shouldn't then go exposing the business' customers to that thing.
If somebody is shipping the prototypes, that's a problem. I was just speaking up for the utility of playing around as a necessary part of learning your tools.
There is like 0 cost for distribution, switching and using LLMs "AI" and other tools. Whatever comes, comes to everybody. There is basically 0 first movers advantage, that cannot be overcome in couple of months when new usefull tools become available.
>>“… wonders why people aren't more annoyed with AI companies “
Outside a small bubble within Silicon Valley and the finance ecosystem funding it, I’d say most folks are increasingly fed up with AI.
It’s a very noticeable shift these last 6 months. The mood went from excited, to just annoyed at all the slop and folks using AI as a half-baked easy button vs doing real deep value-add thought.
Business is also noticing that the ROI simply isn’t there and a lot written about this. That doesn’t bode well for AI providers that need to massively increase prices to make the math work on their business models.
The world inside of the AI bubble seems largely ignorant of the mood shift underway, which suggests interesting times are ahead.
I think it's just hard to know this for the people working on it. AI radically changed my life. I'm doing at least 10 times more, more ambitious, higher quality work. I've been listening to people around me talking about alignment and the singularity for almost a decade. It's strange to imagine that people live in a world where this isn't and hasn't been happening for a while now. "Over-hyped" is not the word I would use if I take my daily experience as an example, nor when I consider even lower-bound projections.
>I'm doing at least 10 times more, more ambitious, higher quality work.
Got any examples you can share?
> if I take my daily experience as an example, nor when I consider even lower-bound projections.
did you generate 10x more income in the time AI changed your life? What is the projection you are doing?
> I'm doing at least 10 times more, more ambitious, higher quality work.
Is your pay scaling in a similar manner? Or have you just raised the floor for what's expected of you?
Cocaine radically changed my life. I'm doing at least 10 times more, more ambitious, higher quality work.
It's actually not a bad comparison. You might feel like you're getting 10x more done with AI but it's going to be 10x more buggy and/or 10x missing the edge cases, in the way AI usually misses the mark. I don't do coke, but I know plenty of people who do, and I would not trust them with anything important.
Agreed. This place is legit delululand.
I speak to people who work at the upper echelons across various industries regularly and whether you want to believe it or not idc - the management are desperately trying to push AI but it just doesn’t add much value to what they do. At best it’s just a really good search engine across internal data. Many of these places already had things called macros in place so there’s barely any value add.
> Agreed. This place is legit delululand.
Funny, I see HN as having a high concentration of anti-AI comments and general AI doubt. Yours included.
The vibe among less technical people I talk to has a negative sentiment about AI and AI companies, but largely because they see AI as more effective and capable. They think it’s coming for their job and way of life and they don’t like that.
Your post captures exactly what I’m saying.
If AI is coming for people’s jobs and it’s more effective, the management of firms across multiple industries should reflect that by firing lots of people right now. Why wait? Collect the extra cash flows today given future expectations of technological progress. Who says no to more money? Lmfao.
Or… perhaps they don’t quite stand all that much behind that claim.
Moreover ‘less technical’ means what exactly? I referenced people who are senior managers who are trying to wedge AI where they can. Who are you referencing?
I believe he is referencing the proletariat masses, the rabble, etc.
We have a skewed-to-the-positive view about AI around here because we are the industry where it has turned out to work to a significant degree. We can argue about whether it lived up to the promises and the practical implications of using it and how much you can trust it, etc., but it's actually a debate in our space because there is enough value that it is worth debating. I think in a lot of other spaces it isn't working nearly as well. From my blog https://jerf.org/iri/post/2026/programming_is_engineering/ :
"It’s worth taking a moment to really watch how [AIs] work, as they are working on some relatively lengthy task for you. It reminds me of bumper bowling [1]; link to a short video showing what it is. The AIs bang along all our bumpers; failing compiles, failing tests, failing integrations, error messages, all the bumpers we’ve built into our engineering process, and in the end they get a good result. But that good result is as much a result of all the solid engineering processes we have installed as anything else, because the AI without those protections rolls into the gutter relatively quickly. In those fields where the bumpers can’t be built as easily or in as great a quantity as we can have them, that’s what happens with the AIs.
"... it’s not that “programmers are awesome”, it’s that our domain is amenable to having all these bumpers in the first place."
I can think of bumpers for other domains, but not in the quantity we have in our space. Plus there's things like accounting, where "accounting" already is the bumper, having an AI banging into the accounting bumpers is much more concerning than a syntax error on compile is for us. Coding AIs would be nearly useless if the bumpers weren't there, and I think that's where a lot of other domains end up with when it comes to AI.
If you want to see what I mean, watch a longer coding process in your AI, notice the first place it bangs into one of the bumpers I'm talking about, and then imagine how valuable the AI would be if instead it didn't realize that it banged into a bumper, continued on obliviously, and then went off into ever-more-fantastic flights of fancy with no connection to reality. Such an AI would be too hazardous to use. I think that's the experience of almost every other field right now.
[1]: https://www.youtube.com/shorts/yKOBBwUw8yg
Indeed, and HN also has a huge "pro-AI" bias... everytime you make a comment to point out that AI is first and foremost a political artefact, rather than a technology, and that it will be weaponized against people, they downvote...
Although they know perfectly well what happened to their search / personal data, but they still don't want to see the obvious
It took the desktop computer revolution about two decades to show up in productivity statistics. Itt takes time to adapt.
Even within SV there are still luddites who sometimes type out code, in mid 2026!!!
To say it briefly:
>Why aren't people more resentful that these companies have pushed this technology upon them
They are.
I agree, and with a little nuance:
There's a lot of overlap between people who cannot stand the AI boosters, don't want a data center built anywhere near them, are sick of the slop, and still use a chatbot for some stuff.
I don't think this is hypocrisy. I don't think it's a contradiction at all.
It suggests that people actually like natural language interfaces where they make sense and the price is reasonable. What they don't like is the rhetoric, behavior, impact on electricity prices, insistence on cramming it into places where it doesn't belong, layoffs, threats, and general obnoxiousness of the people pushing it and their general milieu.
Which makes perfect sense.
I think people have stopped giving tech companies the benefit of the doubt, unlike the start of the social media era and the smartphone era.
Both of those things did transform life & culture but mostly to the benefit of their makers. People now expect the same from AI and for better or worse most of the CEOs are not even pretending this time. The most they do is some vague hope that it'll all workout magically somehow.
Kudos for the title
the problem is that companies fundementally misunderstand what the true issue is at hand: companies should be afraid of what smaller groups of people can accomplish now.
mid to large sized companies always had to man-power to produce anything they could imagine and AI is not going to change that.
what will change is that your paid product will become free because someone got annoyed at a bug with your paid product, remade it with AI and made it opensource or for a fraction of the price.
the floor has been raised while the ceiling will stay relatively the same, most medium to large companies were already hovering around the ceiling so at the end of the day the framework that these companies were built on is crumbling and that's what should make them afraid, not the fact that they're 'missing out' on AI.
"futurist for data platform" - whatever happened to that Shingy guy?
Domo is now apparently "Governed Data for AI Agents".
The desperation for commodity services and second-tier products to stay relevant is widespread. See also intercom.com "The only helpdesk designed for the AI Agent era".
Doh.
Too many "o"s.
There is kind of a spec - its capture knowledge work / thought so they can sell it back to you. Just how uber captured delivery/taxi making it all cheap and subsidised to start with the goal is to embed it everywhere and make people dependent. And then maybe some hope in the future they no longer have to pay anyone, or maybe pay people far less and devalue them.
"Domo Says No to AI FOMO"
FTFY the headline for you
Domo Says No Mo' to AI FOMO
DOMO CDO: Yo, No Go YOLO AI FOMO, bro