Because VC money depends on the company’s growth plans, and VC money isn’t offered if “AI” isn’t part of the product any more. (Sample size of one, told by a friend who’s in direct contact with the CEO.)
And also I suspect most companies work with big consultants like Bain and McKinsey because they (the companies) are scared and clueless and have no vision about how to run their businesses, which is perfect for them (the big consultants) to extract value from them with smoke up their holes and predictions about a future no one has ever seen yet.
I consult on the topic of technology for non-technology companies (think like a hydraulic piston manufacturer or something. They consume software in order to create something else.)
Basically if the technical leaders at such companies fail to shoehorn AI in somewhere, they will have to find a way to demonstrate to their board of directors that they are keeping up to date and not allowing the business to settle in to abandonware. The guys selling the software also have a similar problem -- industrial abandonware whose development team was laid off 12 years ago is for sale right now and you have to be careful not to accidentally spend a million dollars on it. Something that has AI bolted on, even in an insignificant capacity, is more likely to have present day relevance.
As someone who has experience building a small AI powered company and making these decisions on a small scale, I can say maybe?
For some companies, automation that is based on being able to pull info from a gigantic knowledge base that still has bounds is helpful for them. Most orgs are still figuring this out in the face of immense pressure from their stakeholders not to fall behind and miss any potential windfall. They don’t know how LLMs can help them but the hype may push them in the black or lead to (false) growth so they lean in.
I think many of the larger tech companies were hoping to make human engineers obsolete so that they could achieve the true promise of SaaS - almost no investment, instant money faucet. Unfortunately for them, we still need people to help us understand people so engineers, designers, and product managers aren’t as expendable as some of them were hoping.
No one thought AI would be free or cheap, but a LOT of ppl bet that the true cost could be obfuscated or waved away temporarily while the money was stupid and then revealed once enterprise was addicted and struggled to manage their switching costs. By then the smartest folks have made their money, moved it to safer havens, and await the next stage of the lifecycle.
I love LLMs but the way we use them seems very stupid, IMHO. It’s like everything is a screw now but everyone still has bolts and nails.
That was a relief. I thought users want it. I can understand investors being dumbfucks in grasping actual customer needs or to be completely ignorant about it.
ok but it's in a lot of places where it seems totally unnecessary. For example, I do not need an AI chatbot to help me decide what kind of pizza to order.
If the AI is deeply integrated and feature-rich, I would prefer it. However, if it is just a disconnected chat interface, I don't think it is necessary. Additionally, whether it requires an extra fee is a factor that must be considered.
:-) I have had my share of bad meetings over this, I have always advocated to start with enhancing existing features of product that would benefit from AI. But the org mandate is compulsory one idea for each product and new products should be agentic or RAG based only. I don't understand this rush to incorporate AI, I feel shit must be organic and self paced, forced adoptions wont last long.
I've found the new AI customer support bots that a lot of websites started using are usually more knowledgeable and honest about whatever product they represent than human agents are. I'm sure that will change eventually when they start figuring out how to lock down the AI to a "safe script" the same way they train human customer support, but for now, it's pretty great.
I think for a good share of products it isn't necessary, but I also guess that it's very hard to see from the start. I strongly believe there generally is value in AI, but finding this particular application that unlocks it -- is a conundrum. So, if I imagine myself being a head/vp of product, in one of these companies, I have pretty much no choice but to integrate it and study the metrics. Then, after a few iterations the value is either found or not, and depending on the sanity of stakeholders, the useless AI features can be retired. But not before the evidence is collected, because you can't fight the AI frenzy without ones, lol
Product owners were promised that LLMs/AI is a magical genie that can do anything, so they make it do everything. The trillions of dollars spent on data centers and thousands of layoffs has to be justified somehow.
This. In many cases, they cannot even properly articulate how AI will improve things beyond vague, meaningless, corporate-speak jargon. Most cannot even properly define AI’s place in the org in the first place. They just cannot be seen as someone who is “behind the times” or “a tech dinosaur”.
There are most likely many different reasons. Cutting costs is a big one; leveraging new functionality in a simpler way is another one. For instance, yesterday I watched some youtube videos and one use case was "count to 100 in a very sad voice", even if that is more a joke and ... pretty useless on its own. The AI did.
What was interesting to me here was that if I were to write a program to do the same, I could most likely do that (just simplify the tasks as they are and implement each one), but it would take me longer. As much as I hate AI, there are real benefits in at the least some areas.
Because VC money depends on the company’s growth plans, and VC money isn’t offered if “AI” isn’t part of the product any more. (Sample size of one, told by a friend who’s in direct contact with the CEO.)
And also I suspect most companies work with big consultants like Bain and McKinsey because they (the companies) are scared and clueless and have no vision about how to run their businesses, which is perfect for them (the big consultants) to extract value from them with smoke up their holes and predictions about a future no one has ever seen yet.
I consult on the topic of technology for non-technology companies (think like a hydraulic piston manufacturer or something. They consume software in order to create something else.)
Basically if the technical leaders at such companies fail to shoehorn AI in somewhere, they will have to find a way to demonstrate to their board of directors that they are keeping up to date and not allowing the business to settle in to abandonware. The guys selling the software also have a similar problem -- industrial abandonware whose development team was laid off 12 years ago is for sale right now and you have to be careful not to accidentally spend a million dollars on it. Something that has AI bolted on, even in an insignificant capacity, is more likely to have present day relevance.
As someone who has experience building a small AI powered company and making these decisions on a small scale, I can say maybe?
For some companies, automation that is based on being able to pull info from a gigantic knowledge base that still has bounds is helpful for them. Most orgs are still figuring this out in the face of immense pressure from their stakeholders not to fall behind and miss any potential windfall. They don’t know how LLMs can help them but the hype may push them in the black or lead to (false) growth so they lean in.
I think many of the larger tech companies were hoping to make human engineers obsolete so that they could achieve the true promise of SaaS - almost no investment, instant money faucet. Unfortunately for them, we still need people to help us understand people so engineers, designers, and product managers aren’t as expendable as some of them were hoping.
No one thought AI would be free or cheap, but a LOT of ppl bet that the true cost could be obfuscated or waved away temporarily while the money was stupid and then revealed once enterprise was addicted and struggled to manage their switching costs. By then the smartest folks have made their money, moved it to safer havens, and await the next stage of the lifecycle.
I love LLMs but the way we use them seems very stupid, IMHO. It’s like everything is a screw now but everyone still has bolts and nails.
Someone I know said it's because investors get excited to know your product has AI.
That was a relief. I thought users want it. I can understand investors being dumbfucks in grasping actual customer needs or to be completely ignorant about it.
Every company is not incorporating AI everywhere. It maybe seems that way and of course it's "everywhere" but not every single company.
ok but it's in a lot of places where it seems totally unnecessary. For example, I do not need an AI chatbot to help me decide what kind of pizza to order.
If the AI is deeply integrated and feature-rich, I would prefer it. However, if it is just a disconnected chat interface, I don't think it is necessary. Additionally, whether it requires an extra fee is a factor that must be considered.
:-) I have had my share of bad meetings over this, I have always advocated to start with enhancing existing features of product that would benefit from AI. But the org mandate is compulsory one idea for each product and new products should be agentic or RAG based only. I don't understand this rush to incorporate AI, I feel shit must be organic and self paced, forced adoptions wont last long.
From the POV of a CEO(not myself), it's a predictably priced, affordable insurance against potentially falling behind the competition.
I've found the new AI customer support bots that a lot of websites started using are usually more knowledgeable and honest about whatever product they represent than human agents are. I'm sure that will change eventually when they start figuring out how to lock down the AI to a "safe script" the same way they train human customer support, but for now, it's pretty great.
Related: https://news.ycombinator.com/item?id=48964185
If enough people/companies are on the bandwagon, you're afraid to push back and be the crazy one, potentially losing money. So you roll with it.
I think for a good share of products it isn't necessary, but I also guess that it's very hard to see from the start. I strongly believe there generally is value in AI, but finding this particular application that unlocks it -- is a conundrum. So, if I imagine myself being a head/vp of product, in one of these companies, I have pretty much no choice but to integrate it and study the metrics. Then, after a few iterations the value is either found or not, and depending on the sanity of stakeholders, the useless AI features can be retired. But not before the evidence is collected, because you can't fight the AI frenzy without ones, lol
Product owners were promised that LLMs/AI is a magical genie that can do anything, so they make it do everything. The trillions of dollars spent on data centers and thousands of layoffs has to be justified somehow.
AI is well and good until it touches the product in any possible way. Please integrate in your own yard not in user's face.
I don't mind AI being added to products, I just want it to solve a real problem instead of becoming another button that I never click.
FOMO.
This. In many cases, they cannot even properly articulate how AI will improve things beyond vague, meaningless, corporate-speak jargon. Most cannot even properly define AI’s place in the org in the first place. They just cannot be seen as someone who is “behind the times” or “a tech dinosaur”.
To make the line go up.
There are most likely many different reasons. Cutting costs is a big one; leveraging new functionality in a simpler way is another one. For instance, yesterday I watched some youtube videos and one use case was "count to 100 in a very sad voice", even if that is more a joke and ... pretty useless on its own. The AI did.
What was interesting to me here was that if I were to write a program to do the same, I could most likely do that (just simplify the tasks as they are and implement each one), but it would take me longer. As much as I hate AI, there are real benefits in at the least some areas.