Are founders adding AI because users want it, or because the pitch deck expects it?
I have been noticing the same pattern in a lot of early product plans. The team wants to add AI before they have fixed the basic workflow.
Not better onboarding later.
Not faster support later.
Not cleaner search later.
AI first.
The demo usually looks good.
But in many cases, it does not improve the thing that matters most. It does not make people come back. It does not make the product easier to adopt. It just adds more build time, more edge cases, and more things to explain.
The few times I have seen it work well, the product already had a clear repeat behavior and the AI removed real user effort. I wrote this down in detail elsewhere, but I want to know how others are seeing this.
Where has AI usefully improved retention, conversion, or support cost in your product? And where did it mostly create more work?
Exactly. That early category assumption is usually formed before the founder realizes it is happening.
This is also why I think the naming/domain decision needs to be pressure-tested while the product is still flexible, not after the market has already learned the wrong frame.
If you are working with any pre-launch founders or MVP teams who are still deciding the name, domain, or positioning direction, feel free to send them my way. That is the stage where I can actually be useful before the brand gets too fixed.
Happy to connect on LinkedIn as well if it makes sense.
The retention angle is the right test. Have you seen a case where AI looked weak in the demo, but still materially improved repeat usage because it removed one annoying step users hit every day?
Yes, actually. One example was a support dashboard where the feature looked pretty underwhelming in demos because it wasn’t flashy at all. But users kept using it because it saved them from rewriting the same replies every day. It removed a small, annoying task they were already doing constantly.
I think that’s the difference I keep noticing. The useful cases usually feel boring in the demo but helpful in daily use.
Feels like a lot of teams are using AI as a way to compensate for unclear core value.
If the main workflow isn’t obvious, adding AI just gives people more to process instead of less.
The few products where I’ve seen it actually work — the value was already clear, and AI just removed friction from something users were already doing.
Otherwise it ends up hurting adoption more than helping.
I also think how the product is positioned (even down to how it’s described or named) plays into this — if people don’t “get it” quickly, AI doesn’t fix that.
Have you seen any product where AI actually made the core use case simpler rather than more complex?
Completely agree with this. The products where it worked well already had a very obvious main use case before anything extra was added.
One example I saw recently was a scheduling tool where users normally had to clean up messy form submissions manually. The added feature just organized the data better and reduced back-and-forth. Nothing fancy, but it made the product easier to use almost immediately.
I think problems start when the added feature becomes the thing users have to figure out instead of helping with something they already understand.
Exactly. That is the difference.
When AI improves a workflow users already understand, adoption feels natural. When AI becomes the new thing they have to understand, it adds friction instead of removing it.
The scheduling example is a good one because the value is obvious: less cleanup, less back-and-forth, faster completion.
That is also where naming matters. If the product name or domain makes users think “AI tool” before they understand the actual relief, it can slow adoption.
The first test is simple:
Can users describe the core benefit without mentioning AI?
If not, the positioning, and sometimes even the name, probably needs to be sharpened before AI gets pushed harder.
That’s actually a good way to look at it. Most users just want something that makes their work easier. The moment they feel like they need to learn the product first, you can almost see the drop-off happen.
I’ve seen founders spend more time explaining the feature than explaining the actual benefit, which usually says a lot on its own.
A few people asked me where I’ve actually seen this go wrong vs work well, so I wrote down some real patterns we’ve been seeing during product planning and MVP discussions. Especially the cases where teams added features too early before the main workflow was even stable.
Why Adding AI Too Early Can Slow Your Startup’s Growth (And How to Know If It’s Too Soon)
That’s the exact point.
A lot of MVPs don’t fail because the AI is bad. They fail because the product is already unclear before AI gets added.
And naming/domain is part of that.
Early stage is the cheapest time to fix the name, positioning, and .com direction. Once founders launch, write content, collect users, and get remembered under a weak name, changing it becomes harder.
For this kind of MVP/product planning layer, I’d look for a name that feels serious and scalable from day one. Something like Beryxa.com fits better than another descriptive AI/MVP name because it can carry a broader product or venture studio brand without boxing it into one feature.
That’s why I think naming and domain fit should be part of MVP planning early, not after traction.
That’s true. A weak or confusing name creates friction way earlier than most founders realize.
I’ve seen products where the workflow was decent, but the positioning made people assume it was either too technical, too broad, or just another generic tool before they even tried it.
And yes, changing direction later gets messy fast once content, backlinks, demos, and word-of-mouth start building around it.
Exactly.
That is why I think naming should not be treated as a “later branding task.” It is part of whether the MVP gets understood in the first place.
Once a founder has content, demos, backlinks, screenshots, and early users tied to the wrong frame, even a good product starts carrying old baggage.
The best time to fix it is before launch or before the product gets publicly repeated.
If you’re working with founders at the MVP/planning stage, this is probably where naming/domain fit should be pressure-tested early.
Happy to connect on LinkedIn if useful. This is the kind of thing I usually help founders think through before the brand gets too fixed:
https://www.linkedin.com/in/aryan-y-0163b0278/
Agreed. A lot of founders think the problem is acquisition when sometimes people just never fully understood the product in the first place. And once a certain perception sticks, it’s surprisingly hard to undo later.
Appreciate the discussion here. You brought up a side of MVP planning that honestly does not get talked about enough.
Exactly, that perception layer is usually invisible until it starts hurting conversion.
Glad the framing was useful.
If you ever work with a founder who is pre-launch, still shaping the MVP, or unsure whether the name/domain fits the product direction, feel free to point them my way.
That is usually the best stage to fix it before the market locks onto the wrong frame.
Yes, once people mentally place a product into the wrong category, everything after that becomes harder including onboarding, retention, and even referrals. I think a lot of founders underestimate how early those assumptions form. Usually before the product is even fully built.