You Don’t Need More AI. You Need a Better Spoon.
AI products are easy to build. Useful ones aren’t.
I scrunched my eyes, trying not to look too skeptical.
My friend was pitching me on a new startup he’d found, led by a repeat founder.
“It seems like a great opportunity. AI that sits on top of your data would be awesome, right? And he said you can ask it stuff like, ‘What will the next 12 months of rents be?’ and it answers you just like that. They’re looking for BD [business development] help, and they’ll pay a referral fee. I thought of you immediately. Would you be interested?”
If I had a dollar for every call like this, I’d be retired. Okay not retired, but I’d definitely be sipping overpriced mocktails on the regular. Okay fine, I kind of do this already. But still!
(For the record, I love that this colleague/friend thought of me first for this. Very kind of him.)
While he was talking, I was already jotting down three companies doing the same exact thing: AI wrappers for your data. All real estate-specific. Two more came to mind while we were on the call. And since then? I've thought of even more.
Because right now, everyone and their seed-stage cousin is building AI for real estate. Don’t believe me? Check out the Blueprint conference agenda. Our panel — cleverly titled All AI Do Is Win, thank you very much — is one of like 5 panels about AI.
It’s all anyone in CRE is talking about. It’s what every founder is pitching. It’s what every VC is funding. (The last two are a bit of a chicken-and-egg situation, but you get the point.)
And yet — when my friend asked if I was interested — I said no.
Not because the founder isn’t smart. I’m sure he is. Not because the tech isn’t flashy. I’m sure it is too. But because they skipped a crucial step: nailing the problem.
Some people call it product-market fit. Some call it “being useful.” Either way, you don’t start with “we have AI.” You start with, “here’s a massive, painful, expensive problem.” And then you use AI — if it makes sense.
I made this mistake too. At my high school graduation, I gave a speech about rejecting conformity. Very original stuff. I quoted E.M. Forster: “Spoon-feeding teaches us nothing but the shape of the spoon.” And I brought a literal spoon on stage, pulled it out from behind the podium, and flung it dramatically over my shoulder. “So let’s throw away our spoons!”
It got a big cheer. It was heartfelt. And it was... completely and adorably wrong.
Because in the real world, people need spoons.
They’re overwhelmed. They're drowning in systems. They're not looking to “find insight” — they’re just trying to survive the workday. As Malcolm Gladwell wrote in Blink, we don’t have the luxury of slow, contemplative decision-making anymore. The world moves too fast. Good tools help us make faster, better decisions with less effort.
And that means the burden is on the builder to be clear. We don’t need a platform that could do anything. We need one that tells us exactly what to do next.
The companies that understand this are the ones that win.
Take HelloData. (Yes, I’m biased — Grace Hill acquired them, and I advocated strongly for that acquisition.) Marc and the team didn’t lead with “cool AI.” They led with a critical pain point in market surveys — a slow, fragmented, manual process — and made it exponentially faster, easier, and more reliable with AI.
Same with EliseAI. They didn’t just toss AI at property management. They zeroed in on the communication mess between prospects, residents, and leasing teams — and solved it.
Start with a problem. Then build your product. Then layer on the AI. In that order. Don’t skip steps, don’t reverse them, and don’t assume the magic works without the foundation.
Fast forward to yesterday. I was catching up with Anne Hollander, who’s on the Blueprint panel with me. I asked if she was worried about cutting through the AI panel noise, and she just laughed:
“Oh, I have strong opinions.”
(She does and I love it.)
She talked about the fallacy of slapping AI on top of messy data and crossing your fingers and hoping magic happens. It never does. If it were that easy, everyone would be doing it.
And if you’ve ever tried to clean and normalize data across CRE systems — trust me, I have — your startup will spend more time and money being a services company than a software one. So be honest with yourself before raising money: do you want to run a services business? That’s fine! But if you want to be a software company, then pick your problem first. Build the spoon. Make it obvious. Make it easy.
Then, and only then, add the magic.
Want help getting your AI spoon in the right drawer?
Come to the All AI Do Is Win panel at Blueprint. Or subscribe below — I write about AI, real estate, and how we make tech feel human.
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Jen’s Reading Corner
If you haven’t read Malcolm Gladwell’s Blink, do it now. It’s a classic and a must-read.
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You identified a big problem: “ And if you’ve ever tried to clean and normalize data across CRE systems” — How can AI solve that one?