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Episode Transcript
Hey folks, Sean here, and today what I want to talk to you about is not chasing the supposed magic that AI is, or at least that everyone still thinks that AI is. Now, I’m doing interviews at the moment, still performing a lot of discovery and research to look for new opportunities to build B2B SaaS applications around with my new favorite tool, that being artificial intelligence, at least the tools made available and widely available these days from companies like Open ai.
Now more than ever, we’re able to build stuff that is ridiculously capable and very, very quickly. So that presents a lot of opportunity. As such, you may be as excited as I am to just divide and conquer and find all the problems you can and ship as many toll as possible. Now, that sounds great and exciting.
One of the challenges with that is still everyone’s perception of what AI is. Now, if you were. Excited about pursuing strategies like that. I don’t want to discourage you. What I want to do is I wanna encourage you and in the right way, I want you to, while you’re performing your discovery, make sure that you’re not falling into the trap of chasing the dream in terms of who you’re interviewing.
It’s like where you’re performing that discovery. Now I’m looking at a number of different industries, and with some of the interviews that I’ve done just yesterday as I was conducting the interview, I was learning about the problems worth solving and. I had uncovered one and a solid one at that. So largely the interview was complete from my perspective, as in I got what I needed.
I know that there’s a painful problem. That’s a great option that can be solved by an AI tool that I could build a SaaS application around. The challenge, however, is it’s easy to. Continue to go deeper, to continue searching even after you’ve found a great problem we’re solving. And what I mean by that is, as you’re interviewing folks, they might just assume that AI can perform magic, which now, don’t get me wrong, the tools are very impressive these days, but there’s, it’s still not magic.
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Like there’s still logic and routine and all that kind of stuff too, what those tools can do. The problem that I’m getting at is in the interview, The subject that I was researching or performing the discovery with, they continued to come up with quote unquote new ideas for what the toll that I may be building can ultimately do.
And that’s the risk. That’s what I want you to be conscious of, because in these conversations, people may be coming up with all kinds of ideas. Now, they may be enthusiastic, and I don’t want to be discouraging to you or to them, but I wanna make sure that you’re focusing on. Again, the problem we’re solving and the ideal problem we’re solving.
So if you’ve found a solid one, which I have, move forward with that. First, be careful not to fall into this trap of basically just solving more and more problems all at the same time, or trying to perform some form of magic and produce significantly more features than you really need to in order to get started in these discovery interviews.
It’s easy for people to get excited about the capabilities of ai, but. They don’t know typically as much as we do about what they can realistically do. And more importantly, they’re also typically not as honest with themselves, at least in those moments about what they can realistically handle, as in they may wanna skip all the steps and just automate the whole thing, or think that that’s what they want.
But in reality, I’ve tried to provide products like those, and more often than not, they fail. Why? Because people aren’t ready for them. They’re not ready to skip all kinds of steps. They’re ready for their most painful, most time-consuming step to go away because they’ve been dealing with that forever. So if you can build your tool around solving that problem, which sounds much more along the criteria that I’ve set and talk about extensively around problems or solving, that is still the best place to start.
You could continue to. Allow those conversations to move forward and talk about cool ideas and all that kind of stuff, and who knows? Maybe that’s future material that can go on your roadmap as in where the product may go from here. But don’t skip the best problem we’re solving that you’ve identified, especially if it’s relatively straightforward.
That’s a great place to start, right? Software cannot be too easy to use, especially if you are working with industries that are not as familiar with some of these concepts like ai.