We’re building PotenAI — an AI platform for self-discovery
Hey Indie Hackers 👋
We’re a small team building PotenAI, an AI-powered platform that helps people discover their hidden potential.
The problem we’re trying to solve is simple but important:
Most people don’t really know what they’re naturally good at.
Career decisions are often based on pressure, randomness, or limited exposure rather than real self-awareness.
We believe AI can change that.
PotenAI is designed to help users understand their strengths, interests, and potential directions through personalized AI insights—so they can make better decisions about careers, learning, and personal growth.
We’re currently in the early stage and actively building the first version.
We’re sharing everything publicly as we build and would love feedback from this community.
👉 What do you think is the biggest gap in today’s career/self-discovery tools?
We’re here to learn and improve.
The pushback about narrowing to a specific user and decision is the most useful thing in this thread. Self-discovery is a category, not a problem. The moment you can say which specific person, facing which specific decision, at which specific moment reaches for PotenAI, the product becomes something you can actually build toward.
The concrete versus generic insight problem is real and it's the reason most personality tools feel hollow after the novelty wears off. What would make an insight from PotenAI feel like something someone would actually act on rather than just find interesting?
This is genuinely one of the most valuable pieces of feedback we've received—thank you.
You're absolutely right that self-discovery is a category, not a problem. We've been thinking a lot about narrowing the focus to a specific user and a specific decision rather than trying to solve everything at once.
One direction we're exploring is helping people who are actively questioning their next career or education step. Instead of giving broad personality descriptions, the goal is to provide actionable insights—for example, highlighting specific strengths backed by the user's responses, explaining why those strengths were identified, and connecting them to concrete career paths, learning recommendations, or entrepreneurial opportunities.
Our goal isn't for users to leave saying, "That was interesting." We want them to leave saying, "I know what I'm going to do next."
Comments like yours are exactly why we're building in public. Thanks again for taking the time to share your perspective.
Narrowing from a whole category down to one specific decision, like the next career or education step, is a much more testable promise than open-ended self-discovery. "I know what I'm going to do next" is a great bar to hold the product to, it's concrete enough that you'll actually know if you're hitting it or not. How are you planning to measure whether someone actually leaves with that clarity versus just feeling like the session was interesting?
That's a really insightful question, and it's something we've been discussing internally.
We don't want success to be measured by whether users simply enjoy the experience. Our goal is for people to leave PotenAI with a clearer understanding of their next step—whether that's exploring a specific career path, developing a particular skill, pursuing further education, or validating a direction they were already considering.
One of the ways we're thinking about measuring this is by asking users to rate their level of career clarity before and after completing the assessment. Over time, we'd also like to follow up with users to understand whether they actually acted on the recommendations and found them valuable.
Ultimately, if someone finishes PotenAI and can confidently say, "I know what I want to explore next, and I understand why," that's the outcome we're building toward.
Measuring career clarity before and after, then following up on whether people actually acted on it, is a real outcome metric instead of a vanity one, most self-discovery tools stop at "did you enjoy it." Following up on actual follow-through is the harder but more honest number to chase. How long after the assessment are you planning to check back in, is that a matter of weeks, or long enough to see if they actually took the step?
I think there is a real human experience here, but I’m not yet sure it has been framed as a clear business problem. Many people feel uncertain about what they are naturally good at, but that is also something people often explore through life experience.
“Most people don’t know what they’re naturally good at” feels very broad. A broad truth can be hard to build around unless it is narrowed into a specific moment, specific user, and specific decision they are struggling to make.
I’d also want to understand what “self-discovery” means in the context of this product. That term carries a lot of meanings across different domains, from career growth to therapy, meditation, and etc.
Because of that, people may project their own version of “self-discovery” onto the idea, even if that is not the problem you are trying to solve. I think it would help to give more context around the exact moment this product supports.
Thank you for such thoughtful feedback.
I agree that "self-discovery" is too broad on its own, and that's something we're actively refining as we continue validating the product.
Our vision isn't to build a general self-discovery platform or something related to therapy or meditation. The specific problem we're focused on is helping people who are facing important career and education decisions but don't have a clear understanding of their own strengths, natural abilities, or where they are most likely to thrive.
For example, someone deciding what to study, whether to switch careers, or whether they're better suited for employment or entrepreneurship. Those are the moments where we believe AI can provide structured, personalized insights that complement—not replace—real-life experience.
Your point about defining the user, the moment, and the decision is exactly the kind of feedback we're looking for while building in public. We'll definitely use it to make our positioning much clearer. Thanks again for taking the time to share it.
I think the hardest part in this space isn’t generating insights—it’s making them feel specific enough that users don’t dismiss them as generic personality advice. The value usually shows up when the system can connect patterns in behavior to concrete, testable next steps rather than abstract “potential” framing.
I completely agree. That's one of the biggest challenges we're thinking about.
Our goal isn't to generate flattering or generic personality descriptions. If users read the results and think, "This could apply to anyone," then we've failed.
We're exploring ways to make the insights much more evidence-based by explaining why a conclusion was reached, connecting it to patterns in the user's responses, and, most importantly, turning those insights into concrete next steps—whether that's exploring a specific career path, developing a particular skill, or validating an entrepreneurial direction.
Ultimately, we want the output to answer "What should I do next?" rather than simply "Who am I?"
Thanks for highlighting this—it reinforces exactly where we believe the real value needs to be.
I'm glad it resonated.
The distinction between "understanding yourself" and "knowing what to do next" is probably where these products create real value. I had a few thoughts on how that translation from insight → action could be approached, but I'd rather discuss it in the context of what you're building than reduce it to another thread comment.
What's the best email to reach you on?
Thanks, I really appreciate that.
I'd be happy to hear your thoughts. We're actively refining PotenAI, and feedback from people who have experience thinking about these problems is incredibly valuable at this stage.
You can reach us at abdullahhuseynli12@gmail.com
Looking forward to continuing the conversation!
Thanks! I’ve just sent it over.
Looking forward to hearing your thoughts whenever you have a chance.