Why we're building PotenAI with adaptive AI instead of static assessments
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Most career/personality tools follow the same pattern: fixed questions → fixed scoring → fixed report. It's efficient to build, but it treats every user like they fit into 16 boxes. We wanted something closer to how a good mentor actually works — asking follow-up questions based on what you just said, probing deeper on ambiguous answers, adjusting the whole assessment path in real time. So we're building PotenAI on adaptive AI conversations instead of static forms. The technical challenge has…
1Key Takeaways
- Most career/personality tools follow the same pattern: fixed questions → fixed scoring → fixed report.
- It's efficient to build, but it treats every user like they fit into 16 boxes.
- We wanted something closer to how a good mentor actually works — asking follow-up questions based on what you just said, probing deeper on ambiguous answers, adjusting the whole assessment path in real time.
- So we're building PotenAI on adaptive AI conversations instead of static forms.
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — AI reports that most career/personality tools follow the same pattern: fixed questions → fixed scoring → fixed report.
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