Ayush Vijayvargia

Most language tools focus on beginners, targeting work-call fluency for non-native professionals is a much more specific and valuable niche. How does it handle industry-specific jargon? Someone on a finance call uses very different vocabulary than someone in engineering. Does it adapt to the user's professional context?

The Duolingo-meets-Wikipedia comparison is intriguing. Duolingo's magic is the dopamine loop, do you folks replicate that kind of micro-reward structure, or is the engagement more content-driven? Also curious about accuracy with generative content, how do you prevent hallucinated facts from being taught as truth, especially in fields like history or science where precision matters?

Smart idea combining flashcards with DSA patterns most people grind Leetcode problems without building pattern recognition. Do the cards focus on recognizing which pattern to apply to a new problem, or more on memorizing specific solutions? The former would be way more valuable for interviews where you get problems you've never seen before.

The audio-to-flashcard pipeline is clever, most students record lectures but never revisit them. Curious how it handles heavy accent variations or technical jargon in recordings? For something like a grad-level math lecture with a lot of notation spoken aloud, does it capture the formulas accurately or does it need manual cleanup?