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[AI Meeting Copilot] Provide better feedback on clarity during technical interviews

The user shifted focus from generating smart questions to analyzing structure and clarity in responses during technical interviews, indicating a need for better feedback mechanisms.

Original Source

@u/ai-meets | 1 pts | 3/3/2026

&#x200B; I’m building a small SaaS that simulates technical interviews and meeting pressure for software engineers. Initially I thought the value would be: “AI asks questions.” That turned out to be the easy part. The real challenge (and insight) was this: Engineers don’t struggle with knowledge. They struggle with structuring answers under pressure. When I started testing with early users, I noticed: – They knew the concepts – They had real project experience – But their explanations collapsed when interrupted What surprised me most: Users didn’t want more questions. They wanted better feedback on clarity. So we shifted focus from: “Generate smart questions” To: “Analyze structure, hesitation, and trade-offs.” Early takeaway for me: In interview prep, perceived clarity > technical depth. Still validating positioning and pricing. Curious for other SaaS founders here When did you realize your initial value proposition wasn’t the real one?

Discussion

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