Just shipped my AI app for the Flowroom contest ๐ŸŽ‰
Been building quietly for the past few weeks and finally ready to share.
I submitted SnapCaption AI to the Flowroom AI App Creation Contest โ€” and honestly, I learned way more than I expected during this build.
๐Ÿš€ What it does
You upload a photo โ†’ AI actually looks at it โ†’ and in ~10 seconds you get:
  • 3 platform-optimized captions
  • A 3-slide Instagram story
  • 30 ready-to-use hashtags
Plus 5 tone styles: Funny, Heartfelt, Poetic, Gen-Z, Professional
Works for IG, LinkedIn, Twitter.
๐Ÿง  The interesting part โ€” Vision AI
This isnโ€™t a generic caption generator.
The AI analyzes the actual image โ€” scene, lighting, mood โ€” not just keywords.
But getting this right was trickyโ€ฆ
  • It would hallucinate random stuff (โ€œmidnight vibesโ€ on a bright beach pic ๐Ÿ˜…)
  • Sometimes added irrelevant context like timestamps
  • Had to build a validation + retry layer to clean outputs
๐Ÿ› ๏ธ Stack
  • Flowroom (app infra)
  • GPT-4o Vision (image + captions)
  • Vanilla JS
  • CSS animations
Tried to make it feel like a real product, not just a demo.
๐Ÿ’ก 3 key learnings
1. Vision AI = prompt engineering gameIf your prompt isnโ€™t tight, the output drifts fast.
2. UX matters more than AILoading states, copy buttons, history โ€” spent more time here than on the model.
3. Shipping > perfectHad bugs till the last minute. Real-world fixes hit different vs sandbox builds.
๐Ÿ”— Try it
If you post content regularly, would love your feedback (especially on caption quality across different images)
Happy to answer anything about the build ๐Ÿ‘‡
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1 comment
Divyanshu Gupta
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Just shipped my AI app for the Flowroom contest ๐ŸŽ‰
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