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Say hi to my new style ππ
This is my first AI character reel!
If you want to see more videos like this,
check out my YouTube channel π Link in bio!
#AICharacter #NewSeries #PinkVibes #YouTubeChannel #FirstReel #Subscribe
youtube.com
PIXELSTORIES.AiπΌ
Welcome to my AI World πΈ Cute AI Girl | Daily Shorts | Aesthetic Vibes Watch her eat, celebrate, and be adorable π New video daily! Subscribe & turn on π
Really loving the direction here!
Thank you so much Sevkiβ¨
Iβm really glad you liked it. Working hard to improve with each reel β€οΈ
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2 voted
50%
2 voted
50%
4 votes
Closed
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Before you add AI to your product, find the screen where your users already copy and paste.
That's usually where the real AI feature lives. Not a chatbot in the corner, but a step people already do by hand: summarising a ticket, drafting a reply, tagging an upload, pulling fields out of a PDF.
Here's the order I follow when a founder asks me to add AI to an existing SaaS:
1. Pick one workflow, not "AI everywhere." Watch where users leave your app to paste something into ChatGPT and come back. That round trip is your feature.
2. Keep the model behind your own API. One service owns prompts, retries, logging and cost limits, so you can switch providers without touching the frontend.
3. Make it tenant-aware from day one. Each customer's data, prompts and usage stay scoped to their account, or the first enterprise security review will stop you.
4. Ship a draft, not a decision. Let the AI suggest and the user approve. You earn trust and get real feedback before you automate anything.
5. Measure accepted output, not tokens. If users rewrite most of what it produces, the prompt or the context is wrong, and that's your real roadmap.
Most AI features that flop didn't fail because of the model. They were bolted onto the wrong step.
What's the one task your users still copy into ChatGPT?
Watching where users paste into ChatGPT and come back is such a practical way to find the real feature. Most teams start with the chatbot instead.