The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
Your business knowledge can now answer customers for you.
I build AI assistants that pull from your own information, so replies stay accurate and on-brand.
When something needs your attention, I set it up to alert you on Telegram straight away.
It’s a simple way to save time without losing control.
What would you want your assistant to handle first?
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
Just posted a new case study on Contra.
A 60-second promo for Ulta AI by Ultahost, a chatbot that runs a server through plain conversation. Script, storyboard and animation, all built around the real product UI.
Check it out
Let me know what you think💭😍
I'm building MorningAI — an AI automation platform designed to help businesses save time and work smarter.
I'm deciding on the website's visual direction, and I'd love your opinion!
🅰️ Design A: Light, clean & professional
🅱️ Design B: Dark, futuristic & premium
Which design should I choose for MorningAI — A or B?
Drop your choice in the comments! 👇
4 voted
57%
3 voted
43%
7 votes
Closed
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.
