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How to Sell Your AI Product in 2026
Every founder has an AI feature now. Buyers have heard "AI-powered" so many times that it's background noise.
So how do you sell?
1. Sell the outcome, not the AI.
Nobody buys "an AI agent for finance teams." They buy "close the books 3 days faster." Put the result in your headline and move the AI to the second line.
2. Show it working in under 60 seconds.
Buyers are skeptical. A short screen recording of one real task, start to finish, beats a 10-slide deck. If you can't show it quickly, they won't believe it.
3. Answer the trust question before they ask.
Where does my data go? What happens when it's wrong? Who checks the output? Put these answers on your site and in your posts, and you remove the biggest reason deals stall.
4. Prove it with one specific number.
"Saves time" means nothing. "Cut approval time from 5 days to 1" gets remembered. Collect a number from every early customer, even a small one.
5. Let the founder be the face.
When ten tools look the same, people buy from the founder they trust. Show up on LinkedIn with real stories: a customer problem, a failed experiment, a lesson. That builds trust before your sales call.
6. Make the next step easy.
A free audit, a 2-minute demo, a pilot for one team. Nobody signs a big contract with an AI tool they haven't tried.
I'm Maryam, and I ghost-write LinkedIn content for SaaS founders, so your product's story gets seen before your competitors' does. If you want 3 post ideas based on your own product, DM me "STORY" on Contra. They're free.
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I see a lot of founders add AI to give people a reason to use a feature. I don't think it works.
It usually ships before anyone decides which manual work the AI should take away. So it lands in a chat or a separate screen, and people can't see why it suggested what it did.
If they don't act on it, the feature the business case rests on goes unused, and fixing it means paying the team twice.
AI is leverage when it takes manual work out of a step people already do.
Before you build it, I like to ask:
→ Which part of the step is manual work, and which part is a decision?
→ Where do people already do that step?
→ What does the AI show so people can check it?
On a fintech platform's CSV import, Auto-match fills every column that fits one field, right in the mapping table. A column that fits two fields is a decision, so the person opens the cell and picks the "Best fit" field. Then they press Confirm.
When AI takes the manual work out of the step, people are more likely to act on it and get their data in.
SpaceX and Salesforce both renamed AI products this month, and neither of them picked the timing.
On September 29 a federal order told government agencies to say "super intelligence" instead of "artificial intelligence." It doesn't apply to private companies. Within twelve days SpaceXAI was becoming SpaceXSI and Salesforce's AIForce was SIForce anyway.
I'm staying out of the politics. The brand side is what I keep thinking about. If a word in your name came from somewhere else, whoever controls that word controls when you rebrand.
Meanwhile Intuit did a big AI push this year and called it Intuit Intelligence, on a name it already owns. Calendly grew into a platform with AI features and stayed Calendly. Pleo moved into mid-market spend and kept its name and its pink.
None of them has anything to change this week.
If you want trend words in your copy, put them in the descriptor line. That takes an afternoon to change. Your company name takes a year.
I wrote this week's BRIGHT Method about it, with a quick test you can run on your own name and deck.
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🚀 New project added to my Contra portfolio - Dynamiq AI!
I’ve just added Dynamiq AI to my portfolio, a project in the AI space that gave me another opportunity to explore the intersection of technology, product design, and user experience.
When designing digital products, I believe the goal goes beyond creating an attractive interface. It’s about making complex ideas easier to understand, helping users navigate the experience intuitively, and presenting information in a way that feels clear and purposeful.
🤖 What makes the product interesting:
→ Building AI agents and automating complex workflows
→ Connecting AI to business tools, knowledge bases, and data
→ Managing AI agents with security controls and human approvals
→ Monitoring performance and evaluating results
These are the kinds of challenges that make product design exciting for me — turning complex functionality into experiences that feel simple and natural to use.
✨ Always happy to explore new ideas, experiment with different approaches, and share more of my work along the way.
🔗 Check out Dynamiq AI: https://www.getdynamiq.ai/
The interviews with engineers and compliance reviewers caught my attention. What did the reviewers need to see before approving an agent action, and how did that change the approval screen?