AI-first isn’t a feature. It’s a philosophy. It’s about building products that think with you, not just for you.
Start small. Stay curious. Design for the human, not the hype.
If you want to build something that lasts, start with the problem, not the buzzword.
Because the best kind of AI isn’t the one that shouts its presence - it’s the one that quietly makes everything better.

‍

Let’s be honest - “AI-first” has become one of those phrases everyone uses but few truly understand.
You hear it in pitch decks, product pages, and investor calls. But when you look closer, most products are still just traditional software with a chatbot glued on.

Being AI-first isn’t about adding intelligence - it’s about designing with it from day one.
It’s a shift in mindset: instead of asking, “How can we add AI here?”, you start by asking, “What could this experience look like if AI was at the core?”

AI-first products don’t just automate. They anticipate. They learn, adapt, and evolve alongside their users. They make things feel effortless - almost invisible - because intelligence is baked into the experience, not bolted on.

We’re living in an AI-saturated world. Every startup claims to be “powered by AI.”
But users aren’t impressed by that anymore - they expect it.

Think about it: people already use Gmail to finish their sentences, Spotify to personalize their playlists, and ChatGPT to brainstorm ideas. Their baseline expectation for software has changed.
They want products that feel alive - ones that understand them, not just serve them.

And investors? They’re all in. Over 70% of VC funding now goes toward AI-driven startups. The market doesn’t reward “AI somewhere in the stack” anymore - it rewards products where AI is the value.

So here’s the reality: if you’re not building AI-first, you’re building for yesterday.

When you build with AI, it’s tempting to chase the magic.
You want your product to wow people - to feel futuristic.
But here’s the truth: the best AI-first products don’t feel futuristic. They feel natural.

AI should enhance human ability, not replace it.
The moment it becomes intrusive, confusing, or “too clever,” you’ve lost the user.

That’s why design matters so much.
If the AI is truly smart, it should make life simpler - not just smarter. It should feel like the product gets you without you needing to think about how it works.

Invisible AI is the goal. When the experience feels effortless, that’s when you know you’ve built something powerful.

If you’re thinking about building (or rebuilding) an AI-first product, start here:

1. Start with the problem, not the model.
Don’t build AI for AI’s sake. Find a real user pain - something repetitive, complex, or insight-heavy - that AI can truly transform. If your product doesn’t make someone’s day easier, the tech won’t save it.

2. Go small before you go smart.
You don’t have to overhaul everything at once. Pick one feature or workflow and infuse it with intelligence. Launch it, test it, listen. A small, well-executed AI feature beats a big, broken promise every time.

3. Treat data like gold.
Your AI is only as good as the data it learns from. Invest in clean pipelines, feedback loops, and ethical collection. If the data is messy or biased, your AI will be too.

4. Design the AI experience like you’d design a conversation.
Think about tone, trust, and timing. How does your product talk to people? How does it guide them, reassure them, or get out of the way when needed? AI should feel like a guide, not a gatekeeper.

5. Always have a plan B.
AI will make mistakes. Build safety nets - let users edit, override, or opt out. Trust grows when users feel in control.

Over-promising the magic.
If you hype your AI as “revolutionary,” it better deliver. People forgive imperfection, not overconfidence. Be honest about what it can and can’t do.

Under-delivering the basics.
AI that’s slow, inaccurate, or irrelevant will lose users faster than you can say “machine learning.” Make reliability your first KPI.

Adding AI where it’s not needed.
Not every feature needs a neural network. Use AI where it adds real value - not just because it looks impressive in a demo.

Ignoring user feedback.
AI isn’t “set it and forget it.” Treat it like a living thing - keep training, refining, and learning from how people actually use it.

Overcomplicating the experience.
Sometimes, the smartest products are the simplest ones. If users have to work to understand your AI, it’s not helping them.

‍

Let’s talk about Gong - one of my favorite examples of what “AI-first” actually looks like in practice.

If you’re in sales, you know the old pain: endless calls, half-forgotten insights, deals slipping through the cracks.
Traditional CRMs could log the data, but they couldn’t see what was really happening in those conversations.

Gong changed that.
From day one, they built their product around AI’s ability to listen, analyze, and learn from real sales interactions.
Their system doesn’t just record calls - it extracts insights, tracks patterns, and surfaces what’s actually driving closed deals.

Here’s the small but powerful detail: Gong’s AI doesn’t feel like a feature. It feels like a teammate.
Sales reps don’t have to dig through data or remember every client note - Gong quietly does it for them.
The AI fades into the background, letting humans focus on connection and closing deals.

And the results? Gong hit over $300M in annual recurring revenue and helped companies like Paycor close 141% more deals using its AI-powered pipeline tools.
That’s not marketing hype - that’s real, measurable impact.

‍