Are You AI Native?
Read this, then ask yourself that question again.
Every company these days calls themselves “AI-powered”? But every so often, you hear about something “AI-native?” It hits different for me.
Wondering what that actually means? What it leads to?
AI Native is not just about using AI as a gadget bolted onto what you already do. It’s about rethinking the whole process. When you build “AI-native,” you start by mapping out your workflows. Instead of jumping straight to fancy tools or automation, you ask: What tasks do we actually do? Where does the work get tangled up? Only when you see the flow clearly, do you codify it. Then you can automate. You cannot effectively automate what you could not see previously?
Here’s where it gets even better. Instead of hopping between disconnected apps, you build specialized agents; think little digital teammates, each great at their own job. These agents handle routine tasks, linking up with dependable systems like your CRM, ERP, or financial transactions, while still letting humans review the important moments.
Less busywork, more brainwork!
Another thing, data isn’t just thrown away after each project. In the AI-native world, everything you do creates something reusable; datasets, prompt templates, playbooks, even test scripts. Imagine every client engagement leaving behind a toolkit that makes the next one faster and smarter. You’re not just creating work; you’re stacking bricks for the next round and compounding value daily if you’re doing it right.
But here’s what really sets “AI-native” apart: continuous evaluation. You don’t just ship an AI feature and move on. You treat every model or agent like living software. You will be testing it, measuring it, watching for drift, and rolling it back if needed; KPIs, test cases, the works. It’s alive, and you’re always tweaking and improving.
Now, we can all focus on outcomes.
“AI-native” is about putting AI at the heart of how you work. Not just sprinkling it on top and hoping for the best by dropping in random tooling.
Would love to hear what you think. Let me know!
Factually Yours,
Kent


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