Don’t Automate the Whole Job—Automate the Friction
One of the biggest mindset shifts is to stop thinking of AI as some futuristic magic that will automate your entire role. That’s not the goal. Instead, look for friction points—those small, repetitive, mentally draining tasks that interrupt your flow. These are perfect opportunities for AI assistance.
I often use AI tools to:
Draft first versions of emails, blog posts, or training outlines
Clean up messy meeting transcripts
Translate abstract ideas into user stories or test scenarios
Simulate difficult conversations to practice my responses
Each of these examples removes a little bit of friction. The result? I stay in flow longer and finish the day with more energy.
Talk to the AI Like You Talk to a Colleague
This surprises people: I don’t use AI as a search engine. I use it as a thinking partner. I don’t just say, “Give me a summary of X.” I say things like:
“Here are rough thoughts I am having on this topic. I want to turn this into a blog post. Can you clean it up and preserve my tone?”
Or:
“I'm preparing a talk to help senior developers become team leads. Here's my outline so far. What’s missing?”
That shift—from seeing AI as a tool to seeing it as a collaborator—unlocks a different level of value. And it doesn’t require any fancy integrations or coding skills. Just clarity and intent.
The Basics Are Already Enough
You don’t need to dive into machine learning models or prompt engineering to start getting results. Here are three basic techniques that already make a big difference:
Voice Journaling: Speak your thoughts out loud and let AI transcribe and organize them. Great for capturing ideas on the go or debriefing after a long meeting.
Drafting, Not Finalizing: Let AI write your first draft—of a slide deck, a user story, a customer email. Then you refine it.
Compare and Contrast: Ask AI to play devil’s advocate or generate alternative viewpoints. This is especially helpful in decision-making or design reviews.
These are low-risk, high-reward use cases. Start small, iterate, and soon you’ll find new ways to integrate AI into your daily rhythm.
But... Don’t Blindly Trust It
AI is good. It’s fast. But it’s not wise. It doesn’t know your domain, your context, or your users like you do. You still need to validate, rephrase, and refine its output.
Think of it like pair programming: the AI might write the first line, but you’re still the senior engineer reviewing the commit.
I’ve seen people waste time cleaning up bad AI output because they didn’t frame their request well. Or worse, they trusted the answer without understanding the problem. It’s your job to steer.
Final Thought: You’re Not Behind
If you're just starting, that’s OK. You’re not behind. Many people are still figuring out what AI means for them. The key is to start now—not by learning everything, but by trying something.
Pick one use case in your daily routine that feels annoying or repetitive. See if AI can help with that. Build from there.
This isn’t about chasing a trend. It’s about making work life easier, more focused, and more human—by letting the machines handle the stuff they’re good at. Have questions or want help getting started? Reach out to us. We’d love to hear how you’re exploring AI in your work.
