I quit this week.

Welcome to Gratitude Driven, a weekly newsletter where I share practical ideas and insights across personal growth, professional development, and the world of AI and data science.

In This Newsletter

• Knowing When to Quit

• Make Your ML/Data Science Resume Suck Less

Knowing When to Quit

Followers of my content know that one of my "things" is having a lot going on at one time. This is something I generally enjoy, and I'm usually pretty good at (not to pat myself on the back too much).

But this week, I had to quit something important to me.

A few months ago I started working on a passion project: An AI app to help groups decide travel plans. It's gone well overall, and I learned a ton. But ultimately, finishing the project was dragging, and I was increasingly aware of how completing the project would lead to even more work (marketing, dealing with bugs, etc.)

I have known this since I started the project, but I've been stubborn. I think I can do it all.

And truthfully, I CAN do it all. Technically.

But the quality of everything will suffer. I'm distracted at my 9-5, I skipped the gym to work on this, and it was taking time away from leveling up my content creation.

So, I quit. It makes my skin crawl to leave a project 90% complete, but ultimately, there was no other choice.

When you're facing moments like this, here are some questions to ask yourself to gain some clarity on the situation:

What's the real cost of continuing? Look beyond time—consider your energy, relationships, and performance in other areas.

What would you gain by stopping? Focus and attention are finite resources. What could you accomplish if you redirected that mental bandwidth elsewhere?

Are you continuing out of progress or pride? Be honest about whether you're pushing forward because it's truly worth it, or because you can't stand the idea of "wasting" what you've already invested.

What does success actually look like? Sometimes we get so caught up in finishing that we forget to evaluate whether the end result aligns with our current goals and priorities.

What would you tell a friend in this situation? 

For me, the hardest part isn't making the decision to quit. It's living with the discomfort of an unfinished project and trusting that you made the right choice. But that's ok — discomfort is a necessary part of life, and part of growth.

Make Your ML/Data Science Resume Suck Less

This week's content was about improving your resume for AI/ML and Data Science roles. I go over what to include, format, selling your skills, and show a bad resume -> good resume makeover.

Hopefully this helps you get some more interviews!

Read the blog version here.

Want to chat 1:1? Book time with me here.

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