I had a fairly easy tech job, making well over 6-figures. However, every time I went to work, I was never happy. Not due to the amount of stress on projects or relationships with coworkers - but, the idea of knowing I could be making much more efficient use of my time and potential. For the past 2 years, I got deep into swing trading (on the side). I quickly realized that there’s a ton of obstacles I had to cross along the way in order to be consistently profitable. For example, coding up all the indicators I wanted to implement, or even automating my strategies entirely was wayy harder than asking gpt to walk me through it. I used my network to find solutions, and understood that most people in the community don’t know how to code, and if so, it is extremely complicated to use or on the contrary, too much “drag and drop” (meaning that it’s not customizable/flexible enough). Almost a year ago, I created a tool to solve my problem. The more I worked on it, and shared it to my shared groups/community , the more the tool gained interest. After tons of recommendations and criticism, the tool evolved into a platform. After releasing a close group beta (capped at 100 ppl), I saw the traction and understood the validity of what I was building. I saw the potential and put more time in. This time, I was getting 2 hours in before work and putting extra hours in after work (ultimately adding up to 25 extra hours of work a week + the 25 going in at the time) - then having to clock in from 8-5. I was completely obssesed, and thought about doing something unique and helpful in the community: implementing AI insights, exporting of strategies, even having a marketplace for people who want to share their own strategies and get paid off commission. Fast forward to now, over 1.5k users signed up, and it’s gaining real traction as a FinTech startup. And yeah, I understand it’s pre-revenue and I “shouldn’t” leave my comfy job because of how things are this time around. But the truth is, I know I have to take this risk at the age I am, having no real responsibilities in life except having to take care of my parents.

I've been helping dental practices automate patient communication, and the biggest bottleneck was initial outreach. Manually emailing 50+ clinics a day wasn't scalable, but mass email tools got me blocked or landed in spam. So I built this workflow in n8n that reads a Google Sheet of clinic contacts, personalizes each email based on their data, and sends them one by one with proper delays between each send. It feels human because it actually waits between emails like a person would. Here's the full breakdown: Manual Trigger Node This is just the start button. When I'm ready to run the campaign, I click execute and the whole thing kicks off. Nothing fancy here, just a clean way to control when emails go out. Google Sheets Connection Setup This node initializes the connection to my Google Sheet where all the clinic data lives. It's basically telling the workflow which spreadsheet to read from and which columns to pull. I keep Email, FirstName, Organization, Website, and Icebreaker columns in there. Google Sheets Reader This pulls all the rows from the sheet. Every clinic contact becomes a data point the workflow can use. It's connected to my actual Google account using OAuth so it has permission to read the data. Process Email Data This is where the magic happens. It loops through every row, grabs the relevant fields, checks if there's a valid email address, and packages everything into a clean data structure. It also counts how many total emails will be sent so I can track progress. If someone doesn't have an email or it's malformed, they get skipped automatically. Split Into Batches This node processes one contact at a time. Instead of blasting 100 emails at once, it queues them up and releases them one by one. This is critical for avoiding spam flags and staying within email provider limits. Send Email The actual email goes out here. I'm using a custom SMTP connection through my business email so it comes from a real domain. The subject line and body pull from the data fields, so each email is personalized with the recipient's name and clinic name. No generic mass email language.