It is now the 7th of May, and somehow my second day of learning AI has turned into an unexpected experiment about time, self-awareness, and priorities. Today’s project was something surprisingly personal: a 2026 Time Expenses Record . The idea is simple. Treat time the same way people treat money. Every hour spent is an expense. *** Building a “Time Expenses” System I started recording where my time actually goes: work church meeting friends appointments commuting studying for the PTE test any activity that consumes at least 30 minutes to an hour The interesting part is not the tracking itself. The interesting part is how AI helped me automate it. I connected Codex to: Google Calendar Google Sheets Then Codex generated a Google Sheet that extracted data directly from my calendar. What surprised me most was not the automation itself, but how collaborative the process became. I was not simply pressing buttons and receiving outputs. I had to: clean the extracted ...
After several inconsistent attempts over the past six months, I have returned to trading with a more deliberate approach. Today marks the first day of recommitting to the process. Session Context I opened NinjaTrader and traded on simulation. Initially, I experienced some hesitation while reviewing the charts, as I struggled to recall my prior notes and frameworks. However, after spending a few minutes observing price action, I began recognizing familiar structures. The market appeared to be in a choppy condition , which I confirmed by comparing it with the previous day’s price behavior. Trade 1 Setup: Predefined with Fibonacci tool Context: Choppy market Action: Entered trade quickly Result: + $160 I later validated my interpretation of the market condition, confirming that identifying the chop was correct. This reinforced confidence in my read. Post-Trade Observation Shortly after, price broke below my Fibonacci retracement level. Based on this, I decided to pause ...