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As a beginner just started to invest last year, I basically dump all my thoughts to AI to see if it can give me any surprise, which I think is basically another way of journaling.
I made this [post](https://www.reddit.com/r/ValueInvesting/comments/1q8ezhl/how_do_you_guys_use_ai_to_help_investing/) over a month ago asking about how to use AI better to help invest. I really appreciate it that a lot of people replied and many of them are very helpful. I was really inspired and generated this basic idea:
"AI shouldn't be relied upon as a \*\*source of truth\*\*; it is far more effective as a \*\*thought-verification tool\*\*. It allows you to course-correct by identifying where you're \*\*missing an obvious angle\*\*, flagging \*\*confirmation bias\*\*, and helping you visualize the \*\*risks of an investment\*\* and the full \*\*range of outcomes\*\*."(Thanks to those who replied and inspired me: CherryRoutine9397; Itchy-Commission-195; UnderstandingLess156; Erioch\_s; austincathelp; IshfaaqPeerally; Rcraft; )
As it happens, my Figma investment just 'rewarded' me with a \*\*-60% return\*\*—thanks to Figma for finally motivating me to actually build something :) . So I started thinking about digging through my old chat logs to uncover the original 'why' behind that buy.
The steps of doing it are quite simple: I searched for the keyword figma to find out all relevant conversations and asked AI to analyze them for me. But soon I realized what really matters is the trajectory of my own thoughts, not the AI’s output, after all, as a probabilistic engine, AI doesn't care about its own internal consistency. So I manually tuned several prompts to audit things like cognitive evolution, decision models, self-persuasion, bias and so on. For example, I ran a simple logic check to spot flaws in my previous models or emotion-driven assumptions. I also look at my actions through a 'Buffett lens' to see what I’m actually doing, or use a psychological framework to trace where certain preferences and biases were born.
I am quite satisfied with the results, and I still revisit these reports occasionally just to re-read and sit with the progress.
I realized this workflow might be useful to others, so I formalized it into a purely local desktop app, making it easy for anyone to plug in their own API key and get started. It ships with 3 templates I personally find fascinating, but it’s designed to be open so you can add your own prompts using the same format.
\### \*\*A few tips if you try it out:\*\*
1. \*\*Context is King:\*\* If you're importing a massive conversation history, I highly recommend using \*\*Gemini 2.5 Pro\*\*. Its massive context window allows you to feed in the entire history at once. (Our logic preserves 100% of user input while summarizing AI responses to keep the "Self-Audit" as accurate as possible).
2. \*\*Supported Sources:\*\* Currently supports one-click data exports from \*\*ChatGPT, Grok, and DeepSeek\*\*. I am still trying to figure out a good solution for Gemini as I recently moved to it.