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I am a scientist with no coding background. I built the portfolio tracker I wanted.

A materials scientist with a PhD and almost no coding background built and shipped a live stock portfolio tracker over about three months and 277 commits, pasting code blocks the AI gave him into a terminal and pasting the results back. The tracker is not about returns: it makes him write down why he bought a stock and what would prove him wrong, then pressure tests his reasoning and scores how well his past calls held up.

How it works

  1. Describe the tracker to the AI and get code blocks to paste into a terminal
  2. Paste the output back and repeat, for about three months and 277 commits
  3. Build the app on a self hosted database and hosting stack
  4. Add the pressure test that argues against his reasons and scores his old calls
  5. Use it live on his own portfolio

Why it’s worth knowing

He cannot read most of the code. He reads the behavior, like an experiment, and catches the agent that way.

Where it’s from

Summarized from a public post on reddit.com. See the original ↗

Upgraded prompt

A ready-to-use prompt for this idea, built from research on what makes AI agents do the job right: who the AI should be, the exact steps, and a check to make sure it was done the way you wanted.

1Who the AI should be
2The prompt, with the steps
3The check when it’s done
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Try next

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Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.