An AI model must read specific files at the start of every work session. These files contain important rules and past lessons. Reading these files prevents repeating expensive mistakes.
By Pawan Nayar · from the LLOS AI Learning record
An AI model must read specific files at the start of every work session.
These files contain important rules and past lessons. Reading these files prevents repeating expensive mistakes.
An AI model must read `mistakes_and_lessons.md` first. This file contains rules learned from past problems. Each rule in this file saved a lot of time. Not reading this file means the AI model will likely repeat old errors. The AI model should also read other files that contain rules. These rules change how the AI model usually works. Not reading these files causes the AI model to make costly mistakes again.
A developer starts a new project with an AI model. The AI model begins to write code without first reading `mistakes_and_lessons.md`. The AI model then makes a common error that was already documented in that file. The developer must spend extra time to fix this error. This delay could have been avoided if the AI model had read the file.
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An AI model must always read a specific set of files. These files include 'mistakes_and_lessons.md'.
A developer should not create new ways to do things. The existing process works well.
An AI model must state the full path every time it creates or changes a file. The AI model must list all full paths at the end of a conversation.
An AI model can generate a large glossary by using a multi-pass data pipeline. Each pass focuses on different content.
An AI model must read specific files at the start of every work session. These files contain important rules and past lessons. Reading these files prevents repeating expensive mistakes.