There are many manifestations of Artificial Intelligence. Large Language Models being one of these.
Large Language Models (LLMs) produce human like conversation and can quickly estimate what words to respond with given a query.
A LLM Agent will search for specific markdown files in a project directory. It will use the information therein to guide it as to the user's prefeences of framework structure, coding standards and what it can and cannot do.
There is also a project synopsis, quite often, that keeps track of what the project goals are and what has been dicovered so far. This is needed due to the fact that an LLM has a limited memory to keep track of everything that is critical to the project.
AGENTS.md Boilerplate
# AGENTS.md
## Project Overview
Brief description of what this project is and its goals.
## Architecture
Key components, folder structure, and how they relate.
## Commands
- `build`: how to build
- `test`: how to run tests
- `lint`: linting command
## Conventions
- Language/framework versions
- Code style rules
- Naming conventions
## Agent Instructions
- What agents should and shouldn't modify
- Where to find context (e.g., docs/, specs/)
- Any sensitive areas to avoid