1 Developer Tools Fundamentals

Chapter 1 has one job: make sure you can create code, run code, save code, and explain how to rerun it.

See The Workstation

Read the picture first. The whole chapter is this loop:

terminal→project folder→Python environment→editor/notebook→Git history

Do not try to master every tool now. Build one stable workstation, then reuse it in later AI projects.

Learning Order And Task List

Use this sequence as both the guide and the task list.

1. 1.1.1 Terminal and command line: run pwd, ls, and cd; keep a short command log.
2. 1.1.2 Basic terminal operations: create, move, inspect, and remove files; keep a folder screenshot or terminal output.
3. 1.1.3 Package managers: check how your system installs tools; keep tool version notes.
4. 1.2.1 Git basics and 1.2.2 Git core operations: save a first local project snapshot; keep one clean Git commit.
5. 1.3.1 Python environment, 1.3.2 VS Code, and 1.3.3 Jupyter: run Python in the right environment, edit code, and restart-run a notebook.
6. 1.4.1 Follow-along workshop: combine terminal, Python, editor, notebook, and Git into a reproducible ai-learning-lab README.
7. 1.4.2 AI Coding Agent Workflow: turn a coding request into scope, permission, test, evidence, and review gates before letting an Agent edit.

The workshops stay at the end because they are integration steps: learn the pieces first, then connect them with reproducible evidence.

First Runnable Loop

Run this in a practice folder. It creates a tiny project, runs it, documents it, and commits it.

mkdir ai-learning-lab
cd ai-learning-lab
python -m venv .venv
. .venv/bin/activate
python -c "import sys; print(sys.executable)"
printf '.venv/\n__pycache__/\n' > .gitignore
printf 'print("AI learning lab is ready")\n' > hello_ai.py
printf '# AI Learning Lab\n\nActivate env: . .venv/bin/activate\nRun with: python hello_ai.py\n' > README.md
python hello_ai.py
git init
git add .gitignore README.md hello_ai.py
git commit -m "init learning lab"

Expected output:

AI learning lab is ready

If the command fails, do not erase the error. Save the command, full output, operating system, Python version, and current directory. That record is useful project evidence.

On Windows PowerShell, use .venv\Scripts\Activate.ps1 instead of . .venv/bin/activate. If your system uses python3, replace python with python3 consistently in the commands and README.

How to read this output

• AI learning lab is ready proves the script ran inside the project folder.
• python -c "import sys; print(sys.executable)" proves which interpreter is actually running.
• The Git commit proves the project can be saved and reviewed later.
• If any command fails, the command plus the full error output is evidence, not noise.

Depth Ladder

Level	What you can prove
Minimum pass	You can create a folder, run a script, and identify the current directory and Python interpreter.
Project-ready	A fresh terminal can follow your README, .venv/ is ignored, and git status only shows intentional changes.
Deeper check	You can explain why PATH, working directory, shell, and interpreter choice change results across machines.

Evidence to Keep

Keep this page’s proof of learning as a small evidence card:

Workspace

terminal, Git repo, editor, Python environment, and notebook all verified

Artifact

small command log, commit history, script output, or notebook cell result

Debug Note

one setup problem and how you diagnosed it

Failure Check

path confusion, environment mismatch, Git state, or missing dependency

Expected Output

a ready-to-learn workstation evidence pack

Common Failures

Symptom	First thing to check	Usual fix
Command not found	Is the tool installed and available in PATH?	Reopen the terminal or reinstall the tool
Python import fails	Are python and pip from the same environment?	Install with python -m pip install ...
File not found	Are you in the correct directory?	Run pwd and ls, then move to the project folder
Git commit fails	Is Git initialized, staged, and configured?	Run git status and set username/email if needed
README command fails	Did the README include every required step?	Test from a fresh terminal and update the README

Pass Check

Move to Chapter 2 when you can answer these five questions:

• Which directory is the terminal using?
• Which Python interpreter is running your script?
• What changed since the last Git commit?
• What command reruns the project from a fresh terminal?
• Where did you record your first error and fix?

Check reasoning and explanation

1. The terminal directory is the folder shown by pwd; it should be the project root or the folder named in your command.
2. The Python interpreter is the path returned by which python or python -c "import sys; print(sys.executable)"; it should match your course environment.
3. Git changes are checked with git status --short and explained with git diff before commit.
4. A fresh rerun command should include environment activation, an install/check step if needed, and the exact script command.
5. The error record is acceptable when it includes symptom, command, likely cause, and fix. A screenshot alone is not enough.

The goal is not tool perfection. The goal is a workstation stable enough for the rest of the course.