Most free AI tool roundups are just catalogs. A useful stack assigns each tool a clear job so you can learn faster, make better decisions, and ship more with less friction.

If I had to rebuild my AI workflow from scratch today using only free options, I would keep four layers: NotebookLM for source-grounded research, Google AI Studio for fast prompt and model checks, Gemini CLI for terminal-side execution, and Hugging Face for open-model experimentation.

NotebookLM is where serious daily AI use should start

NotebookLM remains one of the strongest free AI tools because it works from your sources rather than from vague memory.

Google AI Studio helps you fail cheaply before you build expensively

AI Studio is useful because it lets you test prompts and interaction patterns before you commit them to a workflow.

Gemini CLI matters because execution beats explanation

The reason a terminal agent matters is simple: work becomes real when it touches files, scripts, commands, and systems.

Hugging Face keeps your judgment honest

Testing open models and Spaces is not just for ML engineers. It helps you understand whether the value you are seeing comes from the model, the workflow, or the interface.

The daily sequence I recommend

• Collect sources in NotebookLM.
• Test the framing in AI Studio.
• Execute in Gemini CLI when the task touches real systems.
• Cross-check on Hugging Face when you want open-model perspective.

Sources

• Google NotebookLM Help
• NotebookLM sources guide
• Google AI for Developers pricing
• Google: Introducing Gemini CLI
• Hugging Face ZeroGPU
• Hugging Face Inference Providers

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