I'm a big fan of AI's ability to provide personalized tutoring.
So, lately, I have been using my Antigravity IDE (you can use any agentic harness) for personal learning. Things that bubble up during my daily work or just things I want to learn.
---
*Setup*
learning/
├── AGENT.md
├── CURRENT.md
├── linux-admin/
│ └── README.md
├── mcp/
│ └── README.md
├── micro-gpt/
│ └── README.md
├── postgresql/
│ ├── PROGRESS.md
│ └── README.md
└── rag-v2/
└── README.md
- AGENT.md: agent's role, my learning preferences and goals, instructions about different chores: sequence of files to explore and log things to- CURRENT.md: current topic's directory path
- README.md: topic's learning goals, concepts I want to master
- PROGRESS.md: generated and edited by the agent on the fly
---
This is ACTIVE learning. As opposed to what Karpathy's LLM Wiki or any personal knowledge base does.
The learner undergoes 15-20 minutes learning sprints, tries things hands-on, asks to take notes, goes down the rabbit hole and agent tutor keeps the learning contextual and personal.
I have had an excellent experience with this setup so far.
Anyone doing this or anything similar?
I think this has been my biggest hurdle with LLM-based learning, even though I think the concept may be quite powerful...
Happy to hear more about your approach :)