Things I want to learn

2026:

• ✅ Agentic AI / OpenAI Codex, Claude Code, Gemini CLI, etc.
• Bike repair: How to change tires, fix breaks, adjust gear system, etc.
• Skating; Ice Skating of just rollerblades

2025:

• Answer Engine Optimization (AEO). AEO is like Search Engine Optimization (SEO) but aimed at AI assistants, chatbots, and voice search systems that give direct answers instead of just a list of links.
• Carpentry and woodworking

2022:

• ✅ Apache Spark / PySpark. At a certain scale, data doesn't fit in memory anymore, and one needs to learn to use Spark to build their machine learning solutions at scale.
• Non-fiction Writing I want to learn how to write engaging non-fiction. Some authors have a certain rhythm and their words sound like poetry. Some authors know how to incorporate elements of fiction, a la storytelling, into non-fiction.

2021:

• Ethereum Development. My motivation: There is a chance that crypto is the next big thing after the internet and AI. Maybe it is time to learn about smart contracts and crypto development. I am listing Ethereum here since it is the most popular, think market cap, but I am open to learning other protocols such as Polkadot, Solana, Algorand, Elrond, Waves, etc. I'd do some research, but pick the one with cleaner documentation to avoid any analysis paralysis.
• Clustering Ensembles and Subspace Clustering. My motivation: When clustering high dimensional data, we have to apply some dimensionality reduction first or else the clustering algorithm will not work. I was thinking, why not iteratively pick some random dimensions, apply clustering algorithms using those feature subsets, and apply another layer of clustering on those clustering outputs. Then I stumbled upon the Clustering Ensembles and the Subspace Clustering concepts.
• Neural Search. My motivation: Not sure about this one. Just listing it here. Probably will only learn it once I need it; otherwise, I will skip it.

Tarek Amr - Jan 24, 2026