- Build something useful in Rust, with Rust proficiency as a side-effect
- Develop competence with low-level optimization
- tooling: nonius, perf, flame graphs, some dtrace/strace
- assembly: casual familiarity reading x86, comfort with SSE/AVX and associated libraries
- hardware: learn recent microarchitectures (Haswell–) for Intel and AMD, gain empirical expertise with contemporary memory hierarchies including NVMe
- libraries: add a few C++ libraries to my trusted working set beyond Boost, focused on addressing particular performance issues (e.g., replacements for std::unordered_map, B-trees, a trie, a Bloom filter lib, etc.)
- Do everything with some set of Docker, CloudFormation, Vagrant, and Terraform
- Apply some data science/machine learning techniques to real problems
- Become dangerously inept with ReactJS and Django as a frontend/backend webapp platform
With the exception of learning how to use ReactJS with Django in order to build a simple webapp, these goals are focused on developing working expertise, building off my strengths in batch processing/backend/systems development. None of these goals involve surface-level reading about new technologies in order to gain conceptual familiarity. I've read about a lot of these technologies for years. It's high time to incorporate them into my daily development activities.
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