42 student pivoting into AI engineering and agentic systems. I study how to make model-driven systems dependable: tool use, state, checks, and what happens when things go wrong.
- Agentic AI (learning track) — prompts + tools, memory/state patterns, evals, safety and reliability basics
- Systems (42) — C/C++, parsing, processes, concurrency, networking, containers
- Shipping quality — readable structure, reproducible builds, honest READMEs
| Area | Projects |
|---|---|
| Shell & processes | minishell |
| Concurrency | philosophers |
| DevOps / infra | inception, Born2beRoot |
| Networking | NetPractice |
| Graphics | cub3d |
| Capstone | ft_transcendence |
Solid “foundation” work that backs the rest: libft, ft_printf, get_next_line, push_swap, so_long.
- Going deeper on agent reliability (verification, fallbacks, testing, guardrails).
Note: Live “GitHub stats” image cards (e.g.
github-readme-statson Vercel) often break in profiles because GitHub’s image proxy times them out. The badges above stay reliable; for deep stats, open my repositories.
ebella — 42 student