AI Engineer Learning Path: Build First, Then Go Deep Where You Get Stuck
ashishllm · x · 2026-09-13
An AI engineer shares a project-first learning path:
- One solid portfolio project is enough to get hired; learn by building rather than taking courses.
- Top-down-depth approach: start a project (e.g., a RAG app), and when you hit confusion—like implementing the retrieval pipeline—break that part down and master it in depth.
- Then add breadth: map out retrieval types, where to apply them, and tradeoffs to build a mental model, without mastering everything at once.
- Finish like an engineer: push the full project to GitHub with CI/CD and deploy to cloud (AWS), learning only the services you need.
A quoted tweet adds a backend engineer's checklist: DBs, system design, algorithms, API design/security, CI/CD, Docker/Kubernetes, caching, and messaging.
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