AI Engineer Study Library

AI Engineer Roadmap Overview: From ML Foundations to RAG, Agents & Ops

Bashiri Smith · Facebook reel · 2026-10-02 · 0:45 · 9,369 views · Open on Facebook

Topics: Start Here: Roadmaps & Strategy, Retrieval-Augmented Generation (RAG), AI Agents, Tool Use & MCP · Level: beginner

Summary

Bashiri Smith briefly walks through an AI engineer roadmap he built. It covers LLMs and RAG (embeddings, vector databases, semantic search, chunking), integration with agents and orchestration (tool use, Claude Code), ops and evaluation, safety and ethics, and ML/DL foundations. He says it suits beginners and software engineers moving into AI engineering. The full roadmap is shared as a free PDF, "The AI Pivot Field Guide", which he made with Claude alongside a Trello board.

Key points

Resources mentioned

From the PDF shared here: The AI Pivot Field Guide

Open the original · 23 pages

A 2026 guide from the baswe.Ai Engineer Accelerator with three routes into AI engineering: mid-level software engineers (9 to 12 months), new grads (12 months) and non-technical domain experts who want to build agents (9 months). Its main idea is to build first. Start with LLM APIs and RAG, then agents, ops and evaluation, then safety, and leave ML math and foundations for last. It also covers job-market and salary data, portfolio and interview advice, and ends with a resource library of free and free-tier links. Pick your chapter, follow its steps in order, and use each step's 'Start here' links.

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