Software Engineering Fundamentals Before AI Engineering

Bashiri Smith · Facebook reel · 2026-09-18 · 0:49 · 3,494 views · Open on Facebook

Topics: Programming & ML Foundations, Resume, Job Search & Interviews, Start Here: Roadmaps & Strategy · Level: beginner

Summary

Bashiri Smith says many people struggle to become AI engineers because their software engineering skills are weak. Calling an LLM API is not enough. You also need to handle failures, debug the backend and deploy reliable systems. His advice is to stop copying tutorials, learn the fundamentals, build real projects that companies care about, and then apply those skills to AI.

Key points

• Claim: he helped 3 engineers land over $500,000 in combined salary in 30 days, using the advice below.
• Spend much more time on software engineering basics than you think you need. Weak software engineers become weak AI engineers.
• Two common traps: getting stuck in a current job without growing, or spending months copying tutorials instead of building.
• Build real projects that solve problems companies care about. Following someone else's code is not enough.
• Connecting an LLM to your app does not show you can handle failures, debug a backend, or deploy something people can rely on.
• These skills still matter when 'AI' is added to the job title. Don't skip the foundations just because AI engineering is popular.
• Suggested order: master the fundamentals, build real things, then apply those skills to AI.

Resources mentioned

• BASWE.Ai Engineer (Skool community) · community · skool.com · paid
  The creator's paid community and program, with an AI learning roadmap (including the full ops and evaluation track), daily calls with engineers and recruiters, resume and portfolio help, and a job-search pipeline.
  Also in: Basic RAG Pipeline in 60 Seconds: From Documents to Grounded Answers (Bashiri Smith on Facebook · notes), Pointer to Bashiri Smith's Complete AI Engineer Roadmap for 2026 (Bashiri Smith on Facebook · notes), Step-by-Step Roadmap to a $200K+ AI Engineering Role (Bashiri Smith on Facebook · notes), How to Evaluate a RAG Pipeline: Retrieval vs. Generation (Interview Answer) (Bashiri Smith on Facebook · notes) and 76 more

Try this

• Spend more time on software engineering fundamentals before focusing on AI.
• Stop copying tutorials. Build your own projects that solve problems companies care about.
• Learn to handle failures, debug backends and deploy reliable systems, beyond just calling an LLM API.
• Once you have the fundamentals and real projects, apply those skills to AI engineering.