Problem Solving Over Keywords: The AI Skill That Never Expires

Bashiri Smith · Facebook reel · 2026-09-24 · 1:50 · 19,555 views · Open on Facebook

Topics: Resume, Job Search & Interviews, Portfolio Projects, Industry Trends & Job Market · Level: beginner

Summary

The video starts with a clip of Yann LeCun. He says to learn things with a long shelf life and to build the ability to learn quickly, because technology changes too fast to keep up with. Bashiri Smith argues the skill that lasts is problem solving: finding a real issue and building a solution people use. He says resumes full of AI keywords like RAG, LLMs and agents no longer stand out in a crowded job market. Resumes that show problems, solutions and real users do.

Key points

• Yann LeCun's advice: learn things with a long shelf life, and learn how to learn, because technology changes very fast.
• No engineer can keep up with every new AI tool, so focus on the skill that never goes away: problem solving.
• Problem solving here does not mean LeetCode grinding or debugging AI-generated code. It means finding a real issue and solving it.
• RAG, LLMs and agents are still worth learning, but treat them as tools for solving problems, not the goal.
• Resumes that are just lists of AI keywords ('ATS slop') don't stand out to companies sorting through many candidates.
• A strong resume follows this pattern: the problem you found, the solution you built, and who uses it (e.g. 'built XYZ for this person, has 10,000 users').
• A few years ago, knowing React, Node or Next.js was enough to get $100k–$200k jobs. Today there is much more competition, so proof of impact matters more.

Resources mentioned

• Yann LeCun · person · yann.lecun.com · free
  AI researcher and deep learning pioneer whose advice on learning skills that last opens the video.
• 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
• React · tool · react.dev · free
  JavaScript library for building user interfaces.
• Node.js · tool · nodejs.org · free · recommended by both Bashiri Smith & Melvin Vivas
  A JavaScript runtime that comes preinstalled on Droplets created by the plugin.
  Also in: Run Codex in the Cloud: Spin Up DigitalOcean Droplets with the Codex Plugin (Melvin Vivas on X · notes)
• Next.js · tool · nextjs.org · free · recommended by both Bashiri Smith & Melvin Vivas
  Open-source React framework for building full-stack web apps.
  Also in: Is Indie Hacking Dead? How AI Coding Changes the Micro-SaaS Playbook (Melvin Vivas on X · notes), Building and Deploying a Full App with the Codex App, MCP Servers and Skills (Melvin Vivas on X · notes)

Try this

• Prioritize skills with a long shelf life and practice learning new things quickly, instead of chasing every new tool.
• Treat RAG, LLMs and agents as tools for solving real problems, not as keywords to collect.
• Rewrite your resume around problems you found, solutions you built, and who uses them (with numbers, e.g. user counts).
• Remove keyword-stuffed 'ATS slop' from your resume.
• Optional: comment 'solve' to get the link to the creator's community.
• Find a real problem someone has, build an AI-powered solution for it, and get real users, so you can list problem, solution and user count on your resume.