3 AI Portfolio Projects That Get Past the 6-Second Resume Scan

Bashiri Smith · Facebook reel · 2026-09-22 · 0:12 · 85,252 views · Open on Facebook

Topics: Portfolio Projects, Resume, Job Search & Interviews, AI System Design & Architecture · Level: intermediate

Summary

Most AI projects on resumes get skipped because they're basic demos like a chatbot over a single PDF. The creator suggests three production-style projects instead: a hybrid-search RAG pipeline, a multi-agent orchestration system, and an LLM gateway with fallback routing. Each one tackles a real problem AI teams face, and if you document it well you'll have enough to talk about for a 45-minute interview. Note: the spoken transcript is just unrelated background audio, so everything here comes from the caption.

Key points

• Recruiters skip most AI resume projects in about 6 seconds. Single-PDF chatbots and single-agent demos are too common to stand out.
• Project 1, RAG with hybrid search: combine dense vectors with BM25 keyword search, add reranking, and check citations. This tackles retrieval quality, which is what actually breaks in production.
• Project 2, agent orchestration: a supervisor agent, tool use, persistent memory, and handing off to a human when needed. This shows you can design the multi-agent systems teams are shipping now.
• Project 3, LLM gateway with fallback routing: per-team budgets, rate limits, circuit breakers, and switching to another provider when one fails. This is infrastructure engineering applied to AI.
• The LLM gateway lets software engineers reuse the experience they already have in an area where AI teams are short on people.
• Documenting the project matters as much as building it. The goal is one project you can discuss in depth for 45 minutes without running out of things to say.
• These are 3 of the 27 projects in the creator's guide. The guide covers the architecture, build steps phase by phase, interview talking points, and the stack for each project.

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
• Bashiri Smith's AI Projects Guide · pdf · drive.google.com · free
  The creator's guide to 27 AI projects, with full architecture, build steps phase by phase, interview talking points, and the stack for each project.
  Also in: 6-Step Framework for Building AI Projects Target Companies Care About (Bashiri Smith on Facebook · notes), Generate Job-Worthy AI Project Ideas from Recent Research Papers + ChatGPT (Bashiri Smith on Facebook · notes), 15 Production-Grade AI Projects to Go from Software Engineer to AI Engineer (Bashiri Smith on Facebook · notes), 5 Weekend AI Engineering Projects: Cost Routing, Caching, Evals & Observability (Bashiri Smith on Facebook · notes) and 3 more

Try this

• Pick one of the three projects and build it to production quality instead of making a simple demo.
• Document the architecture and your design decisions so you can talk about the project for 45 minutes in an interview.
• Check the slides for the full tech stack of each project.
• Optional: join the BASWE community if you want a roadmap and daily calls while you build.
• RAG pipeline with hybrid search: dense vectors + BM25 + reranking + verified citations
• Agent orchestration system: supervisor agent, tool use, persistent memory, handing off to a human when needed
• LLM gateway with fallback routing: per-team budgets, rate limits, circuit breakers, switching providers on failure