Georgia State University — J. Mack Robinson College of Business PATH — Pathways for AI Training & Hiring CIS 4394 Agentic AI  ·  Fall 2026  ·  Dr. Xinyu Fu
CIS 4394 · Week 2 ⌂ Course 00Prep 01Unpack Codex 02Claude Code 03Build 04Evaluate
Week 2 · Learning from the best

Unpacking coding agents — then building your own.

Reverse-engineer Codex. Discover that the same architecture explains Claude Code. Then transfer the pattern into a completely different domain: a Job Search Agent that thinks before it acts.

CourseGSU CIS 4394 Agentic AI
InstructorDr. Xinyu Fu
TermFall 2026
FormatHands-on studio class
📡 Agent Radar · this weekAgents are getting real powerThree stories from the past few days — physical power, economic power, and a containment incident. Think → Act → Coordinate → Spend → Affect the physical world. →
📝 After classWeek 2 SummaryScavenger-hunt answer key (nine layers → real Codex files) · join your GA1 group on iCollege · Opal / Fleet / ADK tutorials with videos · Quiz 1 readings + five sample questions. →
Start here

The path through today

Work through the four parts in order. Do Prep before you come to class — the session starts with building, not with account recovery.

00 Before classStudent prepAccounts, installs, the guided reading, and what to bring. Fifteen minutes now saves the whole build sprint later. → 01 Part 1Unpack CodexClick through the nine layers of a coding agent, then watch the agent loop run — step by step — as Codex fixes a failing test. → 02 Part 2The same lens on Claude CodeDoes the architecture we extracted explain a competing product? Sort what is shared from what differs. → 03 Part 3Build the Job Search AgentTransfer the architecture to a new domain. Choose Opal, Fleet, or Codex + Python — with full step-by-step instructions. → 04 Part 4Break it, grade it, submit itFour required tests, the evidence standard, ten deliverables, and the rubric. →
Discussion questionIf Codex had the exact same model — but no access to files, shell commands, tools, state, or permissions — would it still be Codex?
No — you would have a chatbot that talks about code. Everything that makes it Codex — reading files, running tests, applying patches, pausing for approval — lives in the harness. The model supplies reasoning; the product is the loop built around it. Part 1 takes this answer apart layer by layer.
Today’s arc

Reverse-engineer → compare → transfer → build

Unpack Codex

What architectural ingredients turn a language model into a coding agent?

Compare Claude Code

Does the same architecture explain a competing product — or is it product-specific?

Transfer & build

Keep the reasoning pattern; swap the goal, environment, tools, and safety boundary.