Print this page in landscape from Chrome or Edge: Ctrl+P → Layout Landscape → Margins None or Default → Background graphics on. The site chrome above is hidden in print.

In the print dialog, leave Margins at Default (or pick None). Picking Custom or Minimum shrinks the printable area below what this layout assumes and the handout tips onto a second page.

Download PDF Pre-rendered Letter-landscape one-pager — for shared / kiosk laptops where the print dialog is locked down.
2 Course 2 · Student Handout

Builder Orientation

From user to builder. One live build, one student build, one paper decomposition drill — in two hours.

Duration2 hr (1 break)
AudienceAspiring builders
PrereqCourse 1
0:00–0:15M1 Builder Mindset15 min · talk
0:15–0:40M2 Live Build #125 min · demo
0:40–0:50Break10 min
0:50–1:30M3 Student Build + Recovery40 min · build
1:30–1:50M4 Decomposition Drill20 min · paper
1:50–2:00M5 Wrap & Assignment10 min

Bring with youDone before you walk in

  • Course 1 complete. Centaur, cyborg, the six 201 skills, and the delegation equation should be familiar — we build on them.
  • A laptop with M365. Power Apps, SharePoint, and one AI tool (GenAI.mil preferred) signed in before you arrive.
  • One real section problem in your head. Something annoying that recurs at least weekly — the candidate for your prototype.
  • A notepad. Module 4 is paper decomposition. No laptop touches paper-only exercises.
  • Your frontier sticky from Week 1. We will reference it in Module 1 and add to it in Module 5.

Key termsThe vocabulary you’ll hear today

  • DecompositionBreaking a problem into the smallest useful pieces before you open AI. The single biggest predictor of build quality.
  • PrototypeA working core function — even if rough. Not pretty, not complete, working.
  • The four decomposition questionsWhat data fields? What does the user need to do? What is the simplest useful version? What data structure backs it?
  • The simplest useful versionThe one core function the tool must do. Build that first; everything else is iteration.
  • Peer review (the four checks)Clear problem statement · core function works · evidence of iteration · can explain the choices.
  • Failure caseA specific thing AI got wrong on your build — the most valuable thing you can share with other builders.

Exercises in classWhat you will do live — and what “done” looks like

M2 · Decompose first, on the whiteboard (5 min, group). Equipment Tracker. Before any AI: name the data fields, the user actions, the simplest useful version, and the data structure that backs it. Done: the room can call out item name, serial, assigned-to, dates, status, and the four user actions before the instructor opens a tool.

M3 · Pick a starter problem and build it (25 min). Choose one: Leave request tracker · Training attendance log · Vehicle inspection checklist · your own section problem (clear scope with the instructor first). Decompose on paper for 2 min, then prompt. Done: the core function works, even if rough.

M3 · Peer review (15 min). Pair up. Six minutes each: demo → partner walks the four checks. Clear problem statement · core function works · evidence of iteration · you can explain why you made each choice. Done: you can answer Check 04 without saying “the AI told me to.”

M4 · Decompose a real unit problem (10 min individual). Pick a recurring problem from your section. Run the four questions on paper. No AI. Done: a specific simplest-useful-version you could prototype this week.

M4 · Pair review the decompositions (8 min). Trade worksheets. Your partner pressure-tests your scope: too big? too vague? data structure missing? Done: you walk out with one decomposition you trust enough to start building tonight.

Anchor phraseFive minutes on paper saves thirty minutes building the wrong thing.

What you’ll be able to doBy the end of the session

  • Decompose a real section problem on paper before opening any tool.
  • Build a working prototype of a single core function in 25 minutes.
  • Run a peer review on someone else’s build using the four checks.
  • Defend why you made each design choice — not just what AI suggested.
  • Spot when a build is “too big” and cut it back to the simplest useful version.

HomeworkCome to Course 3 with four things · 2–4 hours over the week

  • One. A working (or partially working) prototype of the problem you decomposed in Module 4.
  • Two. Notes on what worked — prompts that landed, features that came together fast.
  • Three. Notes on what didn’t — errors you hit, features you cut, dead ends.
  • Four. One failure case worth sharing — something AI got wrong that other builders should know about.
  • Support: office hours (Wed 1500–1600), #builder-orientation Teams channel, ai-builders@1stbn99thmar.mil. Use them; don’t struggle silently.