AI For Dummies — Field Guide A field guide 01 fleet 02 worktrees 03 models 04 skills 05 create 06 field kit 07 hands-on 08 verify review submissions ↗ EN / PT AI ENGINEERING 01 / 2026 A presentation for humans who ship AI for dummies. You do not need an army of models. You need a system: one mind to frame the work, several hands to execute it, and a clean boundary between every task. FIELD NOTE / 001 Ship the system. Skills · agents · worktrees · proof 01 strong model for ambiguity 03 bounded workers in parallel ∞ iterations with evidence Read this as a route map, not a prompt recipe. RULE ZERO Strong model for ambiguity. Light model for bounded work. THINK MAKE A small fleet coordination before parallelism ORCHESTRATOR Decides what needs to happen. Opus / reasoning → UI Component and visual states agent/ui TEST Acceptance cases agent/tests DOCS Guide and examples agent/docs The orchestrator preserves intent, writes small contracts, and gathers results that can be verified. It does not need to type every line. Why the boundary matters one vague task / three predictable failures 01 Context soup Every worker reads everything. Nobody knows which facts are load-bearing. 02 Branch collision Two agents touch the same checkout. The fastest path becomes conflict resolution. 03 Confident drift The diff is polished, but no one checks whether it solved the original problem. The subagent loop Click a phase. See the handoff. Delegation means moving one bounded task into a smaller context—not giving away responsibility. 01 PLAN 02 BUILD 03 REVIEW What crosses contexts brief → diff → evidence Package Contains Why it matters Brief goal, files, boundaries stops the worker inventing the problem Worktree branch and isolated checkout parallel edits do not collide Checks tests, build, criteria turns “looks good” into evidence Diff small, reviewable change integration and discard stay cheap Git worktrees One branch per hand. A worktree is another directory linked to the same repository. Each agent gets its own checkout and index; history remains shared. Select a node to inspect its checkout, owner, and next action. repository topology 4 checkouts ROOT main ● clean UI AGENT agent/ui 3 files · working TEST AGENT agent/tests 8 checks · ready DOCS AGENT agent/docs 2 pages · review Model routing Do not pay for reasoning where you need rhythm. Choose a job to see why the model profile changes. Work Profile Prompt shape Plan strong / broad What changes? What can break? Build fast / focused Implement this slice. Run these checks. Explore read-only / light Find where this contract is used. Review independent Does the diff satisfy the brief? Model gearbox capability tier × thinking effort Two separate knobs Choose the engine. Then choose the gear. A stronger model changes the capability ceiling. Higher reasoning effort gives that model more room to work. Start with the lightest combination that passes your real checks, then move one knob at a time. OPENAI CLAUDE GEMINI REASONING / THINKING LOW bounded + fast MEDIUM default start HIGH complex + costly ROUTING RULE Use strong models for ambiguity and judgment. Use lighter models for bounded execution. Raise effort only when evaluation shows a gain. Skills Write the right way once. A skill is a reusable procedure. It can carry instructions, references, scripts, and assets. It is not magical memory, and it does not replace acceptance criteria. 01 / trigger clearly 02 / load detail on demand 03 / return evidence SKILL PACKAGE SKILL.md procedure and limits references/ facts to consult scripts/ repeatable checks assets/ templates and examples name: review-ui · check focus, mobile, reduced motion · run verification · return evidence Create a skill repeatable pain → reusable judgment The skill forge Teach the decision. Keep the context light. Do not package everything you know. Capture the non-obvious choices that repeatedly improve an outcome, then prove the skill changes behavior. 01 Observe find repeated friction 02 Define trigger route precisely 03 Choose anatomy only needed files 04 Write guidance decisions, not trivia 05 Validate test real behavior OUTPUT / SKILL PACKAGE review-ui/ ├── SKILL.md ├── agents/ │ └── openai.yaml ├── references/ │ └── accessibility.md └── scripts/ └── verify.mjs VALIDATE quick_validate.py ./review-ui AFTER REAL USE observe failure → sharpen one rule → retest behavior → keep it narrow Common skills choose behavior before model The field kit Different jobs. Different instincts. A skill changes how an agent approaches work. Some shape communication. Others enforce research, debugging, review, or completion discipline. Select one to inspect its operating rule and verified source. SIMPLIFY ponytail-lite minimum code that holds COMMUNICATE caveman signal without filler COMPLETE unlazy gates and evidence INVESTIGATE research primary sources first DIAGNOSE diagnosing-bugs tight feedback loop REVIEW code-review standards × spec ECONOMIZE token-saver compress noisy output ONE PRACTICAL LOADOUT PLAN unlazy → BUILD ponytail-lite → DEBUG diagnosing-bugs → REPORT caveman INSTALL PACK Ask your coding agent to verify, install, and validate the skills. COPY ↗ Review every source before installation. Existing local skills must be preserved. Hands-on 10 minutes / one missing feature Tiny Tasks lab Same task. Better operating system. Start with a deliberately incomplete static task board. Run one prompt as written, reset, then run the skill-enabled version. Compare diff size, verification evidence, and unnecessary complexity. Open the starter → Clone from Gitea → Open the rules lab → Clone from Gitea → THE MISSING FEATURE Add All / Open / Done filters that survive reload and browser navigation. STACK HTML · CSS · JavaScript DEPENDENCIES none FILES 3 RUN A Good prompt COPY ↗ Clear context · constraints · acceptance · evidence RUN B Good prompt + skills COPY ↗ Same contract · explicit working methods · stronger proof COMPARE THE RUNS 01 Files changed 02 New dependencies 03 Checks actually run 04 Evidence returned THE HUMAN JOB The agent may be autonomous in execution. Intent, boundaries, and evidence remain yours. START HERE Begin with one agent and one skill. Add parallelism only when the tasks are truly independent. Verification run each gate separately Checks become evidence Three layers. Run each one alone. Run a gate on its own line, print its exit code, attach the output. The result is the deliverable. 01 · STATIC Lint and types Format, lint, type-check. Fast and scoped to one file. Run on every save. pnpm lint; echo "lint=$?" pnpm typecheck; echo "typecheck=$?" 02 · BEHAVIOR Unit and contract Tests that repeat. Run before claiming done. pnpm test; echo "test=$?" cd services/api && go test ./... 03 · INTEGRATION Real UI and API Drive the actual UI, API, or browser. Slower and flakier — only this catches mobile overflow and a missing 404. pnpm check:ui; echo "ui=$?" TURBO_FORCE=true pnpm e2e FOUR WAYS A GREEN REPORT IS FALSE 1 Pipe a gate tail, grep, or head hide the real exit code — a pipeline returns the last command's status. 2 Swallow a rejection A silent .catch(() => {}) hides a panic, an upstream limit, or a partial failure. 3 Trust the cache Turbo caches results. A gate that "passes" may not have run — use TURBO_FORCE=true . 4 Skip the third layer Lint and unit can both be green while the page breaks on mobile and the API never returns 404. RUN IT YOURSELF · two labs, under 10 minutes each Path A · verification lab Fill the four-row comparison strip on the starter. Run A naively, Run B with $gate-discipline and $webapp-testing . Open the starter → Clone ↗ git.marcospaulo.dev.br/.../src/branch/pages/hands-on/starter Path B · rules lab Toggle every rule off, run the prompt. Toggle every rule on, run it again. Compare diff size, gate invocations, and the names of checks the agent names back. Open the rules lab → Clone ↗ git.marcospaulo.dev.br/.../src/branch/pages/hands-on/rules Keep learning 12 new readings + primary docs Go deeper with official documentation, production case studies, Medium, and practitioner workflows. Rules and enforcement case study → Skills review desk → Primary references → 12-part reading path → Navigate by idea short chapters / one system Prefer a focused chapter? Start with the route map , then jump directly to models , agents and worktrees , skill creation , rules , or the skills review desk .