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
.
