Phase 33 · Lesson 12

Hands On Lab and Phase Exit

≈ 2 min core reading · 107 source/companion words

Learning contract

What you should be able to do after this

Explain Hands On Lab and Phase Exit without relying on framework buzzwords.
Connect the lesson to the phase outcome: Build a trustworthy GitHub Actions pipeline that verifies pull requests, creates immutable release artifacts, uses least privilege, caches safely, and controls deployment concurrency.
Reproduce the relevant behavior and verify it with evidence.
Diagnose at least one representative failure instead of guessing.

Figure 33.12 — TaskFlow boundary map

pull request

deterministic install

lint/typecheck/test/build

trusted main

immutable artifact

environment gate

deployment

This lesson belongs to Phase 33. Keep the full request/data path visible even when today's code changes only one box.

Instructor workflow: predict first → implement the smallest slice → run it → inspect evidence → break one assumption → diagnose → explain it back. Do not copy the whole code block before understanding the first failing boundary.

Hands-On Lab and Phase Exit Implement CI, integration testing, and release-image workflows in a branch. Break each gate deliberately and prove it fails for the expected reason. Then restore the repository, publish SHA-tagged images from main, and verify that the release manifest points at exactly that commit.

Integration Images Candidate PR green → green → published → recorded

Exit criteria

What this changes in TaskFlow • Break lint -> CI must fail

• Break migration -> integration must fail

• Break Docker build -> release must fail

• Verify packages permission only in release job

• Verify production gate does not rebuild images

Phase exit requires reproducible green CI plus an immutable artifact tied to the tested commit.

Executable lesson studio · ci

Now turn the explanation into engineering skill.

CI turns repository rules into automated gates. A useful pipeline must be understandable, reproducible locally, secure, and able to fail for the right reasons.

By the end, you should be able to

Explain Hands On Lab and Phase Exit in terms of concrete inputs, ownership, outputs, and evidence.
Implement or reproduce the smallest TaskFlow slice that demonstrates this ci concept.
Diagnose one representative ci failure using observable evidence instead of trial-and-error.

Figure 33.12B — Mental model

git event

runner

install

quality gates

artifact/deploy decision

Read left-to-right while implementing. When debugging, walk right-to-left until the first observed fact differs from your prediction.

Code-along sequence

One coherent change at a time

01
Restate the goal of “Hands On Lab and Phase Exit” as one observable behavior. Write the success signal before touching code.
02
Trace the boundary map: git event → runner → install → quality gates → artifact/deploy decision. Mark the one boundary this lesson changes.
03
Inspect the current repository state and record the exact files, route, table, or runtime involved. Avoid creating an abstraction before you can name the existing owner.
04
Implement the smallest vertical slice. Add one coherent change, run the narrowest verification command, and read the output before continuing.
05
Connect the slice to TaskFlow’s phase artifact: .github/workflows/ci.yml plus release/deploy workflows that build once, tag by commit SHA, and gate promotion.. Verify behavior from the outside as a user or API client would.
06
Create one controlled failure that is safe to reproduce. Predict the symptom first, capture evidence, locate the earliest broken boundary, then fix only that cause.
07
Close the reference and rebuild or explain the core change from memory. Record what you would monitor or test before trusting the same change in production.

yamlBuild the quality gate one step at a time

name: CI
on: [pull_request]

jobs:
  verify:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - run: corepack enable
      - run: pnpm install --frozen-lockfile
      - run: pnpm lint && pnpm typecheck && pnpm test && pnpm build

Do not copy this as a finished answer. Predict what each boundary does, type the smallest useful slice, run it, then compare the result with your prediction.

Verification

Prove the happy path

Run the narrowest relevant command or request and require a clean exit/status.
Inspect the boundary-specific evidence: terminal output, Network panel, database row/query plan, test report, container health, or deployment logs.
Repeat the behavior once after the change so a one-off cached or stale result cannot masquerade as success.

Break it on purpose

Build debugging memory

CI green because important workspace checks never ran
Change one assumption in the ci example—identity, input, configuration, ordering, connectivity, or state—and predict the exact symptom before running it.

SymptomInvestigation path

Works locally, fails in CI

Compare Node/pnpm versions, lockfile state, environment variables, OS assumptions, and generated artifacts.

Workflow has excessive privileges

Set least-privilege permissions at workflow/job level and isolate untrusted pull-request code from secrets.

Closed-reference challenge

Can you transfer the idea?

Without copying the final source, create a second small scenario that applies “Hands On Lab and Phase Exit” to a different TaskFlow resource or input. Write the acceptance criteria first, implement it, and provide the evidence that each criterion is satisfied.

Explain-back

Answer these without reopening the solution

What problem does Hands On Lab and Phase Exit solve in TaskFlow, and what would be observably wrong without it?
Which part of the ci boundary owns the decision, and which neighboring layer must not own it?
What evidence proves the happy path instead of merely suggesting it worked?
Name one realistic failure or abuse case and the first place you would inspect.
If requirements doubled tomorrow, which part of this design should stay stable and which part is allowed to change?

Lesson studio

Turn the reading into skill

Do it

Add environment protection/permissions for deployment and ensure stale production runs are not silently canceled mid-release.

Use the smallest change that demonstrates this lesson. Stop after it works and capture evidence.

Break it safely

CI green because important workspace checks never ran

Predict the symptom before causing the failure. Then locate the earliest boundary where reality diverges from expectation.

Explain it back

Why does this responsibility live here, what input does it trust, what output proves success, and what would go wrong if another layer owned it?

If your explanation is vague, repeat the boundary trace before moving on.

Exit ticket

Before marking complete

Close the reference. Reproduce the core idea from memory or explain the exact request/data flow aloud. Then check your diff or notes for accidental shortcuts that bypass validation, authorization, error handling, or verification earned in earlier phases.

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