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Just-in-Time Release (JIT)
PremiumUse scripts to generate, validate, and commit on the same day
Just-in-Time Release (JIT)
"Do not stockpile content. Produce on demand."
What you will get in this chapter
- A decision framework: inventory vs JIT
- A minimum scripted release pipeline (MVS)
- Quality gates and failure handling
One-sentence definition
JIT release = same-day generate + validate + commit.
The goal is to keep the drip cadence while avoiding inventory and code rot.
When you should adopt JIT
If any two are true, upgrade:
- Keyword pool > 50 and tasks keep piling up
- Templates/components change often
- You need build validation and retries
- External APIs are involved (pipeline must be controlled)
Hidden costs of inventory mode
- Commits look less “fresh”: most changes become
noindexflips - Code rot risk: late pages lag behind current components/layouts
- Status overhead: unpublished lists get harder to track
Minimum scripted pipeline (MVS)
| Module | You need | Acceptance result |
|---|---|---|
| Task queue | scripts/jit-queue.json | Batchable by priority |
| Controller | scripts/jit-worker.ts | Retry on failure |
| Quality gate | pnpm build | Failures are not pushed |
| Scheduler | cron | Stable cadence |
Queue and controller example
Task queue (scripts/jit-queue.json):
[
{ "keyword": "pdf to jpg", "status": "pending" },
{ "keyword": "video compressor", "status": "pending" }
]Controller flow (scripts/jit-worker.ts):
- Load
pendingtasks, pick N (e.g. 5) - Generate openspec + page code
- Run
pnpm build(retry or abort on failure) git add/commit/push- Mark tasks as
done
Scheduler (cron):
0 3 * * * pnpm tsx scripts/jit-worker.ts --queue scripts/jit-queue.json --batch 5 --generate-command "..." --commit --pushGitHub Actions vs persistent worker
| Option | Best for | Cost |
|---|---|---|
| GitHub Actions | Small scale, simple logic | Slow cold start, limited retries |
| Persistent worker | Scale with quality gates | Requires a managed machine |
Acceptance checklist
Task queue is graded and batchable
Build validation is in place; failures are not pushed
Scheduler runs reliably with drip cadence
Common mistakes
- Generate in bulk without validation -> CI breaks
- No retries or rollback -> one failure blocks the batch
- Cadence drift -> noisy metrics and weak attribution
Summary
Key takeaways
1. JIT is about control, not speed.
2. Quality gates are non-negotiable.
3. Keep cadence aligned with the drip strategy.
Next chapter: Internal Linking Automation - let authority flow inside the site.