Spec Your First Agentic Workflow: Social Scheduling with a Human Checkpoint
Objective: Apply the lesson's 3-step rule to design a repeatable, low-risk agentic workflow spec with exactly one human review checkpoint before anything publishes.
You're on the growth team at MVMT, the DTC watch brand acquired by Movado Group in 2018. Social captions currently get written by hand for every platform, every week. Leadership wants to test agentic automation on this task first because it's repeatable and low-risk.
Follow the lesson's 3-step rule to spec a workflow that pulls a brand brief, drafts captions per platform, and pauses for one human approval before scheduling.
Before you start
What you'll need
Free path (everything below is enough to finish)
Free self-hosted tier with 70+ AI nodes; no per-task pricing while testing a first workflow
Free way to track the '30% edit rate' quality signal the lesson recommends measuring
Paid upgrades (optional, faster/deeper)
Plain-language automation setup across 8,000+ apps, faster to deploy without engineering help
The process
1 step
Step 01 of 01
The lesson's 3-step rule: (1) choose a task you do the same way every time, (2) write out every step as if explaining to a new hire, (3) identify exactly one place where human review makes the output safe to ship.
MVMT's weekly social captioning is repeatable, currently manual, and low-risk if a draft is wrong before it publishes. Where does the one required human checkpoint go in this workflow?
Procedure
- Define the trigger: a new brand brief document dropped into a shared folder each Monday
- List every step a new hire would follow: read brief, draft caption per platform in brand voice, select or generate an image, format for each platform's character limit
- Insert exactly one approval checkpoint: all drafts post to a Slack channel for marketer sign-off before scheduling
- Define the final step only after approval: push approved captions to the scheduling tool
- Write the spec as a numbered list a developer could build directly from
MVMT Social Caption Workflow (spec excerpt) 1. TRIGGER: New brief in /briefs folder (weekly, Monday 9am) 2. AGENT: Draft 1 caption per platform (Instagram, TikTok, X) in brand voice from brief 3. AGENT: Attach suggested image from asset library 4. CHECKPOINT (human): All drafts post to #social-review Slack channel; marketer approves or edits 5. AGENT (post-approval only): Schedule approved captions via scheduling tool
Healthy
Every draft passes through the Slack checkpoint before scheduling; nothing publishes without a human decision.
Unhealthy
The spec has the agent scheduling directly after drafting, with no checkpoint step at all.
What this means
A workflow spec without an explicit checkpoint step isn't a scaled-down risk, it's a fully autonomous workflow that was never designed to be one.
So what do I do about it?
| Symptom | Action | Effort |
|---|---|---|
| Draft captions occasionally miss brand voice or make a factual claim about a product | Keep the Slack approval checkpoint in place until 20 consecutive runs need no edits, per the lesson's review-then-remove guidance | 5 min |
Final deliverable
A numbered workflow spec for MVMT's social captioning task, with trigger, every agent step, exactly one human checkpoint, and the post-approval step, ready to hand to a developer.
See a reference example
ThredUp, Weekly Listing-Copy Workflow (spec excerpt) 1. TRIGGER: New inventory batch tagged 'ready to list' 2. AGENT: Draft product description per listing from photos and category data 3. CHECKPOINT (human): Merchandising lead reviews 10% random sample before batch publish 4. AGENT (post-approval only): Push descriptions live to the marketplace listing
Success criteria
You're done when you can:
- Workflow spec includes a clearly named trigger, every intermediate step, and exactly one human checkpoint
- No step after the checkpoint runs before human approval