A working content engineering system

A working content engineering system

Team Pick
AI & Agents
Slate
Human review is counted per article at 8-12 minutes, against about 3 hours before the system existed.
Source
Slate
Tools
Slate, CMS, AI models
Runs
Weekly cycle
Cost
Free guide, runs in Slate
Last updated
August 7, 2026

What it is.

Six workflows, each with its output shown: a listicle builder, a long-form drafter, content refresh, citation gap outreach, an SEO brief generator, and an image and screenshot pipeline.

Brief approval runs 2 to 3 minutes each and final review 8-12 minutes per article, against about 3 hours per article before the system. Three caveats open the piece, including that none of it is for scaling low-quality content.

Slate's own account of building on Slate, so running it as described needs their platform. The six workflow shapes and the review accounting transfer anywhere.

What you get.

  • Six named workflows with the output each produces.
  • Human time accounted for per stage, at 8-12 minutes of final review per article.
  • The before figure, at about 3 hours per article with earlier tooling.
  • A distinction between workflows and agents, where an agent is a workflow with memory.
  • Three stated caveats, including that topic selection still matters more than the system.
HOW TO USE IT

How to set it up.

1

Pick the one workflow with the most repetition in your own process and build only that.

2

Count your current human time per article before you automate, so you have a baseline.

3

Build the brief generator before the drafter, since a bad brief makes a bad draft faster.

4

Keep a review gate with a stated time budget, at roughly 8-12 minutes per article here.

5

Add memory to a workflow only once it runs reliably without it.

6

Treat topic selection as a human decision that sits outside the system.

Use cases

See the whole pipeline

Read the six workflows and what each one produces before building any.

Budget the human time

Use the per-stage review minutes when planning capacity.

Pick the first workflow to build

Start with the stage that costs your team the most time today.

Best for

Deciding what to automate first

Six workflows with outputs shown is more useful than a list of possibilities.

Costing a content system

Per-stage human minutes is the number a business case needs.

Arguing against volume automation

The caveats section says outright that this is not for scaling low-quality output.

Open the original.

Hosted on Slate, free to open.
Open the Tool

Questions about A working content engineering system

Should I build all six workflows?
Are the time savings a benchmark?
How flattering is the sample?

Questions about AI & Agents

What does content engineering mean in practice?
Where should a team start?
Strengths
  • Human review time is counted per stage instead of implied to be zero.
  • It opens with caveats, including that experience matters more than the tooling.
  • The workflow-versus-agent distinction is a useful line, where memory is what separates them.
Limitations
  • Slate's own account of building on Slate, so the platform is the setting for the whole piece.
  • It is one person's setup, so the time figures are theirs and not a benchmark.
  • Six workflows is where it ended up, so building all of them at once is the wrong read.
  • Outputs shown are from their own content, which is the flattering sample.
Skip this if
  • Skip it if you already have an automated content pipeline with review counted per article.
Ideal for
  • Content ops leads
  • Heads of content
  • Stage: Series A onward

Want this running without building it yourself?

TripleDart has scaled 300+ tech companies with expert operators and AI workflows behind every play.