AI Engineering: Advent of AI with goose Day 15 - AI Multi Platform Recipe System

Source: Dev.to

Overview

The marketing team needed a coordinated social‑media push across Instagram, Twitter X, and Facebook. Each platform required a different tone, structure, and content style.

This challenge introduced sub‑recipes in Goose. Instead of writing three separate pieces of content by hand, the goal was to build a reusable automation system:

• One input → Three platform‑specific outputs
• A single orchestrator recipe coordinating the entire workflow.

The Challenge: Automate Multi‑Platform Content Generation

The task was to create a four‑recipe system:

All recipes accepted the same core parameters:

• event_name
• event_date
• event_description
• target_audience
• call_to_action

The orchestrator:

1. Called each sub‑recipe.
2. Aggregated the results.
3. Saved everything to a unified output file.

Each recipe was:

• Validated.
• Structured with proper YAML front‑matter.
• Tailored to the communication style of its platform.

The Social Media Campaign System

The completed system generates:

• A fashionable, high‑impact Instagram caption
• A concise, professional five‑tweet Twitter X thread
• A warm, family‑oriented Facebook event description

All content is produced from a single input set and saved to a unified Markdown file.

Technical Architecture Diagram

Below is a generated text‑based diagram showing how the recipe system is structured.

                         ┌──────────────────────────────────────────┐
                         │        Social Campaign System            │
                         └──────────────────────────────────────────┘
                                        │
                                        ▼
                   ┌──────────────────────────────────────────────┐
                   │           Main Orchestrator Recipe            │
                   │            social-campaign.yaml               │
                   └──────────────────────────────────────────────┘
                                        │
        ┌──────────────────────────────────────────────────────────────────────────┐
        │                                                                          │
        ▼                                                                          ▼
┌──────────────────────────┐                                      ┌──────────────────────────┐
│ instagram‑post.yaml      │                                      │ twitter‑thread.yaml      │
│ Platform‑specific caption│                                      │ Multi‑tweet thread       │
└──────────────────────────┘                                      └──────────────────────────┘
                                        │
                                        ▼
                              ┌──────────────────────────┐
                              │ facebook‑event.yaml      │
                              │ Long‑form event content  │
                              └──────────────────────────┘

Technical Stack

This recipe‑based automation stack is designed for repeatable, scalable content generation.

Platform Outputs

The system generated three fully formatted outputs for the Magic Night of Lights and Ice Sculpture Unveiling. Each output reflects the tone and expectations of its platform.

Instagram

A high‑impact caption with strategic hashtags and a polished, visual‑forward tone.

![Instagram post – Magic Night of Lights and Ice Sculpture Unveiling](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/pz46nie8v0ampm5xnmnp.png)

Twitter X

A five‑tweet thread (≤ 280 characters per tweet), structured for clarity and shareability.

![Twitter thread – Magic Night of Lights and Ice Sculpture Unveiling](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/po0v7q3hffqi2rmk7us8.png)

Facebook

A long‑form event description that feels warm and family‑oriented.

[![Facebook post – Magic Night of Lights and Ice Sculpture Unveiling](https://media2.dev.to/dynamic/image/width=800,height=,fit=scale-down,gravity=auto,format=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fj9bcpc4knwoc1rq7wmye.png)](https://media2.dev.to/dynamic/image/width=800,height=,fit=scale-down,gravity=auto,format=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fj9bcpc4knwoc1rq7wmye.png)

Description (for families and community‑oriented audiences)
[Insert the full Facebook copy here – the original content was truncated but follows the same friendly, inclusive style as the Instagram and Twitter examples.]

All images use descriptive alt‑text for accessibility.

My Final Thoughts

Day 15 shifted the focus from knowledge engineering to workflow automation. Recipes appear simple at first glance, but orchestrating multiple sub‑recipes into a cohesive system requires architectural thinking. What stood out in this challenge was the clarity that comes from building reusable automation. Instead of writing content three separate times, I now have a system that will work for every future event with no additional effort.

• This is engineering that scales.
• This is engineering that saves teams time.

This is exactly where goose excels—it rewards structure, clarity, and repeatability.

Day 15 encouraged me to think like a systems designer rather than a content generator, and that shift will matter in the challenges ahead.

This post is part of my Advent of AI journey – AI Engineering: Advent of AI with goose, Day 15 of AI engineering challenges.

Follow along for more AI Engineering Adventures with Eri!