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03 / 03 · AI WORKFLOW SYSTEM · 2026

CONTENT OS

A modular AI system for content production.

ROLE
Automation / AI Integration / Development
YEAR
2026
STACK
n8n / OpenAI / Notion / APIs

01 — PROBLEM, APPROACH & ARCHITECTURE

Problem: content work scatters across notes, drafts, assets and platforms with no shared structure. Approach: design six independent modules with one contract between them — each stage receives a defined input and produces a defined output. n8n orchestrates the flow, OpenAI handles the language work, and a Notion-style library keeps every asset searchable and traceable.

IDEA SYSTEM RESULT

02 — PROCESS: SIX STAGES

  1. 1

    RESEARCH

    Gather sources, links and references into one intake. AI summarizes; humans keep what matters.

  2. 2

    IDEATION

    Turn research into angles and hooks. A structured backlog replaces scattered notes.

  3. 3

    WRITING

    Draft with AI assistance inside templates — consistent voice, faster first drafts.

  4. 4

    ASSET GENERATION

    Derive visuals, snippets and formats from the same source draft.

  5. 5

    ORGANIZATION

    Everything lands in a searchable library with status and ownership.

  6. 6

    PUBLISHING

    Ship from the library on schedule. Finished work feeds back into research.

Modules over monolith

Each stage runs standalone — adopt research alone or the full OS without rework.

One contract between stages

Defined input, defined output. Swap models or tools without rewiring neighbors.

Library as source of truth

Nothing lives only in chat threads; every asset is searchable and traceable.

03 — OUTCOME

An architecture concept where modularity is the feature: change one part without rewiring the rest.