LinkedIn Content Engine
A configurable content marketing system that turns campaign goals, audience context, and live trend data into a full structured LinkedIn content brief — up to 10+ posts per run, each mapped to a specific format and objective, exported as formatted Word documents in under two minutes.
LinkedIn content marketing fails at scale for one reason: volume without strategy produces noise, and strategy without volume produces inconsistency. Most teams settle for one or the other. The LinkedIn Content Engine was built to deliver both — a system that takes a marketing goal and produces a full, structured content brief mapped to that goal, ready to hand off to any writer or publish directly after a final human pass.
What I built
A Node.js pipeline with an Express backend and a form-based frontend. A marketer or content strategist fills in the inputs: campaign theme, target audience, marketing objective (awareness, engagement, lead generation, thought leadership), field notes or product context, repurposing flags for any existing content worth reactivating, and the desired post count. The system handles the rest.
Configurable output volume. Post count is fully configurable per run. A light week might call for three posts. A product launch or campaign sprint might need ten or more. The generation pipeline scales to match the brief without sacrificing format variety or strategic coherence across the batch.
Trend integration. Before generation runs, the engine pulls the week’s relevant headlines from Google News via RSS, filtered by topic and cached for two hours. The trend data gets woven into the generation prompt so posts connect to something happening in the market right now — not recycled observations that could have been written any week.
Objective-mapped generation. The system prompt encodes a full content strategy layer: hook formats, storytelling structures, engagement mechanics, call-to-action ratios, and tone calibration per audience type. Every post in the brief is mapped to the campaign objective set at input. A thought leadership brief generates differently from a lead generation brief, even with the same source material.
Dual-document export. Every run produces two Word documents. The main brief contains all posts formatted and ready to edit or approve. The second is structured as a NotebookLM source document, so the content feeds directly into a research and ideation workflow without copy-pasting. Both are zipped and returned in a single download.
Usage logging. Every run logs token consumption, generation time, and campaign metadata behind an API route — easy to track output volume and cost over time without leaving the tool.
Why a pipeline rather than a prompt
A raw prompt produces a post. A pipeline produces a content programme. The difference is in what gets encoded: the campaign objective, the audience profile, the format mix, the trend layer, the structural consistency across every post in the brief. None of that survives a one-shot prompt. All of it survives a well-built system prompt paired with a structured generation pass. The LinkedIn Content Engine is that system — a reusable marketing infrastructure that any brand, team, or professional can point at a new campaign and get a structured, editable brief out the other side.
What it delivers
A content brief that would take a marketing team an hour to plan, write, and format now takes under two minutes to generate and another ten to review and personalise. The output is topical, format-varied, and aligned to the campaign objective from the first draft. The human layer — judgment, voice, final edits — stays exactly where it belongs. The engine handles the structural work that used to eat the calendar.