I automated my LinkedIn pipeline so the posts are basically a byproduct of work we were already doing. Here is how it works: - Everything gets captured raw → Meeting transcripts, voice notes, messy half-thoughts: they all get dropped into one inbox folder. Zero formatting, zero cleanup. Capture first, structure later. - An AI agent parses the inbox → It reads every drop and sorts what it finds into people (CRM update) , tasks, decisions, ideas, and content angles. Every single meeting gets asked " is there a LinkedIn idea in here?" ( I have flows for what is considered "content" , aligned with the brand) - I approve every item → The agent proposes, I decide. - Approved ideas land as drafts from a template, each one linked back to the meeting it came from. - The words come from a voice fingerprint → I fed my own transcripts into a profile of how I actually talk, so the drafts sound like me. - Once a month I sit down with the agent for a proper conversation → It brings what the industry published that month and what our own meetings taught us, and together we draft the company posts. - I edit, pick the visuals from a small set of templates, and schedule. The end goal: capture once, decide once, and let structure do the rest. If you want to build this yourself, start with the inbox. One folder where everything raw lands. Everything else grows from there.