Schedule LinkedIn posts with an AI agent
Let your assistant draft, revise and queue — and keep the last look for yourself. Agents write to the queue; Blabigo publishes.
Start freeThe loop, and where you sit in it
Most “AI posting” tools collapse this into one button and hope the output is good. Splitting it into four moves is slower to describe and much faster to live with, because the expensive mistakes all happen between step two and step three.
Draft
linkedin_create_draft You describe the post, or point the agent at something you already wrote — a release note, a customer call, a paragraph from a doc. It writes a draft into your Blabigo account. Nothing is scheduled yet, and a draft has no path to publication on its own.
Revise
linkedin_update_post You read it and say what is wrong. The agent edits that same post in place rather than generating a second one, which is the difference between a queue you can read and a drafts folder with eleven near-identical versions in it.
Queue
linkedin_schedule_post You give it a time and it goes on the queue. The agent's involvement ends here: Blabigo's scheduler is what talks to LinkedIn, at the time written on the post.
Change your mind
linkedin_cancel_scheduled_post Cancelling reverts the post to a draft. It does not disappear, so you can always see what was pulled back and put it in again later.
Prompts that produce something usable
The difference between a post you can send and one you delete is almost never the model. It is whether you gave it raw material and told it what you do not want.
Turn work you already did into a post
“Read the changelog I just pasted and draft a LinkedIn post about the one change customers will actually care about. No emoji, no hook question, and don't call it a game-changer.”
Write in your own voice
“Pull my last ten published posts and draft a new one about hiring engineers in a small team. Match how I actually write — sentence length, how I open, whether I use lists.”
Fill a week
“Draft three posts from these notes and queue them for Tuesday, Thursday and the following Monday at 9am. Show me all three before you schedule anything.”
Review what is coming
“What's on my queue for the next two weeks? Flag anything that overlaps in topic or would go out less than a day apart.”
Respond to performance
“My post about remote onboarding did well. Draft a follow-up that goes deeper on the part about the first week, and queue it for Thursday.”
The limits an agent runs into
These are enforced on the server, so they bind the agent, the API, the CLI and the web app the same way. They are not instructions the model is asked to follow.
10 posts per account, per day
Per LinkedIn identity, counted against the UTC day the post is scheduled into. A loop that tries for an eleventh is refused.
100 queued posts per user
The most future-scheduled posts one account may hold at once, across every identity.
10 minutes minimum spacing
Two posts on the same identity cannot be queued within ten minutes of each other.
180-day scheduling horizon
Nothing can be queued further out than six months.
60-second minimum lead time
A post cannot be scheduled so close to now that it races the publisher — which also means it can never be used as an instant-publish trick.
Frequently asked questions
- Can AI schedule LinkedIn posts for me?
- Yes. Connect an AI assistant to Blabigo over MCP and it can draft a post, edit it after your feedback, and place it on your publishing queue for a specific time. What it cannot do is publish — Blabigo's scheduler does that when the scheduled time arrives, which leaves you a window to read and cancel.
- Why can't the agent just publish the post itself?
- Because an agent that can publish has no undo. Language models misread instructions and loops repeat themselves, and on LinkedIn the cost of that lands on your professional reputation in public. Queueing keeps the speed of automation while leaving a checkpoint where a human can still intervene, and it costs almost nothing — the post still goes out at the time you asked for.
- What stops a runaway agent from flooding my feed?
- Server-side quotas that apply to every route equally: a maximum of 10 posts per LinkedIn identity per UTC day, at most 100 queued posts at once, and a minimum of 10 minutes between two posts on the same account. An agent stuck in a loop hits a refusal, not your followers.
- Will the posts sound like AI wrote them?
- That depends almost entirely on what you give the agent. Asked to write about a topic from scratch, it will produce the generic result everyone recognises. Asked to work from your notes, your changelog or your own past posts, and told explicitly what to avoid, it produces something much closer to usable — and you still edit it before it goes out.
- Can I use this for a company Page as well as my profile?
- Yes, for any profile or company Page you have connected to Blabigo and have permission to post from. Permissions are re-checked when the post publishes, not only when it is queued, so access removed in the meantime takes effect.
- Which AI assistants can do this?
- Any client that supports the Model Context Protocol, including Claude Desktop and Claude Code. Setup is a single endpoint URL in most clients.
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