AI agent publishing

How an AI Agent Writes and Publishes Blog Posts

What agent-driven publishing actually requires, what you can try for free, and the legal questions people keep asking before they set one up.

In short

AI agent that writes and publishes posts

An AI agent that writes and publishes posts is software that generates blog content and pushes it live on its own, without a human copying and pasting into an editor. It needs somewhere to write, a way to authenticate as itself, and an endpoint to call when a post is ready. A chat window that hands you a draft is not t

What agent-ready publishing requires: an API, an SDK, a CLI, not a cha

cli

$ floggy publish

post deployed 200

$ floggy posts list

GET /api/posts 200

$

Built for developers

Headless CMS, API, and a CLI to publish from anywhere with your favorite agent.

Scheduled

Publish with intent

Long-form posts, scheduled, co-authored.

Note

One workspace

Notes and tasks beside the draft.

FAQ

Legal questions people ask before turning an agent loose

Is it legal to publish AI-written content?

In most jurisdictions, publishing AI-written content is legal on its own. The legal risk is usually around copyright of the output, plagiarism if the content copies existing work too closely, and platform-specific disclosure rules, not the act of AI authorship itself. Check the terms of any platform you publish to and any advertising or FTC-style disclosure rules that apply where you operate.

What is the '30% rule' for AI?

There's no single official '30% rule.' It shows up informally in different contexts, some content platforms and creators use it as a rough guideline that a meaningful share of a piece should be original human input or edit, rather than raw AI output published unedited. Treat it as a community norm, not a law, and check the specific policy of any platform or client you're publishing for.

Do I need to disclose that a post was written by an AI agent?

It depends on where you publish and who you publish for. Some platforms and some regions have specific disclosure expectations for AI-generated content; others have none. There's no universal requirement, so the safest approach is to check the policy of the specific platform and any regulations that apply to your audience before you decide.

How it works

Running an agent on a schedule instead of one-off generation

  1. Connect the agent to a real publishing target

    Give your agent an API key or CLI access to a blog it can authenticate against, not just a place to hand off drafts for manual posting.

  2. Define the schedule, not just the prompt

    A single generated post is a demo. Agentic SEO at scale means the agent runs on a cadence, checking what's already published through the API before deciding what to write next.

  3. Let it use custom collections for structure

    For programmatic SEO, the agent isn't just writing blog posts, it's populating structured collections through the CMS so a whole set of pages can be generated and maintained on a schedule.

  4. Review the loop, not every post

    At scale you're checking the agent's overall output and cadence periodically, rather than approving each individual post before it goes live.

Ready when you are

Give an agent something real to publish to

Start a free blog with API, SDK, and CLI access, then connect an agent whenever you're ready.

  • Your own domain

    Everything lives at an address you control.

  • Nothing to wire up

    Publishing, audience and analytics ship together.

  • Reach inboxes

    A newsletter and a subscriber list, built in.