If you run a business or lead marketing at one, you already know the hardest part of content isn't having ideas. It's showing up consistently. I built a system that does the heavy lifting for me: research, draft, citations, image, publish. In this video I run it live, hit two real bugs, fix them, and show you exactly what it costs.

Why I built this in the first place

I help founders and heads of marketing at small B2B companies move away from content that only happens when the founder has an hour to spare. That inconsistency has a real cost. B2B companies that blog consistently get 67% more leads monthly than companies that don't. It takes 3 to 5 pieces of content before 40% of B2B buyers even reach out to a seller, and responders consume an average of 4.5 pieces of content before contacting a supplier. If the content trail runs cold, buyers just don't call. That's the whole reason this system exists.

52% of B2B marketers say blogging is the most essential tactic in their content marketing, and 59% call blogs their most valuable channel. I'm not writing about things I don't know. I built this for people who already have the expertise and just need to get it out faster, 10, 15, 20 times faster than typing it out manually.

Running the system live: topic, sources, categories

I open my script, called create blog post, and run it. It starts asking me questions. First one: what's the next post about? I can type a topic or paste a source URL and let the research start from there. For this video I pasted a URL about why businesses should use AI automation, benefits and drawbacks included.

Then I pick a category. I run three: automation, AI tools, and AI for business. This post technically fits two, but I keep it to one category for cleanliness, so I chose AI for business. Next it asks if I want a FAQ section. I always say yes. It helps readers and it helps SEO. Then it asks for a publish date, month, day, year. I hit enter for today's date.

Last question before research starts: does this post include any tools or products with links? This one didn't, so I said no. My rule here is simple: any affiliate link gets a disclaimer stating the post was written independently and that I may earn a small commission at no extra cost to the reader if they subscribe. The tool review itself never changes because of that link.

When the automation breaks, and why that's actually good

Claude goes online, researches multiple sources, and cross-checks them so I'm not stuck going back and forth burning tokens on a rough draft. First run: it failed. Turned out I'd hit a token limit I'd set per post. Normally I'd just close the window and start over, but that wastes money already spent. Instead, I adjusted the system, which saves any output generated but not used in the last 5 days, and clicked resume to pick up right where the system left off.

It failed again on the second try. This time I figured out why: this post asked for both benefits and drawbacks, which made the draft longer than my system allowed. I went into my script, raised the drafting length limit, ran it again, and chose resume. That time the draft came through.

This is the part I actually like about AI automation. Every time something breaks, it's a chance to fix the system permanently. Next time this exact bug won't happen again.

The review window: sources are a hard rule

Once the draft is done, I land on my review window: title, excerpt, quick summary, introduction, sections, all editable. One rule I never bend: every post needs sources. I want credible links for SEO, sure, but more than that, I want to back up every claim I make. My AI tool goes online, finds those sources, and drops them into the post as numbered citations a reader can click straight through to.

On this run the citations came back empty at first. Small bug: a case-sensitive title mismatch. I fixed one letter from lowercase to uppercase and reran the check. Sources showed up fine after that. I won't approve a post without them, no exceptions.

What this actually costs

Here's the number I want business owners to sit with. The copy for this post cost 29 cents through the Anthropic Claude API. The image cost 16 cents through OpenAI's image API. That's 45 cents total for a fully researched, cited, branded blog post that would otherwise take me hours to write.

Current API pricing backs this up as a normal result, not a lucky one. Anthropic's Sonnet model runs around $3 per million input tokens and $15 per million output tokens, with a cheaper Haiku tier at $1/$5 per million for lighter tasks. A blog draft with research and a few revision passes uses a small fraction of a million tokens. On the image side, OpenAI's own pricing puts medium-quality image generation around 7 cents each, which lines up almost exactly with what I paid.

I stop and think about that for a second every time. Under a dollar in raw API costs for something that used to eat an entire afternoon. The real investment isn't the API bill, it's the time spent building and debugging the automation itself, which is exactly what those two failed runs show.

Why I still read every word before it publishes

Once I approve the draft, the system generates the hero image, branded to my site colors and style. I review that too before approving. After that, it checks all files and links, then asks if I want to publish now. I say yes, and the post goes live with a full structure: quick summary, table of contents, numbered citations linking to sources, and an FAQ section.

I do this review step on purpose. Google has been direct about this: however content is produced, success in Search comes from original, high-quality, people-first content that demonstrates real expertise. Google's own guidance frames the risk as scale without review, mass-producing thin pages or publishing AI articles daily with no editorial check, not AI writing itself. My system automates the drafting. It doesn't automate my judgment. I still read the whole post before it goes live.

In a market full of AI-generated content, that distinction matters more, not less. Genuine expertise and a real point of view are getting rarer, and 97% of B2B buyers say trust is a decisive factor in their purchase decisions. A cited, reviewed, human-approved post is a different thing than a pile of unreviewed AI output, even if both start from the same script.

Writing so it doesn't sound like AI wrote it

One more piece I want to flag. Behind this system I run two specific skills that stop the output from sounding hollow or generic, an anti-AI writing skill and a humanizing AI output skill. Without them, the draft reads noticeably more like typical AI slop, more em dashes, more hollow phrasing, less like an actual person talking.

I share both of these files through my newsletter, Boundless Automation. Subscribe on the homepage or go straight to the newsletter page, and the welcome email includes a link to download all free resources in a shared Canva document. In there you'll find both files. If you're already subscribed, they're linked in the resources section of my weekly emails.