Why We Let an AI Draft Our Blog, and Still Read Every Word
Most of what you read on this blog, including the college-campus proposal guides and seasonal planning posts, starts life as an automated draft. We are not hiding that. What we do not do is let an automated draft publish itself without a human reading it first, and the reason comes down to how we built the guardrails versus how much we still do not trust them unsupervised.
What the automation actually does
We run what we internally call an editorial wheel: a rotating set of content ideas, tied to real seasonal patterns (football homecoming weekends, proposal season, graduation timing) and real venue facts, that gets turned into draft blog posts on a schedule. Each draft runs through a set of automated checks before it is even allowed to request review: no em dashes, no claims that contradict our actual sound curfew, no made-up acreage numbers, no accidental recommendation of a paid wedding directory, meta descriptions in the right length range for search snippets, and a minimum number of working internal and external links.
Those checks catch a lot. They do not catch everything, and they are not supposed to.
Why we still read every draft
Automated guardrails are good at catching the kind of mistake you can describe as a rule: a banned phrase, a missing field, a link that returns a 404. They are much worse at catching the kind of mistake that requires judgment: a fact that is technically true but slightly stale, a tone that is correct for a bride-focused post but was generated for the wrong section, a statistic that needs a source we have not actually verified recently.
We learned this directly. Earlier in building this content pipeline, we found college-themed proposal posts with venue facts that had drifted from the current numbers, and a cluster of posts with no category assigned at all, both invisible until someone went looking. The automated checks had no rule against "this post has no category," because nobody had written that rule yet. A guardrail only catches what someone thought to write down. A human reviewer catches the rest.
Where the line actually sits
Thinking about touring? Most couples know within the first ten minutes on the grounds. See tour times or check pricing first.
Our current process is: the wheel generates a draft, the automated guardrails run as a hard gate (a draft that fails them cannot move to approved), and then a review pass checks the things guardrails cannot, mainly whether the content is actually useful to someone and whether it fits the section it is meant for. Only after that does a post get a publish date and enter the queue. Nothing skips that sequence, including the posts in this proposal-season batch.
This mirrors the general guidance Google has published on AI-assisted content: the production method matters less than whether the result is accurate, original, and genuinely useful, which in practice means someone has to actually check it. A good overview of why automated content pipelines still need a review stage, rather than full autonomy, is laid out in Google's SEO starter guide, and it matches what we found the hard way: the gate matters more than the generator.
What changes going forward
Every rule in the guardrail list exists because something specific got caught by it, or should have been. We expect that list to keep growing as we find new edge cases, the same way the category gap and the duplicate campus post did this month. The automation gets more capable over time. The review step is not going away.