Most of this blog is drafted by the agent it describes, so these are field notes, not theory: what a post actually costs to generate, how an approval-first pipeline fact-checks its own claims and links, when building your own agent beats buying one, and where automated writing still needs a human hand on the shears.
The drafting prompt is the easy 10%. Here's what it really takes to build your own AI content agent: dedup, link checks, schema, cron, retries, cost caps.
ai-agentscontent-automationbuild-vs-buyengineeringseo
Google Search ignores llms.txt and says so in writing. Here's what the data shows about who actually reads the file, and when it's still worth shipping.
seogeoai-agentsllms-txtstatic-sites
How often should you publish blog posts in 2026? The benchmarks say frequency helps until it flattens — here's the cadence a solo operator can hold.
content-strategypublishingseobloggingai-content
The real cost to generate a blog post with AI in 2026: per-run token math, hosted tool fees, caching, and a model table running from $0.34 to $26.92.
ai-contentllm-costsagentscontent-strategyseo
How to fact check AI generated content in 20 minutes: resolve every URL, tell dead links from fabricated ones, and match each claim to its source.
ai fact-checkinglink verificationcontent qualityeditorial workflowai writing
Google's scaled content abuse policy never makes AI the offence. Here's what it actually bans, what it doesn't, and how to publish safely in 2026.
seogoogle-searchai-contentcontent-strategypublishing