I think your budget constraints matter too.
Your options increases.
A few people have built solid content workflows with Claude + n8n/Zapier, especially around research → drafting → repurposing → publishing pipelines.
One thing I’d recommend before going deep into agents is designing the “content system” first:
source inputs (ideas, docs, transcripts, tweets, etc.)
feedback loop (performance data)
The workflows usually become way more reliable when the AI is only responsible for specific steps instead of “create everything autonomously.”
Some genuinely useful resources:
n8n creator workflows on YouTube/GitHub (a lot of practical agent examples)
Anthropic’s prompting docs for Claude workflows
LangChain/LangGraph examples for multi-step orchestration logic
People building “AI media companies” on X are sharing surprisingly detailed architectures lately
A pattern I keep seeing work well:
Research agent → outline agent → drafting agent → formatting/repurposing → human review → scheduler/posting
Also, if you’re using Claude Code specifically, it becomes really powerful when paired with structured file systems + markdown knowledge bases instead of trying to keep everything inside prompts.
Hope that helps