2 Content Operations AI Agents, Live in Production.
2 live agents automate content operations within marketing. They all run on demand. Each one publishes the inputs it needs, the steps it works through and what it hands back.
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Content Research
Research a topic from a brief, grounded in live web results and your own reference library, and get a cited draft.
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Social Media Post Generator
Turn one piece of source material into posts written for each channel you pick, with the character limits respected.
Citing the source, and writing for the channel rather than resizing for it
Content operations is where quality is quietly lost to throughput. Research is the first casualty: a writer under deadline uses whatever a search returns on the first page, and the draft carries facts with no recorded source, so nobody downstream can verify a number and it survives into publication because checking it would take longer than trusting it. Repurposing is the second. One article is supposed to become posts across several channels, but the practical method is to paste the same text and cut it to fit, which produces something that reads as an excerpt on every channel and as native on none — and the character limits get discovered at posting time.
These agents keep the provenance and respect the format. Content Research researches a topic from a brief grounded in live web results and your own reference library, and returns a cited draft. The citation is the whole point: an uncited draft is a set of assertions somebody has to re-verify, and in practice nobody does. Social Media Post Generator turns one piece of source material into posts written for each channel you pick, with the character limits respected — written for the channel rather than trimmed to it, which is the difference between a post and a truncation. Two agents cover this process, and both produce drafts; nothing is published, consistent with everything else here that would appear under the company’s name.
What this moves
- Claims traceable to a source
- Research is grounded in live web results and your own reference library and returned cited, so a fact in a draft can be checked rather than trusted.
- Repurposing effort per piece
- One piece of source material becomes posts written for each chosen channel with character limits respected, instead of one post truncated across several.
Marketing
How AI agents handle content operations
Drawn from the 2 agents above — what they require, how they run, and what comes back.
What they need
- Research brief
- Output settings
- What are you posting about?
- Post settings
What comes back
- Draft
- Angles worth considering
- Web sources
- From your library
- Check
- Drafted posts
- The angle
How they run
- Run on demand
- 2
- Steps per run
- 3–4
- Credits per run
- 4–6
- Use a knowledge base
- 1
Where content operations fits in marketing
Competitor tracking, market monitoring and content briefs are the slow part of a campaign. Agents keep that running continuously, so a launch is not waiting on someone to go and read things.
Next Step
Deploying content operations agents
These run as-is against the inputs listed above. Most deployments adapt one — a different source system, a different tolerance, a different approval path. The first call establishes which.