Marketing & Growth

How to plan a monthly content calendar with AI

Marketing & Growth3 AI tools7 steps6 friction points

Want an agent to handle this on your live data? See the Starch version →

A monthly content calendar is the connective tissue between your marketing strategy and your team's actual output. It maps topics to publish dates, assigns owners, tracks channels, and makes sure nothing falls through the cracks between 'we should write about that' and 'it went live.' For most operators, building and maintaining this calendar is one of those recurring tasks that takes more brainpower than it deserves — not because it's hard, but because it requires pulling from a dozen different sources at once.

Content planning feels like an AI-ready problem because so much of it is pattern-matching and structured thinking. You're taking inputs — your audience, your goals, your existing content, seasonal moments — and converting them into an organized output. That's exactly the kind of synthesis work where LLMs shine. The first instinct is usually right: paste your situation into ChatGPT or Claude and ask it to build you a calendar.

General-purpose AI tools can genuinely help here. ChatGPT, Claude, and Gemini can brainstorm topic clusters, suggest a realistic publishing cadence, draft a month's worth of headline ideas, and output the whole thing as a structured table you can drop into a spreadsheet. If you give them enough context about your business, audience, and goals, the output is often good enough to act on. The friction shows up when you need that calendar to reflect what's actually happening in your business — not what you described in a prompt last Tuesday.

Skip the manual work → See the Starch version

Marketing & Growth3 AI tools7 steps6 friction points

AI walkthrough

How to do it with AI today

A practical walkthrough using ChatGPT, Claude, and other off-the-shelf LLMs — what they're good at, what you'll have to do by hand.

Tools that work for this

ChatGPTClaudeGemini

Step-by-step

1 Open ChatGPT or Claude and paste a context block: your company description, target audience, primary marketing channels, content goals for the month, and any dates or campaigns that are already locked in. The more specific you are here, the less generic the output.

2 Ask the model to generate a list of 20–30 topic ideas grouped by theme or content pillar. Review the list, cut anything that doesn't fit, and add topics you know are needed from your own product knowledge or sales conversations.

3 Feed the refined topic list back into the same thread and ask the model to assign topics to specific publish dates across the month, accounting for cadence (e.g., two blog posts per week, one newsletter, three LinkedIn posts) and any known business milestones.

4 Ask the model to output the calendar as a markdown table with columns for date, topic title, format, channel, owner, and status. Copy that table into a Google Sheet or Notion database — you'll likely need to manually clean up formatting and fill in owner assignments.

5 For each high-priority piece, prompt the model separately to generate a content brief: target keyword, angle, key points to cover, and a suggested headline. These briefs live in separate documents or rows and become the handoff artifact for whoever is writing.

6 At the end of the month, run the same process from scratch for the next month. Pull whatever performance data you have from Analytics or your CMS, summarize it in the prompt as context, and ask the model to weight next month's topics toward what worked.

7 If your team uses a project management tool like Notion or Asana, manually recreate the calendar there by copy-pasting tasks from the AI output. There's no direct write path from the LLM to your actual task system.

Prompts you can copy

We're a B2B SaaS tool for restaurant operators. Our blog targets owner-operators at independent restaurants. Generate 25 content topics for June, grouped into 4 pillars: operations, labor, finances, and marketing. Avoid generic advice — we want topics that feel specific to someone running a 3-location restaurant.

Here's my approved topic list for June. Assign each topic to a specific publish date, assuming we publish 2 blog posts and 3 LinkedIn posts per week. Keep blog posts on Tuesdays and Thursdays. Output as a markdown table with columns: date, topic, format, channel.

Write a content brief for this blog post: 'How to reduce food waste without cutting menu variety.' Include target keyword, search intent, 5 key points to cover, and 3 headline options. Audience is independent restaurant owners, not chains.

Last month our top 3 performing posts were about labor scheduling, tip pooling compliance, and delivery margin analysis. Use this to weight next month's topic mix — suggest where we should double down and what we should de-prioritize.

Turn this content calendar table into a list of Notion tasks, formatted as: Task name | Due date | Assignee (leave blank) | Status (Not started). Output as plain text I can paste into a bulk import.

Reality check

Where this gets hard

The walkthrough above works — until your numbers change, the LLM hallucinates, or you have to re-paste everything next month.

No connection to your actual performance data — you have to manually summarize last month's analytics before each planning session, and whatever you paste in is already stale.

The calendar lives in a markdown table inside a chat thread, not inside your team's actual workflow. Someone has to manually transfer every row into Notion, Asana, or wherever tasks actually live.

Context resets between sessions. The detailed brand voice notes and pillar definitions you spent time establishing last month aren't remembered — you re-paste them every time.

The model doesn't know what content is already in draft, in review, or published. Without that context, it can suggest topics that duplicate work already in flight.

Nothing triggers the next month's planning automatically. The whole process is manual and depends on whoever owns it remembering to start the cycle again.

Output structure drifts between runs — column names, date formats, and topic groupings vary enough that cleaning the output into a consistent format takes real time every month.

Tired of the friction?

Starch runs the whole workflow on live data — no copy-paste, no hallucinated numbers, no re-prompting next month.

See the Starch version →

Starch alternative

The same workflow on Starch

Starch is an agentic operating system — an agent builds persistent apps, dashboards, and automations that run continuously against your live business data. For content calendar planning, that means the workflow runs on real performance numbers and writes tasks directly into your systems, not a markdown table you have to manually clean up.

Connect PostHog through Starch's scheduled sync and use the Growth Analyst starter app to get a weekly digest of what content is driving traffic and conversions — so next month's topic priorities are based on actual numbers, not gut feel or a manual export.

Tell Starch: 'Every 25th of the month, pull my top-performing content from PostHog, generate a 20-topic content plan for next month grouped by my four pillars, and create tasks in Project Management with owners and due dates.' The agent builds that automation once and runs it on schedule.

Use the Project Management app — already built into Starch — as the live home for your content calendar. No copy-pasting from a chat thread into a separate tool; the agent populates tasks directly, with fields for channel, format, owner, and publish date.

Store your brand voice guidelines, content pillars, and audience definitions in the Knowledge Management app so the agent always has current context when generating briefs — not whatever you remembered to paste into the prompt this week.

Describe the content tracker you actually want in plain English: 'Build me a calendar view that shows every piece of content this month, its status, channel, owner, and whether it's on track by publish date.' The agent builds that surface and keeps it updated as tasks move through the board.

Because Starch connects to 3,000+ apps through its integration catalog, you can close the loop further — connect Mailchimp or ConvertKit to track newsletter performance, or pull Google Analytics 4 data live when the agent is building next month's recommendations.

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