I've been experimenting with what people are calling "agentic workflows" lately. The YouTube algorithm keeps feeding me videos like "how I’m automating 97% of my business with AI" and "Claude Skills : Create your Own AI Employee in 9 Min". Honestly, the hype around completely replacing human roles with AI agents can feel a bit much. Most of those videos show flashy UIs without getting into the nitty gritty of what actually works.
But there's a grain of truth in all that. You *can* build small, focused automations that make a real difference, especially for repetitive marketing tasks. I decided to build a simple workflow to automate marketing content tasks with AI. My goal: generate blog post ideas and draft social media snippets from a single topic input. No 97% automation here, but a solid win for specific, time consuming tasks.
What is 'Agentic lite' AI for Marketing Automation?
When I hear "agentic AI", my developer brain immediately thinks of complex loops, self correction. And multiple LLM calls. But for practical business use, especially in marketing, it doesn't have to be that complicated. I see it as chaining together a few smart AI actions to complete a small workflow. Think of it as a digital assembly line for your content.
Many of the discussions, like Kobe Smith talking about "VMS & Agentic AI Automate workflows and improve productivity in your business", hint at this. It's not about creating a sentient marketing manager. It's about connecting tools like Zapier or Make (Integromat) with large language models to handle specific, well defined steps. For a small marketing team, or even a solo founder, this kind of automation can free up significant time.
The core idea here is to minimize manual handoffs. Instead of taking a blog idea, writing a draft, then manually writing five social posts for it, you set up a system that does the heavy lifting for you. You still oversee it, but the grunt work is offloaded.
Building My Content Automation Workflow: The Setup
My setup for this experiment was pretty straightforward. I wanted to use tools that are generally accessible and relatively affordable for a small business. I picked:
- Notion AI: For inputting initial topics and storing the output. I use Notion for almost everything, and it's a fantastic hub. Our platform data shows Notion AI is tracked by users averaging $13/mo, which makes sense for its combined power.
- Claude Opus 4.7: For the heavy lifting of generating ideas, outlines, and social posts. I chose Claude because I find its long context window and instruction following excellent for structured output like JSON. You could use ChatGPT just as easily.
- Zapier: The glue that holds it all together. This is where the "agentic lite" magic happens. You could use Make (Integromat) too, which often offers more fine grained control, but Zapier is usually quicker to prototype with.
The general flow I envisioned:
- I add a new content topic to a specific database in Notion AI.
- Zapier detects this new entry.
- Zapier sends the topic to Claude Opus 4.7 with a detailed prompt.
- Claude Opus 4.7 returns a JSON object containing blog post titles, outlines, and social media drafts.
- Zapier parses this JSON and updates my Notion database, creating new entries for blog post ideas and social media drafts.
Before diving into the full automation, I did some manual prompt testing with Claude Opus 4.7 to get the output format just right.
Prompt I used in Claude:
You are a content marketing assistant for a tech blog called AIPowerStacks. Your goal is to generate compelling content ideas and social media posts for a given topic. Topic: "AI marketing trends for small business" Task:
1. Generate 5 unique and engaging blog post titles for the given topic. Focus on practical advice and actionable insights for small business owners.
2. For each title, create a 3 point outline (main headings only).
3. For the FIRST blog post title and its outline, generate 3 distinct social media posts: a. One for Twitter (max 280 characters, include 2 relevant hashtags) b. One for LinkedIn (professional tone, 3 4 sentences, include a question to encourage engagement) c. One for Instagram (short caption, use emojis, include 3 relevant hashtags) Output Format: Return the results as a JSON object with the following keys:
{ "blog_posts": [ { "title": "Blog Post Title 1", "outline": [ "Heading 1", "Heading 2", "Heading 3" ] }, // .. up to 5 blog posts ], "social_media_drafts": [ { "platform": "Twitter", "content": "Tweet content #hashtag1 #hashtag2" }, { "platform": "LinkedIn", "content": "LinkedIn post content..." }, { "platform": "Instagram", "content": "Instagram caption ✨ #hashtag1 #hashtag2 #hashtag3" } ]
}
The JSON output from Claude Opus 4.7 was clean and consistently formatted. This is critical for reliable automation. Honestly, this part always excites me the most: getting a machine to reliably spit out structured data.
Now, to the actual automation. I set up a Zapier workflow:
- Trigger: New Database Item in Notion.
- I created a Notion database called "Marketing Content Ideas". It has a simple 'Topic' property (text) and a 'Status' property (select: 'New', 'Processing', 'Done').
- When a new item is added with 'Status' as 'New', the Zap fires.
- Action: Send Conversation to Anthropic (Claude).
- I selected Claude Opus 4.7.
- I pasted my detailed prompt, dynamically inserting the 'Topic' from the Notion trigger.
- I set the model temperature low (0.3) to ensure less creative, more consistent output.
- Action: Parse JSON (Formatter by Zapier).
- This is a crucial step. I used Zapier's built in Formatter to parse the JSON output from Claude. This turns the raw JSON string into usable data fields.
- Action: Loop through Blog Posts (Looping by Zapier).
- I used a Loop step to iterate over each blog post entry in the `blog_posts` array parsed from the JSON.
- Inside the loop, another Notion step creates a new item in my "Blog Post Outlines" database, populating the 'Title' and 'Outline' properties dynamically.
- Action: Loop through Social Media Drafts (Looping by Zapier).
- Similarly, I set up a loop for the `social_media_drafts` array.
- This loop creates new items in my "Social Media Queue" Notion database, filling in 'Platform' and 'Content'.
- Action: Update Database Item in Notion.
- Finally, I updated the original "Marketing Content Ideas" item's 'Status' to 'Done'.
I ran a test with the topic "Latest trends in B2B content marketing". The Zap ran beautifully. In about 30 seconds, my Notion databases were populated with 5 blog post ideas, their outlines. And 3 social media drafts for the first idea. I was genuinely surprised by how smoothly it went for a first attempt.
Here's the interesting part: While the YouTube gurus talk about 97% automation, my workflow achieved perhaps 50% automation for this specific task. The ideas still need human review, editing, and expansion. But it cut out the blank page syndrome and the initial drafting time completely. For content creation, that's a massive time saver. You can check out Top 5 Free AI Tools for Content Marketing Budget 2026 to see how far free tiers can take you for parts of this process.
This is a common question, and one I get a lot when people ask about our track your AI spend feature. For my experiment, I used Claude Opus 4.7, which is a paid model. Notion AI also has paid tiers, though many of its basic AI features are available on its free plan. Zapier has a generous free tier that would cover this specific workflow for light use.
Many of the tools listed on AIPowerStacks offer free or freemium options. For example, Relevance AI, Shortwave, Mem AI, Poe, and Raycast AI all have free tiers. You could swap out Claude Opus 4.7 for a free LLM like Gemini via it's API, or even some of the local models if you have the compute power. The main constraint for free options often comes down to API call limits, rate limits, or smaller context windows, which might make the output less consistent or require more careful prompt engineering.
I would argue that for initial experimentation, free tools are absolutely enough. Once you prove the value, investing a small amount (like the average $13/mo for Notion AI users) for more powerful models and higher limits becomes a no brainer. It's a crawl, walk, run approach.
Practical AI Workflow for Social Media Content
My workflow generated three different social media posts for one blog post idea. This is just the start. You could extend this considerably.
- Audience Specific Posts: Instead of general LinkedIn, Twitter, Instagram, you could prompt Claude Opus 4.7 to create posts tailored for specific segments within your audience.
- Image/Video Prompts: Add another step to generate prompts for an image generation AI like Midjourney or DALL E 3 based on the social media text. Then, you'd feed those prompts to your chosen image tool. This is a path to what we discuss in New AI Video Studio Accessibility 2026.
- Scheduling Integration: Instead of dumping into a Notion database, the social media drafts could go straight to a scheduling tool like Hootsuite AI via Zapier, awaiting final human approval and scheduling.
The key here is that the modular nature of these AI tools, combined with integration platforms, allows for incredible flexibility. You can build out these tiny automations step by step, refining each piece as you go.
Avoiding Common Pitfalls in AI Marketing Automation
Based on my own trials and errors, and seeing what often goes wrong in discussions:
- Over automation: Don't try to automate 97% of your business from day one. Start small. Identify one truly repetitive, low risk task. My content ideation workflow is a good example.
- Vague prompts: "Write some social media posts" is terrible. "Generate 3 distinct social media posts: one for Twitter (max 280 characters, include 2 relevant hashtags), one for LinkedIn (professional tone, 3 4 sentences, include a question to encourage engagement), and one for Instagram (short caption, use emojis, include 3 relevant hashtags)" is much better. Specify format, length, tone, and audience.
- Ignoring quality control: AI output is rarely perfect. It needs human review and refinement. My workflow generates drafts, not final copy. Always factor in human oversight.
- Data silos: Make sure your tools can talk to each other. That's why Zapier or Make (Integromat) are so important. This is crucial for AI Workflow Integration for Marketing Teams 2026.
- Cost creep: It's easy to rack up API costs if you don't monitor usage. Keep an eye on your AI spend. Start with freemium tools and scale up as needed.
My experience is that the initial setup takes a bit of thought, but once it is running, the time savings are real. It's not about replacing humans, it's about empowering them to focus on higher value, creative tasks.
You can try this yourself. Browse 600+ AI tools on AIPowerStacks to find components for your own workflow. Start simple. Find a task that takes you 15 minutes a day, and try to automate even 5 minutes of it. The compound effect is what really matters.
FAQ
What is the easiest way to start automating marketing content?
The easiest way to start is by automating small, repetitive content generation tasks, like drafting social media posts or generating blog post titles. Use a no code automation tool like Zapier or Make (Integromat) to connect a content input (like a spreadsheet or Notion AI) to an LLM like ChatGPT or Claude Opus 4.7.
Yes, you absolutely can. Many powerful AI tools offer free tiers or generous freemium models, such as Poe or certain LLM APIs with limited usage. For orchestration, Zapier and Make (Integromat) also have free tiers that are sufficient for basic automations. The main limitation will be API call limits or context window sizes.
How much time can AI automation save for small businesses in marketing?
While claims of 97% automation are often exaggerated, even automating 10% to 30% of repetitive marketing tasks like content ideation, drafting, and preliminary research can save a small business significant time. This allows marketing teams to focus on strategy, creativity, and direct customer engagement, leading to better overall outcomes.
What's the difference between an AI chatbot and an AI agent in marketing?
An AI chatbot is primarily for interactive conversation, often answering questions or providing information. An AI agent, in the context of marketing automation, refers to an AI system designed to perform a sequence of predefined tasks autonomously, often by interacting with multiple tools or APIs. For example, a chatbot might answer a customer query, but an agent might generate a blog post outline, draft social media posts, and schedule them based on a single input, without continuous human prompting.
