My Agent Work: How Im Using Automation for Impact

Hey everyone, Ryan here from agntwork.com. Hope you’re all doing well. Today, I want to talk about something that’s been on my mind quite a bit lately, especially as my own little corner of the internet continues to grow and, frankly, get a bit messier without some intervention. We’re going to dig into automation, but not in the usual “AI will take your job” kind of way. Instead, I want to focus on how we can use automation to make our human work more impactful, specifically by tackling the often-dreaded task of content repurposing.

If you’re anything like me, you’re constantly creating. Blog posts, social media updates, newsletters, maybe even short videos. And if you’re also like me, you often look at that amazing long-form blog post you just poured your soul into and think, “Man, this would be great as a series of tweets… or a LinkedIn carousel… or a short video script…” And then you don’t do it. Or you do it, but it takes you an hour when it should take ten minutes. Sound familiar?

That’s where intelligent automation comes in. Not to replace your creative spark, but to act as your tireless, always-on intern, ready to slice, dice, and reformat your content for different platforms and audiences. I’m talking about turning one piece of stellar content into five or six different assets, almost on autopilot. And no, you don’t need to be a coding wizard to make this happen. A good understanding of how to connect a few tools and a dash of AI know-how is all it takes.

The Content Repurposing Bottleneck: My Own Story

Let me tell you about my own struggles. A few months ago, agntwork.com hit a pretty good stride. My long-form articles were getting decent traction, but I knew I was leaving a ton of potential engagement on the table by not consistently pushing snippets and variations to LinkedIn, X (formerly Twitter), and even my weekly newsletter. I’d finish an article, breathe a sigh of relief, and then immediately dread the hour-long slog of manually extracting key points, rewriting them for character limits, finding relevant hashtags, and scheduling everything.

It was a massive bottleneck. My content calendar would look great for blog posts, but the social media column would often be filled with “TBD” or, worse, just blank. I tried batching – dedicating a whole afternoon to repurposing – but that just led to burnout and often, less-than-stellar content because I was rushing. I needed a better way. I needed to automate the busywork so I could focus on the creative decisions and the overall strategy.

My goal wasn’t to eliminate my involvement, but to offload the repetitive, mind-numbing stuff. I still wanted to review the final output, tweak a headline, or add a personal touch. The machine’s job was to give me a high-quality draft, not to publish something without my oversight. This distinction is crucial for successful AI-powered automation.

Building Your Content Repurposing Machine: The Core Components

So, what does this “machine” look like? At its heart, it’s a series of connected tools, often orchestrated by an automation platform like Make (formerly Integromat) or Zapier, with a large language model (LLM) doing the heavy lifting of content transformation. Here’s a breakdown of the typical components I use:

• Content Source: Where your original content lives. For me, it’s my blog’s CMS (WordPress) or a Google Doc where I draft posts.
• Automation Platform: Make or Zapier. This is the glue that holds everything together. It watches for new content, triggers the AI, and sends the output to your various destinations.
• Large Language Model (LLM): OpenAI’s GPT models (or similar). This is where the magic happens. It takes your long-form text and transforms it into different formats based on your instructions.
• Destination Platforms: Your social media scheduler (e.g., Buffer, Hootsuite), email marketing platform (e.g., ConvertKit, Mailchimp), or even just a Google Sheet for review.

Example 1: From Blog Post to LinkedIn Carousel Script

Let’s get practical. One of the most effective ways I’ve found to repurpose blog posts is by turning them into LinkedIn carousels. These grab attention, encourage scrolling, and deliver value in bite-sized chunks. Here’s a simplified workflow I set up:

1. Trigger: New blog post published on WordPress. (Make detects this via an RSS feed or WordPress module.)
2. Action 1 (Retrieve Content): Make pulls the full content of the new blog post.
3. Action 2 (AI Transformation): Make sends the blog post content to OpenAI’s API with a specific prompt.
4. Action 3 (Review & Refine): The AI’s output (a draft carousel script) is saved to a Google Doc or sent to me via Slack for review.
5. Action 4 (Manual Polish & Scheduling): I review, make any necessary tweaks, and then create the actual carousel images and schedule them. (This last step is still manual, but the heavy lifting of drafting is done.)

The key here is the prompt you give the LLM. It needs to be clear, specific, and provide context. Here’s an example of a prompt I might use for a LinkedIn carousel:

"You are a content strategist specializing in LinkedIn engagement.
I have a blog post about [TOPIC].
Please extract 5-7 key takeaways or actionable tips from the following blog post content.
For each takeaway, create a concise slide title (max 60 characters) and 2-3 bullet points or a short paragraph (max 200 characters) of explanatory text suitable for a LinkedIn carousel slide.
Also, suggest an engaging opening slide title and a strong call-to-action for the final slide.
The goal is to provide value, encourage interaction, and drive traffic back to the original blog post.

Blog Post Content:
[FULL BLOG POST CONTENT HERE]
"

This prompt tells the AI its role, the desired output format, character limits, and the overall goal. The output isn’t perfect every time, but it’s usually 80-90% there, saving me hours of initial drafting.

Example 2: Blog Post to X (Twitter) Thread

Another high-impact repurposing strategy is creating X threads. These are great for breaking down complex ideas into digestible tweets and building anticipation. The workflow is similar to the LinkedIn carousel, but the AI prompt changes significantly.

1. Trigger: Same as above – new blog post published.
2. Action 1: Retrieve blog post content.
3. Action 2 (AI Transformation): Send content to OpenAI with a thread-specific prompt.
4. Action 3 (Review): AI output (draft thread) saved to Google Doc or Slack.
5. Action 4 (Manual Polish & Scheduling): I review, add emojis, refine wording, and schedule using Buffer or similar.

Here’s a prompt tailored for an X thread:

"You are a social media manager expert in crafting engaging X (formerly Twitter) threads.
I have a blog post titled '[BLOG POST TITLE]' about [TOPIC].
Please create a 5-7 tweet thread based on the content below.

Rules for the thread:
- Start with an attention-grabbing hook tweet (Tweet 1/X).
- Each subsequent tweet should build on the previous one, delivering a single key point or tip.
- Keep each tweet concise (ideally under 240 characters) to allow for user interaction.
- Incorporate relevant hashtags naturally where appropriate (suggest 2-3 per tweet).
- End the thread with a clear call-to-action to read the full blog post.
- Ensure a natural flow and narrative throughout the thread.

Blog Post Content:
[FULL BLOG POST CONTENT HERE]
"

Again, the AI won’t always nail the tone or the perfect hashtag, but it provides a solid foundation that I can quickly polish. This is about augmentation, not replacement.

My Personal Experience and What I’ve Learned

When I first started playing with this, I was overly ambitious. I tried to automate everything, including the final publishing step. That led to some awkward posts going out without my review – a definite “learning experience.” Now, I’ve pulled back and focused on automating the initial drafting and formatting. My rule of thumb is: if it requires subjective judgment or creative flair, I want to be the final editor.

Another lesson: garbage in, garbage out. The quality of your original content and the clarity of your AI prompts directly impact the usefulness of the automated output. If your blog post is vague, the AI will struggle to extract concrete takeaways. If your prompt is ambiguous, you’ll get generic results.

I’ve also realized the importance of iteration. My prompts today are far more sophisticated than they were six months ago. I constantly experiment with different phrasings, role-playing for the AI, and specific constraints (like character limits or desired tones). It’s an ongoing optimization process.

The biggest win for me isn’t just saving time; it’s the consistency. Before, I’d repurpose content sporadically. Now, with these workflows in place, every new blog post automatically kicks off a chain of events that leads to a draft LinkedIn carousel, an X thread, and even a few bullet points for my newsletter. My social channels are more active, my content gets more mileage, and my overall engagement has seen a noticeable bump. And crucially, I’m not feeling that constant dread of the repurposing chore.

Actionable Takeaways for Your Own Automation Journey

Ready to build your own content repurposing machine? Here’s where to start:

1. Identify Your Repurposing Pain Points: What content do you create regularly that you wish you could easily transform for other platforms? Start with one or two high-value transformations (e.g., blog to LinkedIn, video transcript to blog summary).
2. Choose Your Tools Wisely: If you’re new to automation, start with a user-friendly platform like Zapier. If you need more complex logic and better control, Make is a fantastic option. For the AI, OpenAI’s API is a solid choice.
3. Start Simple with Your Prompts: Don’t try to create the perfect prompt on day one. Begin with clear instructions, desired output format, and any constraints. Iterate and refine as you see the results. Think like you’re giving instructions to a new assistant – be specific!
4. Automate Drafting, Not Publishing (Initially): Focus on getting a high-quality draft from your AI. Always put a human in the loop for review and final approval, especially when you’re starting out. This builds trust in your system.
5. Measure and Refine: Pay attention to which repurposed content performs best. Is your LinkedIn carousel getting more clicks than your X thread? Use that data to inform how you refine your AI prompts and overall workflows.
6. Don’t Be Afraid to Experiment: The beauty of these no-code/low-code platforms is that you can try things out quickly. Set up a basic scenario, test it, tweak it, and learn. It’s an ongoing process of discovery.

Automating content repurposing isn’t about eliminating the human touch; it’s about amplifying it. It frees you from the mundane, allowing you to focus on the strategic, creative work that truly moves the needle. So go on, give it a try. Your future self (and your content calendar) will thank you.

Until next time, keep building those smarter workflows!

🕒 Published: May 2, 2026