In this blog, I’ll guide you through the process of building an advanced AI-powered blogging and social media agent. This system can generate fully formatted WordPress posts, complete with internal links and relevant YouTube videos, all while utilizing powerful AI tools to streamline your content creation.
I created an automation that serves as an AI blogging and social media agent. This tool can generate fully formatted WordPress posts, complete with internal links, relevant YouTube videos, and stunning images. Each article is thoroughly researched and includes accurate links to sources. Users can interact with the agent through text, voice notes, and images, making it a versatile tool for content creators.
This automation operates through Telegram, enabling seamless communication and command execution. It also allows for bulk generation of posts via an Airtable base, where users can approve social media text before triggering the posts. This entire system is built without any coding, relying on N8N to connect various tools and workflows.
Key Features
- Generates fully formatted WordPress posts with internal linking.
- Integrates relevant YouTube videos and AI-generated images.
- Allows interaction through text, voice notes, and images via Telegram.
- Supports bulk post generation through Airtable.
- Utilizes OpenAI’s GPT-4 for content generation.
Demo
I’ll walk you through a demo of how to use this agent effectively. The first step involves sending a voice message to request a list of keywords related to current AI news. The agent processes this request and responds with both a voice note and a text note, providing relevant keywords and current news highlights.
For instance, when I ask, “Can you write an article on the future of generative AI?” the agent suggests a title and prompts for any specific instructions or points to include. This interaction showcases the agent’s adaptability and responsiveness to user input.
Once the title is approved, I can request an AI-generated image to accompany the article. The process is straightforward. I simply respond with instructions, and the agent generates an image based on my request. This image is created using advanced AI technology, ensuring high quality.
After confirming the image, I instruct the agent to write the article. The article is then generated and uploaded to a test website in draft mode. This allows me to review and make any necessary edits before publishing. The agent also adds a relevant YouTube video and internal links to enhance the article.
Reviewing and Approving Content
Once the article is created, the agent prompts me to approve the text and imagery for social sharing. By clicking on the provided Airtable link, I can review each social media post’s draft text. This step is crucial for ensuring that the content aligns with my brand voice and messaging.
When I’m satisfied with the text, I can trigger the posts to go live. The automation allows for instant triggers that push the content to various social networks. Alternatively, I can use a simple button in Airtable to initiate the process. This flexibility makes it easy to manage social media content efficiently.
Agent Workflow
The workflow for this AI agent is built using N8N, starting with a trigger from Telegram. Although I’ve focused on Telegram, the system can be easily adapted for other messaging platforms like WhatsApp and Slack. Setting up the Telegram bot involves obtaining an access token from the BotFather channel, which allows the agent to receive messages.
Once the bot is set up, I can create a scenario in N8N that listens for messages. A filter is established to ensure that only messages from authorized users are processed, enhancing security. The workflow separates incoming messages based on their type—text, audio, or images—using a switch statement. This organization allows the agent to respond appropriately to different types of input.
For audio messages, the agent retrieves the file and sends it to OpenAI for transcription. This transcription allows users to interact with the agent using voice commands. The resulting text is then combined with any other relevant data to create a cohesive response.
Each interaction with the agent is stored in memory, allowing it to recall previous conversations and maintain context. This feature makes the agent more intuitive and user-friendly. Setting a session ID for each user ensures that interactions remain personalized and secure.
Agent Tools
To enhance the capabilities of my AI agent, I integrated multiple tools that streamline the content creation process. Initially, I added the AI agent to my workflow by simply dragging it into the canvas. The next step involved selecting a chat model, specifically the OpenAI GPT-4 model for its advanced understanding of context and language.
After assigning the model, I configured the credentials for OpenAI, ensuring that the agent could access the necessary resources. This setup allows the agent to remember past interactions, facilitating a more conversational experience.
Additionally, I granted the agent access to various tools like Perplexity, which provides live web access and a language model for enhanced research capabilities. By utilizing HTTP request tools, I set up specific functionalities for tasks such as researching topics and generating keywords.
For effective keyword generation, I created a dedicated tool within my workflow that generates a list of relevant keywords based on the provided topic. This tool ensures I have both short-tail and long-tail keywords, which are crucial for SEO optimization. Although I could use more advanced tools like Data for SEO, this simpler approach suffices for many use cases.
Blog Writing Workflow
The blog writing workflow is designed to be efficient and user-friendly. After initiating the AI agent, I provide an article title and any specific instructions. The agent then generates an outline based on the topic, which I can review and tweak as necessary.
Once the outline is approved, the agent proceeds to create the full article. It utilizes the previously defined tools to pull in relevant data, including internal links and citations from Perplexity. The process is streamlined, allowing me to focus on content quality rather than the technical details of the workflow.
After the article is created, I can review it within Airtable, where all drafts are stored. This centralized storage makes it easy to manage multiple articles simultaneously. I check for any necessary edits, ensuring that the content aligns with my brand voice before publication.
Posting to Social Media
Once the article is finalized, the next step involves creating social media posts to promote the content. The AI agent generates tailored posts for various platforms, including Facebook, Twitter, Instagram, and LinkedIn. Each of these posts is crafted to align with the specific audience and format of the respective platform.
I have set up a structured output parser to ensure the social media text is organized and easy to digest. This structured approach allows me to customize the tone and style of each post while ensuring they capture the essence of the article.
After generating the social media content, I can choose to either post immediately or schedule the posts for later. This flexibility is crucial for maintaining a consistent online presence without overwhelming my audience with content all at once.
Finally, I update the status in Airtable to reflect that the social posts have been created. This tracking mechanism helps me manage my content calendar effectively and ensures that I can easily revisit any post if needed.
AI Agent Responses with Text & Audio Messages
The AI agent is designed to respond to user inputs in various formats, including text and audio messages. When the agent finishes processing a task, it sends a response back through Telegram. This process is efficient and user-friendly, ensuring that I receive the information I need promptly.
For text messages, the agent uses a specific Telegram node to send the output directly. It pulls in the chat ID from the initial trigger, which ensures that the message reaches the correct user. Once the message is sent, I can view the response in the chat, making it easy to follow the conversation.
If the input was an audio message, the agent generates an audio response using OpenAI’s capabilities. The process involves selecting the appropriate audio resources and formatting the output to include both audio and text. This dual response allows for a richer interaction experience.
Mapping the binary data from OpenAI for audio ensures that I receive a high-quality audio message. The agent sends the audio file along with the text message, providing me with both formats for convenience. This flexibility enhances communication, allowing me to engage with the agent in the way that suits me best.
Additionally, if the message contains images, the agent extracts those from the output and sends them as photo messages. This feature is particularly useful for sharing visual content quickly. The automation aggregates all these responses into a cohesive output, ensuring nothing is missed.
