Question

How to Build a Better AI Content Generation Workflow?

When using AI for writing, we often encounter issues where the generated content feels too stiff. So, how can we optimize the workflow for using AI to generate content?


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Bobby Iliev
Site Moderator
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September 4, 2024

Hey,

Here’s a tip: Use AI to generate ideas, but don’t skip the human touch. Take the time to actually write your own content and polish the content, so it really resonates with your audience. This way, you’re not just saving time for yourself but also respecting your readers’ time by offering them something worth reading.

Think of it this way: If you use AI to create text in a minute that takes five minutes to read, but it doesn’t add real value, it’s like holding up the line at a store for something that could have been handled better. Your readers will appreciate the extra effort, and your content will be much stronger for it.

On the AI/ML note, GPU Droplets are now in Early Availability! You can sign up for them here:

https://www.digitalocean.com/products/gpu-droplets

- Bobby

KFSys
Site Moderator
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September 5, 2024

Heya,

The most important rule in my observation is to formulate your questions properly and even ask multiple questions not just one.

Also, what I do is take whatever I need from the a couple of responses and build it together.

Hope that helps.

Building a better AI content generation workflow involves combining the right tools, strategies, and expertise. At Kellton, we leverage AIML solutions to create robust, efficient, and scalable content generation processes. Here’s an approach to consider:

  1. Data Preparation: Start with high-quality, diverse datasets. The success of any AIML solution relies on well-structured and relevant data.
  2. Model Selection: Choose or fine-tune AIML models tailored to your content needs, such as GPT-based models for natural language generation.
  3. Workflow Automation: Integrate AIML solutions with automation tools to streamline content creation, editing, and distribution.
  4. Human-in-the-Loop (HITL): Maintain quality by incorporating human oversight to review and refine AI-generated content.
  5. Continuous Improvement: Use analytics to measure content performance and train your models continuously for better results.

By adopting this approach, Kellton helps businesses enhance their content generation workflows and achieve higher productivity with AI-driven solutions.

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