Generative AI tools like ChatGPT can create content, but it doesn’t always sound natural.
Without the right guidance, the content can come across as dull or robotic.
Fortunately, there are techniques for making AI-written text more human-like, engaging, and fun to read.
This article explores ways to get more life-like, conversational content from AI.
Specifically, we’ll look at how to customize the prompts you give ChatGPT so it better understands the tone, emotion, and audience you want to target.
Prep your ChatGPT environment for stronger output
You need a user-friendly interface to interact with AI and refine the content it generates.
Most people are more familiar with OpenAI’s ChatGPT than other AI platforms (though you could also check out Anthropic’s Claude or Perplexity).
In this article, I’ll focus on guidance for ChatGPT, though many of these tips will likely be useful across multiple AIs.
To get the most out of the tool, sign up for ChatGPT Plus, which costs just $20 per month.
Subscribing gives you access to OpenAI’s more powerful models, including:
- GPT-4o.
- GPT-4.1.
- GPT-4.5.
Though slower than GPT-4o, GPT-4.1 and GPT-4.5 offer deeper reasoning and often generate longer, higher-quality content.
If you want faster responses but still prefer something more advanced than GPT-4o, the subscription also gives you access to o3 and o4-mini.
If you were generating tens of thousands of short snippets via OpenAI’s API, GPT-4o might be your best bet due to its speed.
But for our purposes, I recommend using GPT-4.1 or GPT-4.5. You could also experiment with o3.
Once you’re logged into ChatGPT and subscribed to ChatGPT Plus, you can select GPT-4.5 as your model of choice.
Dig deeper: How to blend AI and human input in your content approach
Let ChatGPT help you sound less like AI
You can begin by asking ChatGPT directly for help in terms of building your prompts (chat messages) so that they result in more human-like output:
Several of these listed items could prove extremely useful to us. Let’s explore this in more detail.
Building a sample blog post
You can start out with a simple prompt such as:
- “Please write a blog post on the benefits of solar energy instead of wind farms.”
ChatGPT will have a go at producing something, even without too much direction:
This is fine, but it’s not too detailed and could sound “more” human.
It’s also too short and lacks defined subsections and subheadings. So far, we have defined:
- A topic.
- A content type (e.g., blog post).
What else can we define? Here are some key options:
- Ask ChatGPT to include headings and subheadings for better structure.
- Add specific details. For example, the author’s goal is to persuade authorities to build more solar farms, since wind farms are often noisy and visually intrusive. You could also note that solar farms may be easier to maintain, as they have no moving parts.
- Request a conversational tone – technical and informative, but with a bit of creative flair to avoid sounding dry.
- Aim for emotional impact. For instance, you might want readers to strongly support solar energy over wind power.
- Ask for examples and analogies to make the writing more relatable, or suggest using a storytelling approach to increase engagement.
- Define the audience so ChatGPT can tailor the reading level. In this case, the audience could include the general public and renewable energy decision-makers, so the content should be clear but persuasive.
- Set a target word count. ChatGPT won’t be exact, but it usually gets close. Here, aim for 1,000 to 1,200 words.
Adjusting and enriching your prompt
Now that we’ve identified key details to include, it’s time to put them to work.
To do that, we’ll need to fully restructure the prompt to incorporate all the essential elements.
As you can see from the above, we have accounted for all the details and elements we wished to add to our prompt.
There’s a lot more detail here than there was at the start.
The prompt has expanded from 15 to 220 words (over 1,100 characters). This is roughly what you should be aiming for. Now it’s time to process our new prompt.
Dig deeper: Advanced AI prompt engineering strategies for SEO
Results from an enriched human-centric prompt
It’s immediately obvious that the AI is responding in a more human, more structured way, complete with formatted headings:
You can view the complete 930-word blog post here.
It isn’t quite as long as we wanted, but it’s close to our target length (ballpark accurate).
Iterating and refining the content
Remember that you’re interacting with AI via a chat interface to iterate and refine the AI’s output.
You could process follow-up prompts such as:
- “This is really great, but it’s not quite long enough. Can you expand on a few points to make the word count slightly longer?”
- “I really like this post, but I feel that the writing tone is too informal. Please make the content sound a bit more formal and fact-driven.”
- “Please rewrite the post in the style of [famous editor or well-known columnist name].”
- “Please add a bullet point summary at the top of the post.”
As you can see, there are a number of ways to refine your AI-generated content:
Once you are done refining, your content is complete.
You can enhance it with your human creative spice, fact-check the produced content, and ensure that formatting matches your expectations.
Dig deeper: The art of AI-enhanced content: 8 ways to keep human creativity front and center
Alternative AI platforms and chatbots
ChatGPT isn’t your only option:
- Claude by Anthropic: While often slower than OpenAI’s models, Claude (e.g., Claude 3.7 Sonnet, Claude 4 Sonnet) excels at writing. For long-form content, I sometimes prefer it over ChatGPT.
- Perplexity: A solid choice, especially for research-driven queries.
- Sonar: Built by the team behind Perplexity, Sonar is particularly strong for coding tasks.
- Google’s Gemini: Evolved from the Bard project, Gemini can sometimes process larger inputs more quickly (depending on the model). That said, its output isn’t always as strong.
Don’t overlook the limits of AI-generated content
AI can be incredibly helpful, but it still has blind spots.
You’ll often need to fact-check or apply a human editorial lens to its output. One recurring issue is hallucination, where AI infers details that weren’t provided.
For example, if you ask it to include specs for a brand-new product, it might substitute data from a similar item it already “knows,” leading to inaccuracies.
In 2025, retrieval-augmented generation (RAG) helps reduce this by enabling AI to fetch real-time information from the web.
However, RAG has its own risks.
AI crawlers aren’t as sophisticated as traditional search engines, so they may surface misinformation, spam, or low-quality sources.
That’s why a human-in-the-loop process is still essential.
Also, avoid overly abstract or ambiguous prompts. AI performs best when it is given clear, grounded direction.
Enhancing AI-generated outputs
To get better results from AI:
- Lean on the most advanced models available (e.g., GPT-4.5 or Claude Sonnet 4), especially for long-form content. These tools are more capable of producing detailed, natural-sounding output.
- Refine prompts for human-centric results: Be specific. Include the article’s purpose, desired tone (e.g., informative but conversational), emotional impact, intended audience, and any relevant examples. For instance, you might ask the AI to write persuasively about solar energy while gently contrasting it with wind power’s drawbacks.
- Use the iterative nature of AI: Don’t expect perfection on the first try. Prompt, review, and revise. You might start with a general draft, then refine for tone, structure, or clarity – just as you would when collaborating with a human writer.
- Recognize where AI needs support: Even strong models can produce generic, vague, or factually shaky content. You’ll often need to fact-check and apply a human editorial lens. That final polish makes the difference between usable and publishable.
- Apply AI to a range of content types: It’s not just for blog posts. Use it for internal documentation, onboarding materials, and even print assets. Just tailor your prompt to suit the format and channel.
- Aim for emotional and visual resonance: Look for content that evokes feelings or paints a picture. A comparison, anecdote, or metaphor can make content more human.
- Balance technical accuracy with creative flair: Complex ideas shouldn’t come across as dry or inaccessible. Direct the AI to use everyday language alongside clear explanations or analogies.
- Encourage narrative and example-based structure: A storytelling approach – anchored by real-world examples or step-by-step breakdowns – often results in more compelling and memorable output.
- Adjust for audience and use case: Whether your readers are decision-makers in clean energy, everyday consumers, or technical professionals, make sure the AI adapts accordingly. One-size-fits-all won’t cut it.
And if you’re not using AI for full-length articles? It’s still incredibly useful for summarizing, reformatting, or condensing human-written material – quickly and efficiently.
Dig deeper: 3 ways to add a human touch to AI-generated content