When Ithy generates an article for you, it doesn't just produce a block of text. Instead, it creates a well-structured document with various elements designed to enhance readability, convey information effectively, and provide a rich user experience.
Understanding these components will help you better interpret and utilize the articles you generate.
General Article Structure
Generated articles typically follow a consistent and logical structure:
Title (H1 Tag):
This is the main heading of your article, usually a direct reflection or a concise summary of your original question or prompt. It's given the highest heading level (H1) for semantic importance and visual prominence.
Often styled with a distinct color and larger font size.
Subtitle (H3 Tag):
Below the main title, you might find a subtitle (often an H3 tag). This can provide additional context, a slight elaboration on the title, or set the scope for the article.
Introduction Section:
Most articles begin with an introductory paragraph or section. This part aims to set the stage, define the topic, and briefly outline what the article will cover. It helps to orient the reader.
Main Content Sections with Headings (H2, H3, H4 Tags):
The core of the article is broken down into multiple sections, each focusing on a specific aspect of the topic.
These sections are clearly delineated by headings of various levels (H2, H3, and H4). This hierarchical structure helps in organizing complex information and allows for easy scanning and navigation.
Ithy often uses distinct color-coding for different heading levels (e.g., H2 might be one color, H3 another), further aiding visual organization.
Paragraphs of Text:
Within each section, information is presented in well-formed paragraphs. The AI strives for clarity, coherence, and grammatical correctness.
Lists (Bulleted and Numbered):
For presenting key points, steps in a process, features, pros and cons, or any enumerated information, Ithy frequently uses:
Bulleted Lists (
<ul>): For items where the order isn't strictly critical. Often styled with custom bullet points, background colors, or borders for visual appeal.Numbered Lists (
<ol>): For sequential information, steps, or rankings.
These lists help break up dense text and make specific pieces of information stand out.
Conclusion or Summary Section:
Many articles will end with a concluding section that summarizes the main points discussed, offers final thoughts, or suggests potential implications.
Common Visual and Content Elements
Beyond the basic structure, Ithy articles can include a variety of specialized elements, especially if enabled in your Account settings (see "Your Account > Custom Settings"):
Images (
<img>tags):If the "Images" setting is enabled, and the AI deems it relevant, images may be embedded within the article.
These images are typically sourced from Google Images or other providers based on the article's content.
Ithy usually processes these images: they are resized to appropriate dimensions for the article layout and compressed to optimize loading times. They are also styled to be responsive, meaning they adjust to different screen sizes.
Highlighted Sections or Callouts:
Important information, key definitions, or significant data points might be presented in highlighted boxes or with distinct background colors to draw the reader's attention.
Links (
<a>tags):Articles may contain hyperlinks to external websites, source materials, or further reading.
Ithy often includes custom styling for links.
The platform may attempt to verify external links. If a link is found to be broken or inaccessible (returning non-2xx status codes, excluding 403 which might be a temporary block), the link functionality (href attribute) might be removed, and the link text could be displayed with reduced opacity to indicate it's not an active link.
Code Blocks (
<pre><code>tags):If your query relates to programming, software development, or any topic involving code, the AI will format code snippets within
<pre>(preformatted text) and<code>tags. This preserves indentation and monospaced fonts, making the code readable.
Frequently Asked Questions (FAQ) Section:
If the "FAQ section" toggle is enabled in your visual settings, the AI may generate a list of frequently asked questions related to the topic, along with their answers. This can be a very useful summary or way to address common follow-up queries.
YouTube Video Results/Embeds:
With the "YouTube results" toggle enabled, the article might include summaries of relevant YouTube videos, links to them, or even embedded video players (depending on the platform's exact implementation).
Radar Charts:
If the "Radar diagram" toggle is on and the topic lends itself to comparative analysis (e.g., comparing features of different products), a radar chart might be generated to visually represent this data.
Mind Maps:
With the "Mind map" toggle enabled, the AI might generate a mind map to visually organize concepts, relationships, or brainstorming ideas related to your query.
Citations and References:
The AI may attempt to include citations or a list of references, especially for academic or research-oriented topics. The format and completeness can vary. It's always good practice, especially for academic use, to verify these citations and ensure they meet the required standards.
Individual AI Responses
For users interested in the individual AI responses Ithy aggregates for its articles, Ithy provides access to a "Question View" page for previously generated articles. This page can be reached via your account page. This view displays:
Your original query.
The individual, raw responses from the different AI submodels that contributed to the article (e.g., responses from AI based on Perplexity, Google, OpenAI, xAI, Claude, etc.). Each response is typically presented in a copyable block. This detailed breakdown is invaluable for comparing how various AI perspectives approached your topic and can also show the generation time for each component.
By familiarizing yourself with these structural and content elements, you can navigate and interpret your Ithy articles more effectively, extracting the maximum value from the AI-generated research.