How to use firsthand information in WordPress AI articles

Choose the reader's question before supplying your company introduction

To create an AI article in WordPress, first choose one question to answer, then provide the company information that supports the answer. A longer company introduction does not necessarily give readers more useful evidence. Use your mission, vision and values to explain how you make decisions, and case studies to describe specific experiences. Keeping these roles distinct makes a draft easier to review.

For example, a reader asking what to check before publishing an AI article needs your actual review process, the person responsible and the problems that review has uncovered. They do not need your entire company history. Leave gaps unverified and turn them into questions for the person who can answer them.

This article uses Rootpublish's input fields and editorial principles to illustrate how company experience can become evidence for an article. It is not a measured case study of better search rankings or AI citations.

Give values, concepts and case studies different roles

Your mission, vision and values explain what the company aims to achieve and how it makes decisions. A commitment to customer outcomes does not establish that every customer's revenue increased. When describing a principle, explain what it prioritizes in practice.

Your concept helps define whose problem you address. A specific audience and scope make it easier to select relevant topics.

Member introductions should use work the person actually performed and experience that can be verified. Adding a profile does not make that person the author or reviewer of an article. Check the wording of qualifications and job titles too.

For a case study, record the problem, the action, the result and the conditions under which that result was verified. Do not turn one company's outcome into a promise for every customer. Product and service information explains what is offered and under which conditions. Every article does not need all of these inputs.

A template for organizing firsthand information

Complete the following fields for each piece of information you want to use. This is a preparation template. Keep missing information visible and identify who can verify it, rather than letting AI fill the blanks.

• Information type: mission, vision and values / concept / member / case study / service
• Verifiable content: what was actually decided, done or offered
• Subject and date: who the information concerns and when it was true
• Conditions and scope: terms of use, coverage, exceptions and unknowns
• Source and verification contact: original material, recorder and responsible person
• Publication permission: public as written / anonymization needed / private
• Question it can answer: what this information helps the reader decide

For case studies, separate what you did from what changed. Before including a number, verify the measurement period and comparison. Check whether client names and personal information can be published, and keep private original material out of AI inputs.

In Rootpublish, add the organized material to company information, with its source and verification status. Confirm only information that may be used as evidence. Exclude unverified and private information from the draft's evidence.

An example using Rootpublish's own product specification

A real product specification can become a source record. There is no need to invent a customer case or a performance number.

• Information type: service
• Verifiable content: Rootpublish records the versions of company information referenced by a draft and checks for changes during approval
• Subject and date: Rootpublish 0.1.10 implementation, checked on September 14, 2026
• Conditions and scope: matching versions does not guarantee that the text's meaning matches its evidence
• Source and verification contact: company-information validation, draft validation and approval logic
• Publication permission: public product specification
• Question it can answer: how to prevent an old draft from being published unchanged after its source information is updated

This supports an explanation that approval detects changes to company information. It does not support claims that the product prevents every AI error or eliminates review. Recording both the mechanism and its limits helps readers decide whether it suits their workflow.

Build the instruction to your own AI around evidence

Include the reader's question, permitted information, exclusions and review requirements. For example:

• Question: what should we check before publishing an AI article in WordPress?
• Reader: a website manager turning company case studies into articles
• Permitted information: verified service specifications and operational records approved for publication
• Exclude: undocumented achievements, invented numbers, unverified reviewers and ranking guarantees
• Output: answer the question first, explain the reasoning and steps, and identify the source used by each paragraph
• Missing information: return questions for the responsible person instead of guessing

Rootpublish can prepare drafts through the user's own AI API or a supported MCP host. MCP requires the connected AI to be running; connecting it does not make a stopped AI keep producing articles. Define the scope of automation together with how the AI will run.

Compare each claim with its source before publishing

Review more than readability. Check whether the scope of each claim matches its evidence:

• Does the introduction answer the reader's question?
• Does each factual paragraph have evidence that supports it?
• Are principles or goals being presented as achieved results?
• Do the period, subject and comparison behind each number match the source?
• Is a member introduction being mistaken for authorship or review?
• Are publication permissions for company names, personal names and cases respected?
• Can the reader identify what to check or do next?

Rootpublish separates draft submission from publication approval, and checks for changes to the company information and editorial policy used. A source ID alone does not establish that a paragraph is correct. Keep a step that compares the draft with its original sources.

Make AI-search content useful to the reader

Google's guidance emphasizes accuracy, quality and relevance for content created with generative AI. Large-scale generation without added value needs care. The purpose of firsthand information is to answer readers' questions with specific evidence, rather than simply producing more text.

Reference: Google Search Central — Guidance on using generative AI content on your website

For Google's AI Overviews and AI Mode, established SEO fundamentals remain relevant. Dedicated AI text files or special structured data are not requirements. Meeting requirements and appearing in search results are different things. Do not treat this as a specification shared by every AI service, or as a guarantee of citations or rankings.

Reference: Google Search Central — AI features and your website

Start with one question that your own experience can answer and one article whose evidence can be checked. After publication, use available search data and reader feedback to improve explanations that are missing.