LinkedIn Posts
LinkedIn posts written for
AI Search to cite
ChatGPT cites LinkedIn. When a client asks ChatGPT for a product or service recommendation, LinkedIn posts and company pages are among the sources it references most. Simaia writes LinkedIn posts in the specific format LLMs extract, declarative statements, named facts, structured comparisons, and posts them directly to your company page. No login. No brie2f. No approval needed.
Trusted by Founders and Growth Leaders in APAC
Why format determines citation rate
High engagement and high citation rate
require different formats
Engagement-optimized LinkedIn posts use hooks, questions, numbered lists, and emotional framing to drive comments and shares. They perform well for human reach metrics. ChatGPT reads them and finds nothing specific enough to extract into an answer.
LLM-optimized posts state specific operational facts, name real products and prices, and structure information so a model can lift it directly into a response to a buyer query. The same company, the same topic, written differently, produces a measurable difference in how often ChatGPT cites the post in buyer answers.
LLM-optimized structure
Declarative statements, named entities, specific prices and timeframes. Written to be extractable, not just readable.
Client-language targeting
Written using the exact terms potential client type when searching for solutions in your category, not your internal product language.
15 posts per month on Starter, unlimited on Leader
Each post targets a specific buyer query from your prompt tracker audit.
Posted directly to your LinkedIn company page
Simaia posts to your page. You see the posts in your monthly report. No login or content approval required.
FAQ
Common questions about Simaia LinkedIn Post
Why does ChatGPT cite LinkedIn specifically for B2B recommendations?
ChatGPT has been trained on a large portion of publicly available LinkedIn content and continues to retrieve current LinkedIn posts via web search when composing answers. For B2B categories, LinkedIn is treated as a high-trust source because it contains professional, specific, named claims from verified companies. Posts with specific operational facts, prices, and comparisons are frequently cited in ChatGPT responses to buyer recommendation queries.
What is the difference between LLM-optimized and engagement-optimized LinkedIn posts?
Engagement-optimized posts are written to drive human interaction: hooks, questions, emotional framing, and calls to comment. LLM-optimized posts are written to be extracted by AI models: specific named facts, operational details, prices, and structured comparisons. The same topic written in both formats produces measurably different citation rates. A post asking "what do you think about private jet travel?" earns more comments. A post stating the specific turnaround time at Bali Ngurah Rai airport earns more ChatGPT citations.
What signals does ChatGPT use to decide which LinkedIn posts to cite?
ChatGPT favours LinkedIn posts that contain specific, verifiable claims rather than general opinions or questions. Named companies, specific prices, timeframes, or operational facts are extracted more reliably than posts built around engagement tactics. Simaia writes every post with the former structure, targeting the specific buyer queries identified in the audit.
Does Simaia post to my personal LinkedIn or my company page?
Simaia posts to your LinkedIn company page. During onboarding, you provide Simaia with posting access to your company page. All posts appear on your company page under your company name. Simaia does not post to personal profiles.
How does Simaia decide what to write about for LinkedIn?
Every LinkedIn post targets a specific buyer query identified in your AI search audit. Simaia writes a LinkedIn post specifically addressing that topic with the operational specifics ChatGPT extracts. The audit determines the topic. The LLM-optimized format determines whether it gets cited.