The "How did you write this?" Moment.
In a world of automated noise, earning a prospect's respect is the highest conversion metric.
This isn't the result of a generic AI prompt. It’s the result of GTM Engineering:
-Understanding a prospect's product better than their own competitors.
-Reaching out exactly when it matters, with the right context.
-Writing so well that a cold prospect actually sends you a connection request.
Stop the manual "violence". Build an unfair advantage.
He wasn't writing for you. He was writing for ChatGPT.
Profile views tripled anyway. Inbound doubled.
If you're a consultant or founder posting three times a
week, getting likes, and still waiting on inbound, this is the ranking game
you're not playing.
AEO. Answer Engine Optimization.
Someone types a question into ChatGPT Search or Google AI
Overviews. The answer comes with sources. LinkedIn posts are on that list.
Semrush ran 325,000 prompts. LinkedIn showed up in 14% of
ChatGPT Search answers.
Most of those citations went to individual profiles, not
company pages. Half came from accounts under 10,000 followers.
Quotability beat follower count.
What gets quoted (steal this):
1. One question per post
→ Line one is the
exact question a buyer would type into ChatGPT.
2. A plain-English definition inside 3 lines
→ AI lifts clean
sentences. It can't quote a vibe.
3. Your own dated numbers
→ "11
citations in August" gets cited. "Great results" doesn't.
4. A headline + About section that claim the topic
→ The model checks
who's talking before it trusts the post.
Check yourself in 5 minutes: type your ideal client's
question into ChatGPT Search and scroll the sources. If a competitor's post is
there and yours isn't, that's your next topic.
The feed forgets your post in 5 days. An AI citation keeps
answering for you for months.
(I'll say the uncomfortable bit: I think AEO beats the feed
algorithm for inbound by 2027. Most coaches selling algorithm hacks won't like
that.)
Two years from now: does a ChatGPT citation beat LinkedIn
reach for inbound, or is AEO just SEO in a new hat? Pick a side.
This platform needs less AI generated content.
I don’t mean “less using AI tools for work.” I mean less AI bots commenting for users, less Case Studies written exclusively by AI, and more people caring about the work we do rather than rushing through it.
I kept the commenter anonymous. I did not mean to be rude in this comment, but I feel slightly off each time I read a comment that has no soul. I have even seen $1M+ Contra creators completely AI generate their case studies and just post something of no substance with words that don’t make sense.
I challenge you, if you do this or if you have thoughts about doing it, try the opposite: put more time into reading posts and interacting, put more time into writing and studying for your case studies. See how much you grow. Your influence and your skills will both expand when you stick to authenticity.
hey Trey, thanks for sharing this. we actively discourage AI comments in the feed. if you ever see one, please click "..." and "report this reply" for our team to take a look.
I built an AI-powered client enquiry automation workflow using Zapier, Google Forms, Google Sheets, AI by Zapier, Gmail, and Google Calendar.
The goal was to automate the initial handling of client enquiries from receiving the enquiry to understanding the client's needs, sending an acknowledgement, and creating a follow-up task.
The Problem:
Managing client enquiries manually can be repetitive and time-consuming. Each new enquiry needs to be reviewed, categorized, summarized, responded to, and followed up.
Without a structured process, it's easy for enquiries to be delayed or follow-ups to be missed.
The Solution:
I designed a workflow that automates these repetitive administrative tasks while using AI to analyze the information provided by the client.
The automation follows this process:
Client submits enquiry
↓
Google Sheets captures the enquiry
↓
AI analyzes the enquiry
↓
Gmail sends an acknowledgement
↓
Google Calendar creates a follow-up
How It Works:
1. Enquiry Collection.
The client submits their details and enquiry through a Google Form. The information is automatically recorded in Google Sheets.
2. AI Analysis.
AI by Zapier reviews the enquiry and extracts key information such as the service category, priority, concise summary of the client's needs, and recommended next action.
This eliminates the need to manually review every enquiry just to determine what it is about and how it should be handled.
3. Automated Client Response.
After the enquiry is processed, Gmail automatically sends the client an acknowledgement, ensuring they receive a timely response.
4. Follow-Up Management.
The workflow creates a Google Calendar follow-up, helping ensure that the enquiry doesn't get lost after the initial response.
Result:
The completed workflow turns a manual enquiry process into a structured automated system:
Capture → Analyze → Respond → Follow Up
The key improvement is the use of AI as a decision-making layer, rather than simply moving information from one application to another.
This demonstrates how AI automation can reduce repetitive administrative work, improve response consistency, and help businesses stay organized with client enquiries.
Tools Used:
Zapier | AI by Zapier | Google Forms | Google Sheets | Gmail | Google Calendar
Skills Demonstrated:
AI Automation • Workflow Design • Administrative Automation • AI Prompting • Client Enquiry Management • Email Automation • Calendar Automation • Process Optimization
Really clean workflow, Ann. The Capture → Analyze → Respond → Follow Up structure makes the business value immediately clear. One useful next layer could be an exception route for urgent or low-confidence enquiries, so AI handles the routine cases while anything uncertain...