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AI Visibility Vault

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The Visibility Vault is a business-first AI community focused on visibility, automation, and growth without the need to become an AI expert.

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4 contributions to AI Automation Society
The knowledge I have learned here...
Taking some of the ideas in here allowed me to champion a $5,500 client. My background is 20 years of large corporation pricing and 30 years of web design. AI - maybe 10 years with apps, tools, and oh yeah PYTHON...so... A Saturday morning, 4 hours, and a complete pricing evolution. ๐Ÿ”ฅ I recently helped a small industrial parts business move from manual Excel models to a fully autonomous agentic workflow. Using ChatGPT alongside n8n and Claude, I built a system that audits invoices, expenses, and competitor data for an automated Van Westendorp price sensitivity analysis. ๐Ÿ˜ฑ The user just chats to a chatGPT chatbot to execute. Thatโ€™s the power of this stack. Time to put spreadsheets to bed! ๐Ÿ† Thank you to all the amazing people on here who post GREAT content!
๐Ÿš€New Video: How to Sign Your First AI Workflow Client in 7 days (With Proof)
In this video, I break down exactly how to sign your first AI workflow client in 7 days, with real proof. Youโ€™ll hear directly from a member of AIS+, Christian, who signed his first automation client in just 7 days. We walk through the exact process he used, what actually worked, and how you can apply the same steps yourself.
7 likes โ€ข 29d
Great content right here!
I lost a $6,745 AI automation deal because of this one simple mistake.
I tried to help everyone. Custom solutions. Custom workflows. Custom timelines. Sounds good in theory. Kills you in reality. Hereโ€™s the truth no AI agency wants to admit: You canโ€™t scale โ€œcustom everything.โ€ Most AI agencies fail for one reason: They promise to build bespoke automations for every business. What that actually means: - 4โ€“7 days to build ONE automation - Endless revisions - Clients waiting, chasing, hesitating - You drowning in projects And no one wants to wait a week for automation in 2025. So I flipped the model. Instead of custom work, I productized ONE automation. Then I templated it: - Every step - Every integration - Every edge case - Every deployment process The result? Deployment time went from 7 days โ†’ under 1 hour. Thatโ€™s when everything changed. I went from: - Project-to-project chaos - Consistent, predictable, paying clients Saying โ€œnoโ€ at the start was hard. But speed compounds. Speed = money. Amazon didnโ€™t win because it had the best products. It won because it removed friction. Imagine if Amazon said: โ€œFill a 5-page form and wait 10 days to order.โ€ Youโ€™d never use it. Instead: 2 clicks. Product at your door. LESS FRICTION = MORE SALES
2 likes โ€ข 30d
Great advice right here!
Need help with RAG
Hi guys, Right now i am building my first RAG agent, using n8n. I use a combination of pinecone and the simple vector store native to n8n. It works but not in the way i want to. I am getting abit lost in all the videos and tutorials there is. So basically put i have 2 questions. What is the best way to decide how to chunk or vectorise your documents. What can i do to optimise those documents. Extra questions for bonus points: What would be the most efficient way of gettig physical books into my rag agent if there aren't any e-books findable,.
1 like โ€ข 30d
Make sure you have semantic boundaries. Don't break mid-sentence or mid-thought. If you're indexing documentation, chunk by section. For books, by paragraph or topic shift. Also, store the source, chapter, page number, document title with each chunk. This lets you filter searches and provide context in retrieved results. Last, Your chunking should match how users ask questions. If people ask "How do I configure X?", your chunks should contain complete configuration instructions, not split across multiple chunks.
1-4 of 4
@bradley-trede-3838
I solve math problems and love to tell stories. Yeah I am a pricing and AI nerd.

Active 2h ago
Joined Jan 12, 2026
ENTP
Vernal, Utah
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