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FAI Weekly Gokhan #3

Status
Date
Apr 30, 2025
AI summary
Path 1: Manufacting sales cycle is long, they need a lot of certainty. They seems interested, but it reality they are not. But they are afraid of paying.
Created the demos, we try to re-utilize the them. Similar company in a similar industry. They didn’t ask for more demos. Now we are doing a budget for them.
Path 2: Web3 has advancements, more towards DAOs and DeFI protocols.
The same technology
 
Broader overview
  • Specific automation solutions. Generative AI and chatbots.
  • Tradioanl AI models
  • What is the industry that can benefit from this - who is most willing to pay for this? WHo has the biggest problem?
  • They want a machine they want to go investors, this is the IP we have. What happens if someone leaves the company. If something happen to CEO, that others can continue the work.
  • AI Assistant that has all the knowledge of the company - Structure information and databases. Not just patterns in companies - Goal is being replaced with ChatGPT. Process will also happen in companies.
  • We are struggling with the marketing messaging. If she does not understand something technical about the company, she can ask the system. If you are not technical, you ask questions.
  • People in the factory floor could use it, even with voice then can record it. I made this experiment with the features. 6 months down the line, I want to replicate what this employee did. This would be really benefical for them.
  • You are trying to achive something with a machine, you are knowledgable person or search on the internet. You are already doing this work.
  • On the B2C mindset, in B2B mindset the CEO is more top down. Archive something to use. Done in a company and company basis. And they will do top down. What kind of questions they ask Google, and we made an AI- AI learns your pattern. Health care plastics company, where people would talk. We imagine ppl need both hands.
  • Flows of these products. Machine A will make Product Y, Actually I need product Z - Production planning.
     
     
     
     
     
     
    🗓️

    FAI Weekly Gokhan #3

    Status
    Date
    Apr 30, 2025
    AI summary
    Path 1: Manufacting sales cycle is long, they need a lot of certainty. They seems interested, but it reality they are not. But they are afraid of paying.
    Created the demos, we try to re-utilize the them. Similar company in a similar industry. They didn’t ask for more demos. Now we are doing a budget for them.
    Path 2: Web3 has advancements, more towards DAOs and DeFI protocols.
    The same technology
     
    Broader overview
    • Specific automation solutions. Generative AI and chatbots.
    • Tradioanl AI models
    • What is the industry that can benefit from this - who is most willing to pay for this? WHo has the biggest problem?
    • They want a machine they want to go investors, this is the IP we have. What happens if someone leaves the company. If something happen to CEO, that others can continue the work.
    • AI Assistant that has all the knowledge of the company - Structure information and databases. Not just patterns in companies - Goal is being replaced with ChatGPT. Process will also happen in companies.
    • We are struggling with the marketing messaging. If she does not understand something technical about the company, she can ask the system. If you are not technical, you ask questions.
    • People in the factory floor could use it, even with voice then can record it. I made this experiment with the features. 6 months down the line, I want to replicate what this employee did. This would be really benefical for them.
    • You are trying to achive something with a machine, you are knowledgable person or search on the internet. You are already doing this work.
    • On the B2C mindset, in B2B mindset the CEO is more top down. Archive something to use. Done in a company and company basis. And they will do top down. What kind of questions they ask Google, and we made an AI- AI learns your pattern. Health care plastics company, where people would talk. We imagine ppl need both hands.
    • Flows of these products. Machine A will make Product Y, Actually I need product Z - Production planning.