How I saved 30h/month with AI?

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Aloha friends,

Ever wished you could clone yourself, to save time? 🙏 

I found a way to do just that for a specific use case.

This month, my AI-Assistant saved me a whopping 30+ hours of calls!!!

I’m here to share how you can harness this magic too.

Before we dive into this, here are two AI recommendations: an amazing AI newsletter (see below), and a free virtual event on how to adopt AI 🚀

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⌛️ How AI Saved Me 30h on Calls This Month?

Last year, I began pondering a critical question: "How will AI impact consultants?" Unable to find a clear answer, I decided to go directly to the source and ask consultants themselves. I reached out to my network (see screenshot), and within a few weeks, I received over 300 positive replies.

😅 1. Problem: “I Want Answers, but Have No Time”

While this response was amazing, it was also overwhelming. I realized that what started as a quest for insights had the potential to become a comprehensive research project, not just a simple article. However, time was not on my side, and I needed an efficient solution to manage the deluge of responses. To tackle this overwhelming response efficiently, I turned to AI.

🧠 2. Solution: “AI-Interviewer, instead of Iwo”

Faced with the prospect of managing hundreds of interviews, I knew I needed a way to save time and maintain the quality of data collection. That's when I decided to leverage AI-Mentor to assist me.

The goal was clear: I needed AI to help me handle structured conversations with consultants, gather valuable insights, and prepare the data for analysis. This approach would save me countless hours and ensure a consistent, high-quality dataset.

Building my own AI Assistant transformed the process. Instead of scheduling and conducting Zoom calls, my AI-Interviewer ran structured conversations asynchronously, efficiently gathering the information I needed.

So far, it saved me 30 hours in just the last two weeks (116 interviews completed) and allowed me to focus on analyzing the data rather than conducting interviews. Contributors loved the experience too, as it provided them with a flexible and engaging way to share their insights ❤️ 

Now, let me show you how you can do the same for your projects. Below are the steps I followed to create an efficient AI-Interviewer using the AI-Mentor platform. This process can be applied to a variety of use cases, from market research to employee feedback, making data collection easier and more structured.

🔥 3. What is your use case?

There are countless ways you can leverage an AI-Interviewer. Here are just a few examples to get you started.

Reply if I have some other ideas in mind and I will add them :)

✅ 4. How to build this AI-Assistant? Step-by-step

If you're interested in learning how I implemented this, here’s a sneak peek into my process using the AI-Mentor platform. I used the “Custom Assistant Creator” that guided me through the whole ideation and creation process in 7 simple steps.

Step 1: Discuss the Goal: Discuss your project's goals with the AI.

Step 2: Define Interaction Flow: AI outlines the assistant's structure and tasks.

Step 3: Specify Sections: Choose topics like AI Predictions and AI Adoption.

Step 4: Define Tasks for Each Stage: Identify what the AI should achieve in each stage to maintain a conversational flow.

Step 5: Set Personality and Interaction: Define the AI’s personality traits and interaction style.

Step 6: Set Up Conversation: Outline the stages from introduction to conclusion.

Step 7: Review: Provide final feedback and once you are ready, approve it!

A few minutes later - I got my very own assistant!

🤌 5. Assistant testing and tweaking

Once the AI-Interviewer was built, the next critical phase was testing and adjusting. This step ensures that the assistant functions as intended, handling multiple stages and collecting various types of information accurately.

During the brainstorming phase, we developed a comprehensive flowchart outlining the interview structure. My job was then to review and refine the content for each stage, focusing on the prompts provided to the AI.

For instance, in the "AI Predictions" section, the AI had two main tasks to accomplish, each governed by a set of specific rules to maintain clarity and relevance during the conversation. Here, the AI needed to ask about predictions and ensure that the responses were captured accurately and concisely. This involved testing various scenarios and adjusting the prompts to handle unexpected answers gracefully.

Through iterative testing and tweaking, I ensured that the AI-Interviewer was well-equipped to handle structured conversations, gather meaningful insights, and provide consistent data for analysis. This phase was crucial in refining the assistant's performance and ensuring its reliability in real-world applications.

🚀 6. Time to share it with the world

At this point, I was ready to start sharing it with the world. People who agreed to contribute, got email invites to connect with our AI-Mentor.

Here is an example from a conversation starter with a user.

Reflecting on this journey, it’s clear that leveraging AI can significantly streamline complex tasks and save valuable time. Now, it’s your turn. Have you thought about how AI could revolutionize your workflow?

Feel free to reply with your thoughts or any questions you have about implementing AI-Interviewers in your projects. Let’s keep the conversation going!

Enjoy the rest of your week,

Iwo