Day 2 - The Art of Prompt Engineering and No-Code AI

Day 2, ok maybe this was more like several days - Day 2, 3, 4, and 5, but this is really where I started seeing how fun AI can be. I started with No-Code AI Apps which was amazing but not what I was looking for for the long run but for many of you it may be a way to prototype your ideas.

Understanding No-Code AI: A Brief Overview

No-code AI refers to platforms and tools that allow users to build, train, and deploy AI models without the need to write traditional code. These platforms are designed with a user-friendly interface, often employing drag-and-drop functionalities, visual workflows, and pre-built templates to simplify the AI development process.

Key Features

- User-Friendly Interface: No-code AI platforms provide a graphical user interface (GUI) that makes it accessible for users with little to no programming background.

- Pre-built Models and Templates: Many no-code AI platforms offer a library of pre-built AI models and templates that cover common use cases, such as image generation, natural language processing, and predictive analytics.

- Custom Model Training: Users can train AI models using their own data sets. The platforms typically provide a simplified process for feeding data into the model. However, be careful since you are now giving these platforms your data.

- Integration Capabilities: No-code AI tools often support integration with various data sources, APIs, and third-party services, allowing users to easily connect their AI models to existing databases, software, and systems.

- Scalability and Deployment: These platforms usually offer scalable solutions that can handle increasing data sizes and user demands.

Benefits

- Democratization of AI: By lowering the barrier to entry, no-code AI platforms democratize access to artificial intelligence, enabling a wider range of individuals and businesses to leverage AI technologies.

- Rapid Prototyping and Deployment: No-code tools significantly reduce the time and effort required to prototype, test, and deploy AI solutions, facilitating a faster go-to-market strategy for AI-driven products and services.

- Cost Efficiency: They reduce the need for specialized AI development talent, which can be costly and hard to find, thereby saving resources and making AI projects more feasible for smaller teams and businesses.

Use Cases

- Business Analytics: Automating data analysis and generating insights from large datasets without manual coding.

- Customer Service Automation: Creating chatbots and virtual assistants to handle customer inquiries without deep technical expertise.

- Personalized Marketing: Developing AI models to tailor marketing campaigns and product recommendations to individual customer preferences and behaviors.

How It Works

• Step 1: Define the Problem - Users start by defining the problem they want to solve, such as automating customer service responses or analyzing sentiment in customer feedback.
• Step 2: Prepare the Data - Using the platform’s data preparation tools, users import and clean their data, making it suitable for training AI models.
• Step 3: Select and Customize a Model - Users choose a pre-built model most relevant to their problem and customize it by adjusting parameters or incorporating their data.
• Step 4: Train the Model - The model is trained on the user’s data, a process that is automated by the platform. Users can monitor performance and make adjustments as needed.
• Step 5: Deploy and Use the AI - Once the model is trained and evaluated, it can be deployed into production where it can start delivering insights, automating tasks, or enhancing user experiences.

No-code AI is part of a broader movement towards no-code and low-code development platforms, which aim to make technology creation more accessible to non-technical users and accelerate digital transformation across industries.?

My First Experience with No-Code AI

I learned about No-Code AI by reading this TechRadar article

"I created an AI app in 10 minutes and I might never think about artificial intelligence in the same way again" by Lance Ulanoff. Which goes into how to use You.ai much more than I do here, if you're interested in learning more I'd recommend you read the article or just go play with it.

As someone intrigued by the potential of AI but lacking extensive coding skills, Youai.ai provided an ideal platform to explore this exciting field. Deploying my AI models was almost a seamless process with Youai.ai. I say almost because it was more complicated than what I needed. For delights.ai, I wanted to share with my delights' teammates User Personas of "who" the delights.ai user base would be. However, I was feeling lazy and wanted to see if anyone had created a GenAI tool that would magically generate a User Persona for me with beautiful pictures of the User in various environments along with a description of the User Persona, a Day-In-the-Life, and the User Journey. (By the way, if you are looking for ideas for a GenAI product, I have yet to find a tool that does text and image generation together very well, if at all.)

Since I couldn't find any GenAI tools that would generate User Personas, I decided that my first challenge would be to create the GenAI tool myself. Here is a GenAI Tool that I created using MindStudio’s Youai.ai that you can experience at the below link. Not perfect but it was a start to what I needed.

?https://youai.ai/ais/9d533630-9d9a-4d0b-b361-f82be2e89bd7

Here are some screenshots from Youa i.ai’s interface:

The above screenshot shows the ability to create your prompt in the middle of the screen. The prompt written there is what I would call a self-referential AI loop. I asked ChatGPT 3.5 to write me a prompt for creating User Personas using AI and it spit out the text in white above, which is much better than I could ever write. I would highly recommend that you have the model you are going to use write the prompt for you. Or ask it to "describe" something you're interested in for you to use as a basis for your prompt. I can’t emphasize this enough. It understands itself much better than you will and will produce much better results. But the above prompt was not just a one-time effort. I did enter and ask for multiple prompts over and over again until I got the resulting prompt that would get any of the AI models from ChatGPT, Gemini, Llama, etc to return a half-decent result. Here is the prompt in its entirety:

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# User Persona and Journey Generator

?## Purpose

- The Assistant is designed to generate User Personas, a Day-in-the-Life scenario, and a User Journey for a desired demographic.

?## Parameters

- The Assistant should create detailed and realistic User Personas that represent the target demographic.

- The Day-in-the-Life scenario should illustrate a typical day for the generated User Persona.

- The User Journey should map out the interactions and experiences of the User Persona with a specific product or service.

?## Traits

- The Assistant should be able to create comprehensive and insightful User Personas.

- The Day-in-the-Life scenario should be vivid and descriptive, providing a clear picture of the User Persona's activities.

- The User Journey should outline the various touchpoints and emotions experienced by the User Persona throughout their interaction.

?## Additional Information

- The Assistant should be able to adapt to different demographic criteria provided by the user.

- Each generated output should be tailored to reflect the specific needs and preferences of the desired demographic.

- The Assistant should aim to provide valuable insights and understanding of the target audience through the generated User Personas, Day-in-the-Life scenarios, and User Journeys.

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You.ai also allows for a lot more customization. When you move to the “Automations” tab in the middle of the page it allows you to create interactions and automations that are much richer than what a written prompt could generate. However, I found it to be unnecessary for my purposes and more complicated than what I wanted when all I wanted was a simple way to generate an image of a User Persona along with the description of the Persona.

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Another popular No-Code AI platform is Promptbase?which launched their No-Code App Builder at the end of Jan'24.

Promptbase is more of a Marketplace of Prompts but I found their No-Code App Builder?easier to use than You.AI. The below screenshot is of Promptbase's interface as I tried to create a video for my User Personas.

However, Promptbase, first and foremost is a marketplace for prompts which I will talk about in my next article and this is where things get weird and exciting -- the marketplaces for prompts.

All of these No Code AI tools do get costly after a while and what I started learning from these were the differing costs of these AI models and how these solutions were trying to monetize them. I'll go into that in subsequent articles.

In general, these No-Code AI tools are great if you want to prototype something or to have an AI Model use a private database and/or to create a GenAI for your company exclusively. However, you have to be aware that the data you provide to these platforms may be stored and accessible to them unless you can work with them to protect your data. Here are some other concerns I had when I considered using No-Code AI.

1. Limited Customization and Flexibility

• Generic Solutions: No-code platforms often provide generic solutions that may not fit all specific business needs.
• Limited Control: The inability to fine-tune models at a code level can be a significant constraint for complex projects.

2. Performance Concerns

• Optimization Limits: There may be limitations on how well you can optimize AI models for performance and efficiency. This can be critical for resource-intensive applications or when processing large volumes of data.
• Scalability Issues: While no-code platforms are designed to be scalable, there can be constraints compared to custom-built solutions, especially for very high-volume, high-complexity applications.

3. Data Security and Privacy

• Data Handling: When using no-code platforms, especially cloud-based services, concerns arise regarding data security, privacy, and compliance with regulations like GDPR. Users often have to upload data to third-party servers, which might not always align with an organization's data governance policies.
• Vendor Lock-in: Platforms might use proprietary formats and systems, making it challenging to migrate projects or data to other systems. This dependency can create issues for long-term scalability and flexibility.

4. Over-simplification

• Understanding AI Limitations: There's a risk that no-code AI platforms oversimplify the complexities and ethical considerations of AI development. Users might deploy AI models without fully understanding their limitations, biases, or ethical implications.
• Skill Development: Relying heavily on no-code solutions might hinder the development of deeper technical skills in AI and machine learning, which are valuable for more advanced work in the field.

5. Cost Implications

• Subscription Fees: Many no-code AI platforms operate on a subscription model, which might become costly over time, especially as usage scales. For startups and small businesses, these costs can add up and impact the overall budget.

6. Quality and Reliability

• Dependence on Platform: The quality and reliability of your AI solutions are directly tied to the platform you choose. Any issues with the platform, such as downtime, bugs, or discontinued features, can directly impact your projects.

7. Intellectual Property Concerns

• Ownership of Developments: There might be ambiguity or concerns regarding the ownership of the models, algorithms, or data used and developed within the platform, which could lead to intellectual property disputes or complications.

While no-code AI platforms are powerful tools that lower the entry barrier to AI development, they are not a one-size-fits-all solution. It’s crucial for organizations to weigh these drawbacks against their specific needs, capabilities, and long-term strategies when considering adopting no-code AI solutions.

At the End of Day, This is What I Learned

Creating AI no longer requires extensive coding knowledge, thanks to platforms like Youai from MindStudio and Promptbase.com. Anyone can do it but I don't recommend building an entire business or company off of it without doing a thorough cost analysis. Especially, with the recent news about Stability.AI, an AI company valued at $1B at its Seed Round, CEO stepping down, and fallout with investors and board members, partially due to the cost of server compute. You need to think through whether or not your AI business will be profitable with the cost implications of the compute power that you need. Unless you have the backing of a major cloud service provider like Microsoft for OpenAI or Amazon for Anthropic, it is going to get harder to afford. However, we have found ways around it for delights.ai.

The next post "Day 3 - Prompt Engineering and the Very Gen Z Prompt Marketplaces" will drop in a few days

Stay Tuned!!!

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