How to Find, Build, and Deliver GenAI Projects

In this video, Dave Ebbelaar, founder of Data Lumina, provides a comprehensive guide on how to find, build, and deliver generative AI (GenAI) projects. The video is divided into three main parts: how to find GenAI projects, how to build them, and how to deliver them effectively.

In the first part, Dave discusses strategies for finding GenAI projects. He emphasizes the importance of having a clear offer and deciding whether to go general or niche. For those starting out, he recommends starting general and leveraging existing networks. Dave suggests using social media platforms like LinkedIn and YouTube to share experiences and insights, which can naturally attract potential clients. He also highlights the effectiveness of participating in Discord communities and using freelance platforms like Upwork and Fiverr.

The second part focuses on building GenAI projects. Dave outlines the fundamental structure of GenAI projects, which includes inputs, processing, and outputs. He stresses the importance of prompt engineering and using structured frameworks for creating effective prompts. The video details the tech stack used by Data Lumina, including Python for backend development, Azure OpenAI for large language models, and various tools for project management and deployment. Dave also provides tips on minimizing AI usage to enhance application performance and reliability.

In the third part, Dave addresses the challenges of delivering GenAI projects. He discusses the complexities of moving from local development to production, the importance of monitoring and maintaining applications, and the need for clear communication about ongoing costs and maintenance with clients. Dave explains the different hosting options, including client-hosted and self-hosted solutions, and the use of cloud platforms like Microsoft Azure. He also covers deployment and maintenance practices, such as using Docker for scalable deployment and implementing robust monitoring tools like Sentry.

Dave concludes the video by sharing an example architecture diagram of a GenAI project, illustrating how various components fit together to create a scalable and secure solution. He emphasizes the importance of security measures, such as multi-factor authentication and VPNs, to protect sensitive data.

Overall, this video serves as a detailed guide for data professionals and developers looking to explore freelancing or build GenAI solutions within their organizations.