Jared Zoneraich, Founder of PromptLayer, discusses the vital role of non-technical domain experts in AI development. He highlights how leveraging domain knowledge can enhance the effectiveness of AI applications. The conversation delves into the art of prompt engineering, emphasizing that better interaction with AI lies in expertise, not just tech skills. Zoneraich also covers the shift toward smaller, customized AI models and the importance of continuous adaptation in this fast-evolving landscape, ensuring human insight remains central to AI innovation.
32:43
forum Ask episode
web_stories AI Snips
view_agenda Chapters
auto_awesome Transcript
info_circle Episode notes
insights INSIGHT
Domain Expertise in AI
Domain expertise is key to building successful, differentiated AI products, not just technical skills.
Domain experts ensure the AI's output is relevant and accurate within a specific field.
insights INSIGHT
Small Models and Domain Expertise
Small models combined with domain expert data may be the future of LLMs.
Regardless of model size, domain experts are crucial for defining tasks and evaluating outputs, especially in conversational AI.
volunteer_activism ADVICE
Leveraging Domain Expertise
Non-technical domain experts can leverage their knowledge by getting hands-on with AI tools and GPT widgets.
Focus on improving communication and computational thinking skills to excel in the evolving AI landscape.
Get the Snipd Podcast app to discover more snips from this episode
Prompting a large language model requires a bunch of tech know-how right?
↳ Super structured inputs ↳ RAG ↳ Fine-tuning
Meh. Not so much. The best way to prompt your way to better results? Flex your domain expertise. Jared Zoneraich, Founder of PromptLayer, joins us to discuss.
Topics Covered in This Episode: 1. Importance ofprompt engineering 2. Role of non-technical domain experts 3. Evolving landscape of AI technology 4. Future concerns and preparations
Timestamps: 01:35 Daily AI news 04:32 About Jared and PromptLayer 07:19 Creating successful AI product hinges on expertise. 08:45 Simplifying AI development and retaining human input. 11:50 Small models vs big models: implications for AI. 17:10 LLMs elevate conversation and knowledge sharing. 21:12 Product success depends on voice and connection. 22:29 Rapid adaptation to new technology creates disparity. 27:02 Prepare AI models, modular approach, conversational application. 29:38 Key steps in maximizing AI model productivity.
Keywords: Jordan Wilson, prompt engineering, machine learning, Pope Francis, ethical AI, G7 summit, AI regulation, General Paul Nakasone, OpenAI, cybersecurity, Microsoft, recall feature, privacy advocates, Jared Zoneraich, Prompt Lair, nontechnical domain experts, AI products, AI services, Cursor, Copilot, Hevia, ParentLab, Gorgias, communication skills, large language models, commoditization of knowledge, computational thinking, AI revolution, AI applications, human expertise in AI.
Everyday AI Podcast – An AI and ChatGPT Podcast