Jared Zoneraich

Jared Zoneraich, co-founder and CEO of PromptLayer, dives into the evolution of prompt engineering into context engineering. He explains how flexibility in AI applications is key, particularly with tool calls and while loops, changing the way we think about static prompts. Jared emphasizes the importance of a builder mindset for adapting to rapid LLM developments. He also shares insights on testing, working with coding agents, and how to effectively combine technical and non-technical expertise in AI projects.

Jared Zoneraich, founder of PromptLayer, dives into the cutting-edge world of prompt engineering. He highlights its evolution as a vital skill in generative AI. Listeners learn about the importance of tailored communication strategies for different language models. Jared emphasizes the necessity of systematic methodologies and user feedback in optimizing prompts. He discusses managing updates and the balance between stability and adaptability in AI responses. Finally, he explores future trends, focusing on resilient platforms that adapt to user needs.

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.

Discover the cutting-edge world of prompt engineering with Jared Zoneraich, founder of PromptLayer. Explore how to optimize prompts for language models, adapt to different models' nuances, and tackle challenges in tweaking prompts in multi-model systems. Get insights into the future of prompt engineering and its crucial role in shaping language model tasks.

Jared Zoneraich, CEO of PromptLayer, delves into the evolving art of AI engineering. He discusses how PromptLayer serves as a workbench for testing LLM products and the tension between implicit and explicit knowledge in AI. The conversation explores the complexities of prompt evaluation, distinguishing between deterministic and probabilistic systems. They also touch on 'vibe coding', which emphasizes the influence of syntax and tone on AI outputs, and how this approach could reshape coding education and practices.