Prompting Chatgpt vs Claude
Explore the key differences between Claude and ChatGPT, from their capabilities and use cases to their response speeds and unique features.
Drishti Shah
Prompt Security and Guardrails: How to Ensure Safe Outputs
Prompt security is an emerging and essential field within AI development making sure that AI-generated responses are safe, accurate, and aligned with the intended purpose.
When prompts are not secured, the resulting outputs can unintentionally generate or amplify misinformation. Compliance risks are also a major concern. Enterprises deploying AI systems
What is LLM Observability?
Discover the essentials of LLM observability, including metrics, event tracking, logs, and tracing. Learn how tools like Portkey can enhance performance monitoring, debugging, and optimization to keep your AI models running efficiently and effectively
Evaluating Prompt Effectiveness: Key Metrics and Tools
Learn how to evaluate prompt effectiveness for AI models. Discover essential metrics and tools that help refine prompts, enhance accuracy, and improve user experience in your AI applications.`
How to Build Multi-Agent AI Systems with OpenAI Swarm & Secure Them Using Portkey
Learn how to build multi-agent AI systems using OpenAI Swarm, an educational framework designed for managing collaborative AI agents with Portkey.
Zero-Shot vs. Few-Shot Prompting: Choosing the Right Approach for Your AI Model
Explore the differences between zero-shot and few-shot prompting to optimize your AI model's performance. Learn when to use each technique for efficiency, accuracy, and cost-effectiveness.
The Complete Guide to Prompt Engineering
What is Prompt Engineering?
At its core, prompt engineering is about designing, refining, and optimizing the prompts that guide generative AI models. When working with large language models (LLMs), the way a prompt is written can significantly affect the output. Prompt engineering ensures that you create prompts that consistently generate