what differentiates a normal prompt engineer from super. A few things i can think of
- Cross LLM experience
- Understanding how to accuracy faster
- Expereince with LLM Tools
Sugarcane AI provides an Open Source Microservices Framework for cross-LLM workflow/plugin development, allowing developers to prioritize business logic over LLM selection, cost, and performance.
Framework comprises
- LLM as a Service for Data Scientists, empowering data labelling and fine-tuning
- Prompt as a Service for Prompt developers, streamlining prompt management
- Workflow as a Service for Plugin developers to construct workflow plugins, facilitating the distribution of LLM, Prompts, and Plugins via APIs.
The Open Source framework encourages collaborative dataset development and enhances reusability of prompt packages and fine-tuned LLMs, facilitating sharing and monetization on an open marketplace.
Debuggify is all about tracking problems when users using you website in live environment and help developers to fix them as well. Its can be called Crashalytics for Javacsript driven applications
Whereas Ranger.io seems to monitor URLs, if the url doesnot open it will report