Prompt engineering for enterprise chatbots
Our older intent-based chatbots needed hundreds of intents manually developed over months or years to generate helpful responses for users.
This efficiency is the result of the time and effort we've invested in building the perfect prompts and the technology and structure we've developed around them, without which LLMs can be unpredictable, inaccurate, or outright dangerous.
This article examines what makes a good LLM prompt and gives you an inside look at Enterprise Bot's infrastructure and the process behind our prompt development. We’ve built custom tooling to take the guesswork out of designing and testing new prompts and to ensure that our assistants constantly rank well on our BASIC benchmarking framework.
Basic prompt engineering is how consumers get good answers from LLMs like ChatGPT. You can ask the same thing differently, and some formulations will lead to better results than others. For example, a prompt like, "Write me a poem about my friend Bob" might output something similar to this:
Read more about general prompting in our post on how to write the perfect prompt, or continue reading for guidance on engineering prompts specifically in an enterprise setting.
