Dynamic Context Tuning: Smarter Chatbot Context Resolution Without the LLM Overhead
The Problem With "That Product" Multi-turn conversations are natural for humans but surprisingly tricky for chatbots. When a user asks "What's

Chef Fundamentals on the road again, this time clode to my roots in Innsbruck in Tyrol.
Quite a new situation with a lot of questions on how to run chef-client as a non-privileged user.
| Avg | Min | Max | |
|---|---|---|---|
| 4,78 | 4 | 5 | „course adressing the topics announced“ |
| 4,33 | 2 | 5 | „pre-requisites appropriate“ |
| 4,67 | 4 | 5 | „do you believe you will benefit“ |
| 4,44 | 4 | 5 | „how did you like the course overall“ |
| 4,89 | 4 | 5 | „instructor competent and knowledgable“ |
| 5,00 | 5 | 5 | „Instructor friendly/open to questions |
| 4,67 | 4 | 5 | „instructor taught understandable“ |
| 4,56 | 4 | 5 | „was this a good training event“ |
| 4,56 | 4 | 5 | „book another course?“ |
| 4,67 | 4 | 5 | „recommend training“ |

If you ever want a training class organized in the DACH region (or beyond ;), don't hesitate to reach out to us :-)
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