Chatbot Messg™
Start with a conversation you can finish well.
Choose a chatbot design that matches the task: a guided path, a knowledge answer, or a human handoff. A narrower experience can be easier to understand and review.
Three decisions to make first.
Choose a decision model
A guided flow can offer explicit choices, while a retrieval assistant can answer from approved material. Decide which problem each model is supposed to solve instead of combining them without a clear boundary.
Write the escape routes
A person may not fit the expected path. Plan how the bot handles an ambiguous request, a repeated misunderstanding, and a direct request to contact a human.
Review the complete exchange
A useful answer in isolation may still produce a frustrating conversation. Test several turns, corrections, and topic changes to see whether the bot preserves context without inventing facts.
A useful starting sequence.
- Select one task and its completion condition.
- Write fallback and human-contact paths.
- Test corrections and multi-turn misunderstandings.
What not to assume.
Do not describe a chatbot as a human teammate or imply capabilities it does not have. Make available actions and escalation routes understandable in the interface.
For a practical review, describe the intended audience, the information crossing each boundary, and the person responsible when the ordinary path fails.
One useful question.
Does a chatbot need generative AI?
Not always. A clear guided flow may be sufficient for a narrow task. Choose the simplest model that can handle the expected conversation and explain its limitations honestly.
Keep the idea moving.
Grounded AI chat: useful answers need an evidence boundary
A practical review of source curation, retrieval, uncertain answers, evaluation, and the line between answering and acting.
Read the complete guideExplore nearby topics in the same part of the message journey.
Have a workflow in mind?
Share the message journey you are planning and the point that needs a little more clarity.