Slot filling
Context Lifespan
Conversation Design
Bot frameworks
Machine Learning


I also got the following input from a fellow Dialogflow freelancer who has worked on many bots for his clients. He once mentioned that he prefers a context lifespan of 2, but that he also agrees with me. So I asked him to explain. Here is what he said.

Lifespans are tricky. But very useful once you know what you are doing, when you already have experience and real world operations’ data to deal with.

Yes: in general I think a lifespan of 2 is a better deal than 1, because with 1 you lose context immediately: you have to think in more intents to prevent losses. With 2 you have the risk of some wrong match in the next step, but this situation occurs less frequently, so the trade off is better. And you can design the conversation in order to reduce the risk of two close groups of words.

But I insist: one needs to have some experience to use a lifespan of more than 1. So: if I, like you often do, talk to newbies and less experienced conversation designers, I start with 1. If/when your audience is more advanced, then you can think about better use of lifespan.

So: I don’t really disagree with you 😉

Here is my simple conclusion: when in doubt, set your context lifespan to 1. Once you fully understand which intents become candidates at each step in the conversation in your bot, consider increasing the value according to your requirements.

Generic filters