I think it's worth maintaining a sort of knowledge map as a team to keep a holistic view on which things are going to be most relevant and impactful to your business/product. Learning rituals is a good first step, but when the change is as rapid and impactful as generative AI, I think it's worth considering more formal ownership over specific areas.
For example: within a design team, you might have someone who is very interested in text-based interactions and another person who is more interested in AI within the UI or integrated with the tools that exist.
Ya that makes sense! Your point also reminds me that laddering those learnings into themes or some scaffolding like a knowledge map certainly helps add important context even prior to formal ownership. And also agree that specific people often emerge as experts based on interest or things like prior experience.
Love this! Additionally, I’d add the willingness to experiment with ideas that might not necessarily be within scope or in other words, draw parallels from outside of the domain. This kind of tangential observations and patterns help form a better picture in AI implications. Eg. playing around imaging prompts helps in envisioning better and bring attention to detail to textual ideas--inspiration can come from all around.
Focusing teams to understand what AI is good at doing & potentially useful for is super critical - playing with it to get arms around it technically & functionally is important, and then understanding the use cases it can help supercharge is the next step, seems to me.
Great topic and interesting observations! I am interested in learning rituals and creating a learning culture. I like the point about keeping things informal / having a low barrier to entry so to speak. Any other tips for fostering a learning culture / creating learning rituals?
Love for you to join and others to join our conversation on this topic at www.aiagile.org. We are having conversations on how the future of work and collaboration changes.
I think it's worth maintaining a sort of knowledge map as a team to keep a holistic view on which things are going to be most relevant and impactful to your business/product. Learning rituals is a good first step, but when the change is as rapid and impactful as generative AI, I think it's worth considering more formal ownership over specific areas.
For example: within a design team, you might have someone who is very interested in text-based interactions and another person who is more interested in AI within the UI or integrated with the tools that exist.
Ya that makes sense! Your point also reminds me that laddering those learnings into themes or some scaffolding like a knowledge map certainly helps add important context even prior to formal ownership. And also agree that specific people often emerge as experts based on interest or things like prior experience.
Love this! Additionally, I’d add the willingness to experiment with ideas that might not necessarily be within scope or in other words, draw parallels from outside of the domain. This kind of tangential observations and patterns help form a better picture in AI implications. Eg. playing around imaging prompts helps in envisioning better and bring attention to detail to textual ideas--inspiration can come from all around.
Totally agree! Especially with employing the concept of 'play' in this type of experimentation and using parallels from other domains.
Focusing teams to understand what AI is good at doing & potentially useful for is super critical - playing with it to get arms around it technically & functionally is important, and then understanding the use cases it can help supercharge is the next step, seems to me.
Great topic and interesting observations! I am interested in learning rituals and creating a learning culture. I like the point about keeping things informal / having a low barrier to entry so to speak. Any other tips for fostering a learning culture / creating learning rituals?
Love for you to join and others to join our conversation on this topic at www.aiagile.org. We are having conversations on how the future of work and collaboration changes.