The demands that generative AI makes on product development teams are significantly different from traditional software, and any teams building generative AI features need to adapt. Knowing where to start, how to work together, and best practices to adopt are all important unlocks to moving faster.

Our co-founder Ian Cairns talked about these topics in a recent article with Deloitte Insights.

Here’s why this is all so important to us at Freeplay:

Every day, experienced software teams are getting started building with generative AI for the first time, and they're looking for the fastest way to get up to speed.

Everything that we do is rooted in helping engineering and product leaders and their cross-functional teams build great products with AI. We've built our platform to make it easier to adopt best practices, and to work faster together. Everything we've built is rooted in experience, and informed by what we've seen working (and not!) across countless software teams.

In his article, Ian covers:

• Three key aspects of building with AI that Engineering and Product teams need to understand and adopt: evaluations, data labeling and curation, and testing.

• The evolving roles and responsibilities of engineers, product managers, and domain experts in the product development lifecycle.

• How teams that get all this right can help their entire organizations build competitive advantages.

Read the article in full here.