Method Grid's AI-Empowered Delivery - In Conversation with Senior Back-End Developer Marc North

As Method Grid's AI Beta is rolled out on our platform, we thought this would be the perfect time to pose some questions to one of the architects of the project, Method Grid's Senior Back-End Developer Marc North .

Marc has spent the last few months wowing everyone, whether internally with the Method Grid team or externally, presenting to many of our clients, with the amazing work he has been doing to bring AI empowerment to our platform.

He kindly took some time to answer some questions about the significance of the project, the challenges that were faced, cross-department collaboration, and what the future holds for Method Grid and AI.

Q) Could you give us an overview of the new feature and the significance of the project?

A) The new feature allows users to use AI to help them generate or tweak content within a grid. The obvious main benefit of this new feature is a huge boost in productivity for users, especially in the grid-building phase, but there are also massive benefits in terms of consistency of content development, allowing content to have a consistent quality, tone, and style.

More than that though, it’s also a huge step forward for us in terms of integrating AI features in Method Grid; this is very much the first of many AI-assisted features we’ll be releasing.

Q) What was your role in developing this feature and what were the main challenges you faced during its development?

A) This was an interesting feature to develop, being more R&D driven than most feature releases. As such, even in the planning stages, there was a lot of collaboration between the dev team and other departments, e.g. our professional services team, in exploring what is possible with AI content generation and what would provide the most value to our clients.

As for challenges during development: the blocks of text generated by AI models tend to get most of the attention, but it was actually the other types of content, such as task lists, that were more challenging (and interesting!) to integrate, because they require embedding a more nuanced understanding of Method Grid’s platform and capabilities into the AI models.

Q) How would you describe the collaborative effort between the development team and other stakeholders involved in this project? Were there any unique or noteworthy interactions that stood out during the development process?

A) Definitely. As I’ve said, the planning of this feature involved a lot of collaboration between the dev team and other departments, but there was also a lot of collaboration and feedback gathered from our users during development. We’ve demoed this and similar features to our clients a few times during development, and hearing their feedback, especially during our Senior User Forum, has been incredibly valuable.

During our Senior User Forum, we asked what areas of our app people would most like to see us integrating AI-assist into, and dashboard reporting was a very popular response.

Over the next few weeks, we were able to put together a prototype of an AI-driven report-generating feature that we demoed during our AI Grid Talk; I think that’s a great example of how user feedback during development is guiding what we work on and what features we develop.

Q) Looking ahead, what do you hope to see or achieve with this feature in terms of user adoption, feedback, or future enhancements?

A) I expect this feature to be the first of many AI enhancements we’ll bring to our app. We’ve already got a few more AI features in development that we’ve shown off a couple of times and feedback to them has been very positive.

I think the most exciting AI feature we’ve been developing is the AI-enabled lessons learned; it’s probably the most challenging, but also the one with the most potential.

In terms of user feedback, I’m just hoping that the dialogue we’ve been building around AI use within Method Grid continues,?internally and with our users.

There’s a huge amount of potential to be unlocked with these new features, but also risks and challenges that have to be navigated. I think the best way for us to do that is to continue having open and honest discussions about those challenges with our users.

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If you would like to see the AI capabilities of Method Grid in action first-hand, you can schedule a demo with our team who will show you what our AI-empowered knowledge and project management platform is all about.

Simply book a demo using this link.