What roadblocks have you encountered while integrating AI into your developers’ workflows, and how’d you get around them?
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Chief Executive Officer9 hours ago
I apologize for the delay in my response.
One of the main roadblocks we faced was cultural adoption. Developers often viewed AI assistants as ‘extra work’ rather than as tools that could truly accelerate their daily tasks. To overcome this, we avoided vanity metrics and focused on a single, tangible measure: the number of premium requests per developer in their AI coding assistants. This gave us a clear view of who was actually embedding AI into the SDLC and helped us link adoption to productivity gains. Once adoption became measurable and transparent, resistance dropped and usage grew organically.
Other thoughts.
1. Knowing the pain you want to resolve
2. Being able to evaluate the ROI of the solution
3. Having large amounts of good data for the AI Model to understand the business
4. Not 100% safe behaviour, can’t use on mission-critical decisions.
5. Unable to manage very, very large context. Needs a lot of work to behave as expected in a very long conversation.