Two camps over AI
Half your team trusts what the AI writes. The other half tries to verify everything, which carries a high price tag.
Your team has adopted AI agents extensively, and this has created a split between those who believe that the results are good enough and others who think that a human should gatekeep the code. Even though everyone is using agents, there is no agreement on what the best way is to do so, and this is costing you more than the tools might save.
How we'd handle it
Adopting new technology raises the question of how far you can trust what it produces. We help you define what it is that a tool has to prove before you can rely on it, and where to draw the line between what can be trusted and what needs to be checked.
We bring input and feedback on what's working across the industry and what isn't, so that you can make the right decision for your organization.
Where we've done this
At Sunbit, I built a real-time platform on technology new to the team. Even though I got it to work, the backend team still said no, because they were the ones who would have to run it.
On a Rust rewrite at Redis, I put the component into production before asking anyone to decide. The team had something already running to judge, and they went with it.
Recognize this on your team?
Let's talk