It starts with a policy. Yes, it's boring. Yes, it's necessary. Decide which tools and vendors your developers can use, and how. Should you ban tools with proprietary algorithms to protect your IP? A good policy gives developers clarity on what they can and can't do.
Next, give your team the tools. This is where many initiatives flatline. The assumption is: if developers have AI tools, they'll magically use them and boom, performance boost. Unfortunately, that's not how it works. Some developers will experiment and slowly adopt best practices. Others will ignore the tools entirely, either from disinterest or fear of the AI replacing them.
Adoption needs planning. Measure how widely the tools are being used and in what kinds of tasks. Coach the team towards more advanced use cases. Give them time, support, and the ability to remove barriers. In complex environments, this transformation can take over a year. It's not just about installing tools, it's about changing processes, even adjusting your architecture.
And don't forget, AI isn't just for coding. It can support every stage of the software development lifecycle.
When your current team is humming along, there are still two things left. First, how will new developers learn these tools? Build onboarding processes that help them catch up quickly. Second, stay flexible. New technologies will keep arriving, and your policies need to evolve with them.
If all of this sounds like a lot of work, it is. But the good news is, you don't have to do it alone. I and plenty of other consultants are more than happy to help you survive the future.
