Every week, a new AI tool promises to increase developer productivity and keeping up with the latest developments can feel like a part-time job. Teams will spend days testing and validating new LLM-powered productivity marvels. They will compare Windsurf to Cursor and CodeRabbit to CodeScene. And if they don't yet do it today, they'll have to get started soon.

Picking the best productivity tools is best left to the engineers. They know what works best and what doesn't. But that doesn't mean leaders shouldn't keep an eye on these experiments. While developers can vet the tools that make them more productive, they often don't look for the three other key decision-making criteria: compliance, community and team support.

1. Compliance

Compliance is the most straightforward one. Unless you run your own GPU servers, LLMs send data to the cloud. The text that is copy-pasted into ChatGPT ends up on OpenAI's servers. As a leader, you must understand whether this data is used for training or if there is some contractual protection. Sure, your engineers shouldn't copy sensitive customer data into Claude, but it's best to take precautions. Have your legal team double-check the fine print when selecting a tool. Most vendors have an offering that guarantees your private data is handled with care.

2. Community

AI-powered wonders are bleeding edge by definition, and it's very likely that something will not behave as expected. In that case, you need a tool that has a community to fall back on. A good community helps your team get the most out of the product. Cursor is a lot more popular than Roo, for example. That means Cursor-related issues will be solved faster. Such available community support should factor into the buying decision. New tools that are still in beta often don't even offer professional customer support. Pick a mature product that has some traction.

3. Team support

Finally, tools need to have company-friendly license management. While setting up a trial account is trivial, managing subscriptions per developer becomes a hassle. How easy is it to add a license for the new hire? How hard is it to scale down when the front-enders don't use the tool? Look for tools like Windsurf or Claude that support team plans with user management and centralised billing.

There is more to buying an AI tool than just getting the state-of-the-art. Yes, this productivity multiplier is the main reason for adopting such a tool in the first place. Your engineers are in the best position to validate that. But, leadership also needs to keep an eye on compliance, community and team support.

Look for an AI-powered tool that checks these three boxes and fits into the developer's monthly budget, and start shipping better and faster.