

The conversation around AI coding assistants keeps speeding up, and we are hearing the following questions from technology leaders:
- Which flavor do we bet on—fully-agentic tools (Claude Code, Devin) or IDE plug-ins (Cursor, JetBrains AI Assistant, Copilot)?
- How do we evaluate these tools?
- How do we effectively roll out these tools?
At the top level, I think about:
- Agentic engines are happy running end-to-end loops: edit files, run tests, open pull requests. They’re great for plumbing work, bulk migrations, and onboarding new engineers to a massive repo.
- IDE assistants excel at tight feedback loops: completions, inline explanations, commit-message suggestions. They feel safer because they rarely touch the filesystem.
Here’s a pretty good roundup:
The Best AI Coding Tools, Workflows & LLMs for June 2025.
Most teams I work with end up running a hybrid—agents for the heavy lifting, IDE helpers for day-to-day quick work items.
Whichever path you take, the practices you use matter the most.
Some examples to get you started:
Reading list