5 Steps to Productive AI Coding
1. Create clarity around potential and risks
We start with your current situation: Which tools are already in use? Which teams should be enabled? Which projects are suitable for getting started? Which risks or limitations exist around data, security and compliance?
2. Set up the right working environment securely
Together with your team, we set up the right working environment. This is not about promoting a specific tool. It is about a setup that can truly be used in your project.
3. Use AI coding on real tasks
Your developers work on real tasks from their own backlog. They experience directly how AI coding impacts specification, implementation, testing and review.
4. Support teams in day-to-day project work
During the coaching phase, we support your team in daily project work. We help identify good patterns, avoid poor patterns and continuously improve the way of working.
5. Anchor knowledge sustainably in the company
The experience gained is turned into playbooks, guidelines, review rules and internal champions. This keeps the knowledge within the company and allows it to be transferred to further teams.