Choosing the right champions
Good champions are not necessarily the most senior engineers. They are the people who enjoy explaining, are respected by their peers and are curious about new tools. A mix of teams and technologies helps, so every department ends up with a contact who knows its projects.
Champions also need time for the role. Someone who only helps on the side cannot answer questions promptly, and the network loses impact. We recommend reserving a fixed share of working time for coaching, playbook maintenance and peer exchange.
How the programme is structured
neooutput's AI code engineers deliver the programme in several modules, remotely or on site. Between modules, champions apply what they learned in their own teams.
Between modules, champions collect experience in their teams: which questions keep coming up, where adoption stalls, which tasks suit agents especially well? They bring these observations into the next module. The result is material that answers the real obstacles in your company rather than theoretical ones. Champions also learn from each other, because teams with different technologies often run into similar questions and can share solutions across the network.
- Module one deepens Claude Code, OpenAI Codex and Cursor up to advanced features such as subagents, hooks and MCP.
- Module two develops playbooks, rules files and review standards for your company.
- Module three covers teaching: planning workshops, running live demos and dealing with scepticism.
- Module four has champions run their own trial sessions and receive structured feedback.
- Finally the network is organised, with regular exchange formats and a shared knowledge base.
Keeping knowledge accessible
As the champion network grows, a central knowledge base becomes essential. Playbooks, frequent questions and internal policies can be made available through kalAIDoCreate as a knowledge assistant, so developers find answers even when no champion is around.
Champions often give feedback on internal tools and interfaces as well. UXreviewer.io helps here by delivering AI-assisted improvement suggestions for user interfaces, adding a user perspective to the champions' technical view.
Frequently asked questions
How many champions do we need?
A practical rule of thumb is one contact per team or per technology area. Coverage matters more than headcount: every developer should know whom to ask.
Is neooutput still available after the programme?
Yes. neooutput's AI code engineers can continue to support the champion network, for example with new tool versions, difficult use cases or security questions.
Can champions also train non-developers?
Partly. The programme is designed for software teams. For product management or design, champions can offer adapted sessions, for instance on writing tasks for agents or understanding what agents can and cannot do.