I help companies identify where AI can deliver practical value in products, services and workflows – and turn ideas into something that can be tested. This may involve AI agents, automation, integrations with existing systems or technical prototypes that help inform further development.
I build and test solutions myself, working with language models, APIs, Python, n8n and MCP (Model Context Protocol). With my background in product development and business, I can contribute hands-on while also assessing what is relevant, feasible and worth investing in.
But successful AI adoption involves more than technology. I also consider how new ways of working affect people and organizations, including questions of trust, quality, accountability and governance. The goal is not just to demonstrate that the technology works, but to create the conditions for it to be put to practical use.