AI engineering for real workflows
AI with a clear job to do.
I help teams turn a defined workflow into an AI feature they can test and improve. The work may involve an agent, an MCP server, or a direct integration with software they already use.
Discuss an AI projectWhat we can build.
AI agents
Give an agent a bounded task, useful context, and access to the tools it needs, with clear points for review.
MCP servers
Connect AI applications to existing tools through the Model Context Protocol, with capabilities scoped to the workflow.
AI product features
Put AI inside a web or mobile product, connected to the relevant data and services rather than isolated in a demo.
Start with the workflow, not the model.
What is slow or difficult today? Who uses the result, and what information can the software access? Those answers help us decide whether an agent, a simpler integration, or a conventional software feature is the right solution.
I can connect that work to a web or mobile interface using my Next.js, Flutter, and React Native experience.
Build something you can evaluate.
Before rollout, we should agree on examples of a good result, failure cases, permissions, and where a person remains in control. That makes a prototype useful for making a real product decision, not just a convincing demonstration.
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