Find where AI actually helps
Look at an existing workflow or problem and identify where AI, automation or a small internal tool can remove meaningful manual work—and where AI would only add unnecessary complexity.
Design the workflow
Define how models, prompts, data, APIs, external tools, approvals, human steps and automation should fit together.
Prototype it quickly
Build a focused prototype that can be tested with real users and real data before committing to a larger implementation.
Build the real thing
Implement the solution end to end: frontend, backend, AI integration, APIs, database, authentication, deployment and production workflows.
Not every problem needs AI. Sometimes the best AI decision is not to use it.