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How I use AI models and agents in client work

Claude, ChatGPT, Copilot, Cursor and Codex speed up delivery. Here is where they help, and where a person still decides.

Vyntro, a SaaS product that turns client requirements into project scopes

I use AI models and coding agents every day: Claude, ChatGPT, GitHub Copilot, Cursor and Codex. They are part of how I deliver 50+ web and eCommerce projects without cutting corners on quality.

Where AI helps

  • Drafting boilerplate, tests and migration scripts so I can spend time on the hard parts.
  • Exploring an unfamiliar codebase or a legacy plugin before I touch it.
  • Turning rough client notes into a structured brief and a first-pass scope.
  • Reviewing my own work for edge cases I may have missed.

Where a person still decides

Architecture, security, data models and anything that touches a client's customers. Generated code is read, run and tested like any other code, and nothing ships that I cannot explain.

Building the bridges myself

I also build the tooling that connects products to AI agents: Model Context Protocol (MCP) servers and AI-integrated plugins with multi-provider support. That lets a WordPress site or a SaaS product take part in an agent workflow in a controlled, reviewable way.

What clients get

Faster delivery, more time spent on the decisions that matter, and one person accountable for the result from scoping to production.

  • AI
  • MCP
  • Workflow

In short

AI writes the first draft. I own every line that ships.