Driving AI Agents Through Flutter: World-Class Agentic Development for Senior Engineers

how do you write a good prompt for an AI coding agent?

A useful prompt is task-precise: it names the exact Flutter work to be done, feeds the agent the right context and scope, and sets clear acceptance criteria so you can judge the result. Rather than one big instruction, you steer the agent mid-task through dialogue, correcting course as the code takes shape. This kind of prompting and directing is a core stage of the course.

how do you review code written by AI?

You read AI-generated code critically instead of trusting it, checking whether it actually matches the scope you asked for, holds up under edge cases, and meets your quality bar. When it falls short you correct and refine the output efficiently and debug the failures it introduces, treating yourself as the owner of quality. Reviewing and correcting agent output is one of the stages covered here.

who is responsible for quality when AI writes most of the code?

The engineer is — when agents write roughly 90% of the code, your value shifts to review, testing, and acceptance. That means directing agents to build a real test suite, owning UAT for AI-built features, and deciding what is actually ready to ship. The course treats this ownership as the heart of world-class 2026 practice.

how do you set up a Flutter project to work with coding agents like Claude Code or Cursor?

You prepare an agent-ready workspace so tools like Claude Code and Cursor have the context, structure, and guardrails they need to work on real Flutter tasks. This includes scoping how much of the codebase the agent sees and establishing standards the agent should follow. Setting up this workspace is part of the foundations stage.

what does an end-to-end AI-first development workflow look like?

It runs from prompting and directing the agent, through critically reviewing and correcting its code, into building a test suite and owning UAT, and finally shipping to a defined standard. Each handoff between you and the agent is deliberate, with you owning acceptance at every step. The course walks through this full agentic delivery workflow on real Flutter work.

how do teams set standards for using AI to write code?

Teams agree on shared conventions for how agents are prompted, how their output is reviewed, what the test and acceptance bar is, and who signs off before shipping. Establishing these AI-first standards keeps quality consistent when much of the code is machine-written. The final stage of the course covers setting team standards for AI-first Flutter development.