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JevMade field notes / 10-step tutorial

Jev Engineering: Full 10-Step Roadmap to Set Up and Use a New Brain for AI (from scratch)

A hands-on route from a Playground question to a Python task router that saves Jev’s worker choice to a local queue, then extends the pattern to dynamic browser actions and agent review gates.

Original by codilaAgent workflowsX articleOriginal published Source reviewed

Before you dive in

What you’ll find in the original

  1. Start with one bounded worker choice; research and writing remain separate tasks for tools or generative models.
  2. Save the chosen route and confidence in a local job file, then connect real workers only after the standalone handoff works.
  3. Refresh available actions after each tool result and keep spending limits, publishing approval, and completion checks in application code.
Worth knowing

The starter saves JSON jobs but does not run workers. Its 0.85 review threshold is an example to tune on labeled cases; flight-search speed and cost are attributed to Browser Use, not independently measured here.

More guides →See the experiments →