Magic

Start with one bounded workflow for AI software engineering platform focused on long-context code reasoning, generation, repository understanding, and development automation. Define the input context, expected output, connected tools, permissions, acceptance criteria, and the actions that must remain behind human approval.

Run Magic on representative tasks and inspect what it actually does rather than judging only the final answer. For coding products, review diffs and tests; for customer or revenue agents, inspect conversations and CRM actions; for automation infrastructure, trace tool calls, credentials, retries, and state transitions.

Expand permissions gradually after the workflow is reliable. Use least-privilege credentials, separate test and production environments when available, preserve logs, and make destructive or externally visible actions reversible or approval-gated.

Monitor completion quality, overrides, latency, cost, errors, model or integration changes, and user feedback. Re-test the workflow whenever new tools, models, data sources, or autonomous actions are introduced.