The harness is all you need (mostly)
GitHub developer advocate Burke Holland argues that with AI coding, your biggest productivity lever is mastering the harness—the shared agent interaction/execution framework behind GitHub Copilot CLI, the Copilot app, and IDEs—not chasing new models, MCPs, or clever prompts. The post walks through a repeatable 8-step workflow: start with the Copilot CLI/App and enable YOLO mode (allow-all) inside a Codespaces sandbox; prototype aggressively with one prompt that generated 20 date-picker mockups in a single HTML file or Mermaid diagrams for API options; refine requirements in /plan mode (optionally with the 'grill-me' skill); implement in Autopilot, which automatically dispatches subagents like Explore on small models and General Purpose on larger ones; then iterate via human reviews and finish with a Rubber Duck review from a different model family (e.g., GPT-5.6 Terra asks Sonnet), optionally looping with /autopilot until diminishing returns. The article also advises keeping one model and reasoning level fixed to benefit from prompt caching, running YOLO mode only in sandboxes, and never settling for 'good enough' output.