The harness is all you need (mostly)

If you’re feeling overwhelmed by AI right now, you’re not alone. Every day it seems there is a new tool, new MCP, new model, new skill, new workflow, new feature, new social post that is some form of “Hey look! I have completely figured out AI with this one weird prompt.” I…don’t believe you. I work with AI every single day, and what I’m finding is that less is way more. It’s not about what I install or configure or trick the agent into doing that makes any real difference. That stuff is interesting, but at the end of the day it feels like gimmicks. I see the biggest gains in my productivity from how I use the harness and how well I understand it. So in this post, I’m sharing you a simple workflow that you can use to drastically improve your effectiveness with AI just by using existing features of GitHub Copilot . No weird prompts. No skill everyone else seems to know about. Just the harness. The harness is all you need—mostly. Disclaimers I’m using the term “harness” interchangeably with “GitHub Copilot.” The point of this post is to keep things simple, so just know that GitHub Copilot is an agent harness. I don’t mean to insinuate that you won’t ever need any skills or MCPs or instructions or custom agents, etc. In fact, those things will become quite important as you progress and need to define complex workflows and automate things for your teams. In fact, I use a few throughout this blog post! What I am pointing out here is that you do not need any of those things to be highly successful with AI. Also, there is a lot of slop out there. If you don’t believe that, ask the agent to create a skill to do anything at all. It will happily oblige. Whether or not that generated skill actually works, it can be easily published to any number of skill or MCP registries. 1. Pick a tool, any tool This is an obvious one, right? Pick a tool! It’s so easy! But even within the GitHub Copilot family, there are a lot of options. These include the CLI , the new GitHub Copilot app ,