The Harness Within the Harness: PR Council, a Runnable Experiment in Agentic Engineering
Taking the ideas from the series and turning them into a runnable experiment in agentic engineering.
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Dude, how does this help me?
Putting the pieces together: how I’m using agentic systems in my daily workflow and the patterns that have stuck along the way.
The Harness Within the Harness: Context as a Control Surface
A context parameter seemed like a small addition to my MCP tools. Then I watched the outer harness use it to steer an investigation, again and again.
Maybe I Was Asking the Wrong Question About AGI
I started by asking whether autoregressive LLMs could ever reach AGI. The better questions turned out to be what AGI means and where we draw the boundary around the system expected to achieve it.
The Harness Within the Harness: A Portable Application Boundary for Coding Agents
Keep the workflow, swap the coding harness: using MCP as a portable boundary around bounded, durable agent applications
Runtime QA: Give the Agent the Loop, Not the Last Word
Runtime QA is judgment from end to end, so let the agent own the investigative loop. Separate its judgment from reviewable mechanics, stop for the decisions that carry consequences, and leave the last word with a person.
The division of the local harnesses
The most important question in AI architecture isn’t which model you use. It’s who owns the control loop. That choice affects cost, reliability, and how easily you can swap providers. In this article, I look at three categories of workflows and explore why the nature of the problem should determine the harness, and why code, rather than the model, should often drive the loop.