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.
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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 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.