Last week’s post on the Claude Code leak surfaced something I keep coming back to: the most interesting engineering in a production AI agent isn’t the model, it’s everything around it. How context gets managed across a long session, how the memory is structured so the right details are brought to context when needed, how tools are designed to be composable and provide relevant functionality. As discussed last week, there’s a lot of engineering around the model to make it shine.At first, I thought that all of these patterns and techniques were hidden behind Claude Code’s closed source code, but then I started asking myself (as I briefly alluded in my last post), there’s already a lot of interesting open-source projects that I use on a daily basis implementing agent loops, what are this open-source equivalents doing compared to Claude Code? The Claude Code source showed us how Anthropic solved these problems, but how do Hermes Agent, Pi, and Opencode approach these same problems?I have…
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