Five Agents Compared
The agent landscape in mid-2026 has crystallized into distinct architectural philosophies. This post compares five entries. Four of them — Claude Code, Crush, OpenClaw, kcp-agent — are standalone tools, each successful, each widely discussed, representing fundamentally different answers to the question "what should an agent be?"
This is not a feature matrix. It's an architecture comparison. The interesting part isn't which one is "better" — it's what each one assumes about the problem, and where those assumptions diverge.
The fifth entry, pi-kcp, is a different kind of thing, and the difference is worth being precise about up front. It isn't a standalone product you'd install instead of the others — it's the KCP governance stack integrated into Pi, an independent coding-agent harness; you'd encounter it as part of choosing Pi as your coding agent. It gets full table presence anyway, because it does something none of the other four do: it verifies its own execution against what was approved — digesting what a gate approved for a tool call and, separately, what actually executed, keyed to the same call, and flagging divergence. Along the way it also settles a question the layering argument below would otherwise leave open: whether the deterministic knowledge layer really can be lifted out of one agent ecosystem and dropped into a completely different one. We'll get there.
