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TL;DR: AI application architecture will be divided again according to responsibility. Cognitive structures that help models understand, reason, plan, remember, and correct themsel…
TL;DR: The three paths ultimately converge because real tasks simultaneously require understanding the current situation, reusing historical experience, and executing real actions…
TL;DR: The final form of agents is not one path winning over the others, but the convergence of execution, self-evolution, and personal context into a governed Agent Runtime. This…
TL;DR: The core of the personal context path is transforming agents from general assistants into assistants that truly understand your situation. It will evolve from preference me…
TL;DR: The core of the self-evolution path is making agents stop treating every interaction like a first meeting. It will progress from in-conversation learning to long-term memor…
TL;DR: The core of the execution path is moving agents from “giving advice” to “completing tasks.” It will evolve from tool calling to browser operations, local automation, and go…
2026 marks an interesting fork in open-source agents: some projects focus on “making AI actually do things for you,” others emphasize “long-term self-growth,” and still others pri…