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Notes on lifecycle management
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Agentic Context Management: Solving Agent Memory and Cost by Treating Them as Lifecycle and Architecture Problems
The article proposes a new discipline called Agentic Context Management (ACM) to address issues faced by AI agents in managing their reasoning context, such as conversation histories and large prompts. The authors…
Agentic Context Management: Solving Agent Memory and Cost by Treating Them as Lifecycle and Architecture Problems
The paper discusses Agentic Context Management (ACM), a new approach to managing the context in which AI agents operate. It argues that current methods for managing an agent's context, such as storing and retrieving…
Agentic Context Management: Solving Agent Memory and Cost by Treating Them as Lifecycle and Architecture Problems
The paper presents Agentic Context Management (ACM), a solution to the issue of AI agents being overwhelmed by their own accumulating history and growing token cost in production settings. The authors argue that…
Proof-or-Stop: Don't Trust the Agent, Trust the Evidence -- Loop Engineering for Verifiable Evidence-Gated Lifecycle Control
The paper presents Proof-or-Stop Lifecycle Control, a method that ensures software work transitions only when supported by verifiable evidence. The method was tested using an open-source implementation and showed…
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