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Handover of In-Context Learning State Across Session Boundaries

This study investigates the methodological and theoretical properties of session handover in applications that use large language models. A task may continue in a new session when the context reaches the model's input limit, when the application restarts, or when another agent is asked to finish the task. The application must then decide which information from the earlier session to pass on. We…

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Why GPT-5.6 Luna High Is My Default for Agentic Engineering

I used to pick coding models the same way people pick sports cars: choose the most powerful one and pretend the fuel bill is somebody else's problem.

  • GPT-5.6 Luna favored for agentic engineering tasks
  • Low input ($0.20) and output ($1.20) token costs
  • High reasoning effort ensures effectiveness

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