Will Future Assistants Overcome Current Limitations in Context and Thread Control?

Based on current trends and research directions, the expectation is that assistants will evolve to offer much better built-in control over context and threads. While today's limitations—like opaque context handling and cost issues—are real, ongoing improvements in API design and context management indicate that future systems are likely to incorporate more granular control mechanisms.

Here are some points to consider:

• Evolution of APIs: Developers and researchers are actively exploring ways to include more explicit context management in conversational systems.
• Context Control: Improved control over threads would allow more consistent and explainable conversation handling, which is a priority given the growing demand for transparency.
• Technical Advancements: As machine learning platforms mature, we can expect enhancements in tracking long-term context, thread separation, and memory control, reducing the current limitations.

In summary, while today's assistants might face constraints, the balance of technical progress suggests that future architectures (option 2) will indeed provide significant built-in control over context management.