Smriti: Version control system for AI reasoning state

Smriti represents a novel approach to managing AI conversation contexts, addressing a critical pain point in multi-model and complex reasoning scenarios. By treating reasoning as an explicit, structured state rather than a linear log, the tool introduces 'checkpoints' that capture decision points, open questions, and thinking trajectories with unprecedented granularity.

The key technical innovation lies in its data layer isolation, where only relevant conversation turns are exposed during checkpoint mounting. This approach prevents context leakage and maintains strict boundaries between different reasoning paths, a significant departure from traditional chat interfaces. Developers and AI researchers will find particular value in its ability to fork thinking paths, compare divergent reasoning approaches, and seamlessly switch between models without losing contextual nuance.

While currently in early stages with acknowledged limitations like single-user support and lack of mobile integration, Smriti signals an important conceptual shift in how we conceptualize and manage AI reasoning workflows. Its potential applications span AI agent development, complex problem-solving, and knowledge work, suggesting a future where reasoning itself becomes a more intentional, reproducible process.