Reasoning reuse (cache the chain of thought): how it works and when to use it
Reasoning reuse (cache the chain of thought), stores a chain-of-thought trace as a reusable step graph and replays it for the next query that shares its shape, at roughly 15% of the original token cost. Here's how Crowkis does it and why it matters for cost and safety.
The cheapest token is the one you never spend twice. Reasoning reuse (cache the chain of thought) is how Crowkis stores a chain-of-thought trace as a reusable step graph and replays it for the next query that shares its shape, at roughly 15% of the original token cost.
How it works
Crowkis stores a chain-of-thought trace as a reusable step graph and replays it for the next query that shares its shape, at roughly 15% of the original token cost. It runs inside one Redis-compatible engine, so it composes with semantic caching, agent memory, and the other intelligence layers instead of being a separate service you wire together.
CTHINK "amortize 12000 over 24mo at 6%" "step1 ... payment=" CREUSE "amortize 8000 over 36mo at 5%"
Why it matters
Repetitive LLM workloads are where the money is, and semantic caching can cut costs up to 60-70% on repetitive workloads. Reasoning reuse (cache the chain of thought) is part of what makes that reuse safe rather than reckless, the difference between a cache you trust in production and one you audit after every incident. Community edition ships at full power, free to run.
Infrastructure earns the critical path one boring, verifiable feature at a time.