Conversations, docs, and code context are noisy. Tenure pulls out what's worth keeping, tags where it came from and how confident it is, and gives you a chance to review it before it ever reaches the model.
Tenure extracts decisions, preferences, facts, open questions, expertise signals, and style signals instead of treating entire conversations as memory.
Project, domain, team, and user scopes keep one task’s context from leaking into unrelated sessions.
In observation or curated modes, Tenure can extract and show what it learned without automatically giving it to the model.
Tenure keeps capturing signal separate from trusting it. Extraction just creates candidates. What happens after that comes down to validation, scope, your memory mode, and merge policy.
Tenure watches the relevant context: a conversation turn, onboarding input, imported documentation, or IDE workspace context.
The model proposes structured memory objects instead of free-form notes: new beliefs, updates, open questions, aliases, and style signals.
Tenure parses, repairs when possible, drops invalid output, and enforces the authoritative project scope in code.
Depending on your memory mode, extracted beliefs are ignored, saved as suggestions, merged automatically, or used only for insight.
A belief isn't just an interesting sentence someone said. It's specific enough that, scoped and injected the right way, it actually changes how the model behaves next time.
RAG stores the source text and digs through it again later. Tenure pulls out the actual claim, keeps track of where it came from, and hands the model that one small, useful belief instead of a pile of old transcript.
Later retrieval has to rediscover the useful fact from surrounding noise, stale turns, and unrelated context.
User: We switched validation to Zod... Assistant: Sure... User: Actually only at API boundaries...
The model receives the compact, scoped state it can use immediately, with provenance behind it.
{
type: "decision",
canonical_name: "zod_api_boundary_validation",
content: "Use Zod for validation at API boundaries.",
scope: ["project:billing-api"]
} The conversion point: Tenure can learn what it would remember before you allow that memory to affect model behavior.
Once your work turns into structured beliefs, your team can review them, merge them, replace outdated ones, audit the history, and decide exactly when they reach the model.