Every team has a different comfort level with AI memory.
Tenure meets you where you are, and evolves as you're ready.
These aren't tiers. They're different philosophies. You can mix them, run them in parallel, or start with one and expand as your team gains confidence.
For organizations that want AI grounded in Confluence, ADRs, READMEs, and coding standards. Nothing the model receives was learned from conversation or behavior. It was written down by a human and explicitly approved.
Tenure continuously discovers conventions and patterns from documentation, code, and conversations. But nothing reaches the model until a human approves it. The memory evolves intentionally, not automatically.
Tenure discovers conventions, decisions, and expertise automatically. Context is retrieved per turn, so topic switches don't drag irrelevant memory into the conversation. Memory doesn't sit static. It reflects how the team actually builds.
Turn work into weekly summaries, expertise maps, and organizational insights. The model never receives memory. You do. Reflective Intelligence is for teams that want to understand what's happening before deciding whether to act on it.
You don't have to learn from everything you inject from, or inject everything you learn from. Configure each axis separately, per team or per project.
Start conservatively. Expand as trust is earned. The configuration is yours to change at any point.
You set the terms. You decide what gets learned, what gets injected, and what stays human-facing.
Trust isn't binary. It's configurable. Tenure is built for teams that want to set the terms.