AI-native team
Stop solving the same problem twice.
This is the one Kythene was built for. Many people, each with their own AI instances, all producing work in parallel - and no way to see what anyone else's AI already worked out.
The situation
In an AI-native team the real work happens between a person and their instance, and it stays there. Someone's Claude spends an afternoon working out how a subsystem behaves; the next day a teammate's Claude works it out again from scratch, because that context never left the first chat. The same problems get solved twice, the same decisions get re-litigated, and nothing accretes. The more people you add, the more you re-derive.
What Kythene does
One shared context layer for the whole team. Every output people and their instances produce is visible on the timeline, and every instance can recall a teammate's work over MCP and build straight on top of it - across Claude, Codex and any other MCP-capable tool.
Shared memory sits underneath it. When one person's instance works something out, it remembers it, and the whole team recalls it. The context compounds instead of evaporating, so the team gets faster as it goes rather than slower.
The win: nobody re-derives what a teammate's Claude already knows. The team compounds.
Make it known.
Give your team and their instances one place to publish, read and remember.