AI without context generates generic output. Hamster builds a unified context graph so AI actually knows your product.
For years, teams have made decisions and lost the reasoning in delivery. There was nowhere for it to go. A constraint discussed in a meeting that was never written down. A pattern spotted in recent user calls. A Slack decision from six weeks ago that shaped the entire architecture.
The context graph changes this. Hamster connects to your GitHub repos, Linear projects, Slack channels, uploaded docs, and team activity. It builds a unified understanding of your product — not by asking you to document everything, but by being present when decisions happen.
When AI generates plans, expands tasks, or answers questions — it references real files, real patterns, and real constraints. Not generic boilerplate.
Decisions in Slack
Six weeks ago your team decided to use WebSockets over polling. The reasoning lives in a Slack thread nobody will find again — unless the context graph surfaces it when an agent plans the real-time feature.
Patterns from user research
Three customers mentioned the same friction point in recent calls. That insight shapes what to build next — but only if it reaches the brief. The context graph connects it.
Constraints from meetings
Legal flagged a compliance requirement in last month's review. It was never captured in a ticket. The context graph ensures it shows up when Hamster writes the brief.