Signals are atomic observations captured from anywhere work happens. Error logs, team conversations, user complaints, build failures, design reviews — anything that makes you say "we should look at that" is a signal. They flow through a lifecycle, cluster into patterns, and promote into intent.
Think of signals like error codes. One error in a month is noise. The same error 12,000 times in a day is an emergency. Signals work the same way — frequency, co-occurrence, and cross-referencing reveal what matters.
Signals arrive from everywhere. A developer mentions friction in Slack. An error log spikes. A user files the same bug for the third time. A design review surfaces a gap nobody planned for.
Unrelated signals start referencing each other. Three signals from different sources all point at the same underlying friction. The system groups them — or a human notices the pattern. Either way, the cluster becomes visible.
A cluster with enough weight becomes a candidate intent — a real problem worth solving. The signal amplification score factors in frequency, recency, and cross-referencing to surface what's actually urgent, not just what's loud.