Most production incidents do not start with a lack of data. They start with a lack of agreement. A service degrades. Pagers go off. A bridge call opens. Within ten minutes, three teams are on the same call looking at the same dashboards, and somehow each of them is describing a different system.

The hard part of an incident is rarely the response. It is the moment when several smart engineers reconstruct the same system in three different ways.

The tooling solved the wrong half

Modern incident tooling is good at the mechanics. Alerting routes correctly. Runbooks open quickly. War rooms spin up in seconds. Status pages update themselves. Postmortem templates are pre-filled. All of that is real progress.

But none of it answers the question that actually slows incidents down: *what is the system doing right now, and do we agree on it?*

The platform team sees a queue backing up. The application team sees an upstream timeout. The database team sees a slow query that is probably a symptom, not a cause. Each view is correct. None of them is the system.

So the first thirty minutes of most serious incidents are not spent fixing anything. They are spent translating between mental models.

The bottleneck is alignment, not information

Teams do not need more signals during an incident. They usually have too many. What they need is a shared, current picture of how the system is actually behaving — which flows are active, which calls are degraded, which services sit on the path of the failing journey, which dependencies just changed.

Signals are interpreted. Behaviour is observed.

When every team interprets independently, alignment is slow and political. When everyone is looking at the same behavioural reality, alignment becomes almost automatic. That is the shift. Incident response is a workflow problem. Incident understanding is an evidence problem.

The shift

Response is about who is paged, who is on the bridge, and how fast the runbook runs. Understanding is about whether the people on that bridge are looking at the same system.

The first is mostly solved.
The second is where the real time goes.

This is the direction CodeKarma is building toward — making the runtime behaviour of a system visible enough that incidents stop being a debate and start being a diagnosis.

You cannot fix a system faster than you can agree on what it is doing.