agents. But we took a step back. We didn't do any of that. We like all of us, we went back to Cloud Code. So, we opened a very plain empty directory. I ran Cloud Code. Then give it just bash and the database. Then give it an actual signal which we identified. Then started observing what it is doing. So, while we look at what code does, we are able to figure out fix for all the three issues we discussed. The first the first part. So, what was happening is the agent was looking at data and deciding on a signal. Sometimes it applied some statistical methods. Sometimes it barely look at the data and say this is a signal. Sometimes it's actually a signal. Sometimes it's a noise. This is something we don't want an agent to do. This is a completely deterministic workflow. So, we separated it out from the agentic system. So, we built a pure deterministic workflow with different statistical methods. We put guardrails. We put thresholds. We put prioritization. Everything happened before the agent even kick starts. So, we ran an automated pipeline which scans through the data. Identify signals for each of the KPI. Is anything happening with that? Any anomalies which is happening? Any trend which is very uh any trend which is breaking. Based on that, we identified a signal, we put it on a queue. The moment a signal comes to the queue, the agent wakes up. So, the agent's job is to investigate, not to identify. The second part. So, mainly the issue which we previously what Subair was mentioning, there's no coherence in the output which the agents produced. So, we started consolidating. We look at how cloud code operates. It's able to do a lot of operations, so we started designing around that. So, it's repeatedly writing a function and querying database. So, we give it a tool for that. So, this consolidated the entire process into a single agent. That doesn't mean that we didn't do parallelism. We still do parallelism. What we removed is, do we need distributed reasoning? We didn't but the judgment to be distributed between agents. That we wanted to consolidate to a single agent. So, that what exactly what we did. Then occasionally we observed cloud code, it's launching sub-agents dynamically for a very particular focused task. So, we did the same thing. Because if suppose you want to understand if rapid activity in a particular region, that's an investigation which you need to run. That you can still delegate to a sub-agent. You can get back the uh results back, not the reasoning or the judgment. That is still controlled by the by the main agent, but the investigation and a part of it we did we're delegating it to a sub-agent. So, these are some of the things we kept based on observing what cloud was doing cloud code was doing. So, that give us a more lighter architecture than what was