Mujtaba Ayub

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Purpose-Built AI & Decision Tools

What would a savvy financial analyst flag for the GM this week?

The Monday Morning Brief - Brought to you by Your AI Agents

Agentic market intelligence that triages signal from noise |An auto-updating executive brief with anomaly investigation

Personal build

AI agents detecting an anomaly, investigating it, and assembling an executive brief. On the left, data streams feed a set of agent nodes that detect and investigate an anomaly. On the right, the agents assemble a finished one-page executive brief. market data anomaly detected detect agent investigate agent draft agent Monday Brief decision-ready · every Monday

The problem

Most market monitors aggregate news. Very few know what a GM actually cares about: what is material, what is noise, and what deserves a second look.

The approach

Encode the judgment of the person who writes the Monday brief: materiality thresholds, so-what triage, and decision-ready framing. When the quantitative layer spots an anomaly, an agent goes and builds the explanation rather than just flagging it.

What it revealed

What sets this apart is the embedded judgment rather than the monitoring itself. The agent behaves the way a strategy manager does: it notices the outlier, then investigates why, and returns a brief a GM can act on in minutes.

Under the hood

Python · time-series analysis · LLM agents · scheduled jobs