AI Agent Development
AI agent development becomes useful when an agent does more than answer: it uses sources, tools, rules, and approvals to complete a task.
Product systems and software architectures with Google Agent Development Kit (ADK), React Native & React
An operations exception cockpit brings alerts, affected records, cause hints, options, and ownership into one surface for faster resolution.
This is for operations teams that do not need more alerts, but fewer, better explained, and more actionable cases.
An exception cockpit turns signals into a prioritized worklist with cause, context, owner, and next action.
appamass combines React/Vite interfaces, TypeScript data models, and agent logic when operational exceptions need to be explained and handled under control.
The first cockpit slice should show one exception class from signal to close: detect, explain, assign, and track.
Operations teams do not need another alert list. They need a view that explains why a case matters and which action helps now.
Users see priority, history, affected data, possible cause, suggested action, and owner.
Event streams, Cloud Run APIs, Firestore or Cloud SQL, TanStack Query, React dashboard, rules, Agent Development Kit (ADK) evaluation, audit logs, and notifications connect behind the cockpit.
Priorities, owners, escalations, deadlines, action status, audit trail, and feedback on causes stay controlled.
The first build should turn many signals into a smaller set of workable cases.
Alerts or system events become a prioritized queue with context.
The case shows affected data, possible cause, comparison values, and open questions.
Assignment, status, comment, approval, and outcome stay in the same flow.
Related areas showing how mobile apps, React web systems, AI agents, and controllable automations fit together.