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
Frontend development makes forms, tables, dashboards, dialogs, and status states feel like one coherent product.
This covers product surfaces with many states: tables, forms, dialogs, empty lists, errors, saved drafts, and approvals.
A good frontend reduces uncertainty because it shows what is happening, what is missing, and which action is allowed now.
appamass keeps React/Vite, Tamagui, TypeScript contracts, and backend state together; agents enter when they prepare decisions or explain context.
The first useful build is a real workspace with real data and real error states, not only a set of polished components.
A good frontend reduces uncertainty. It shows what is happening, what is missing, what is risky, and which action is currently possible.
Users see clear states: empty, loading, failed, saved, waiting for approval, or ready for the next action.
React, Vite, Tamagui primitives, TanStack Query, TypeScript, routing, server data, forms, accessibility, performance, Vitest/Playwright checks, and monitoring sit behind it.
Components, design tokens, loading states, form validation, roles, instrumentation, and regression tests stay controlled.
The first step should show a real workspace, not isolated UI pieces. That quickly reveals whether structure, data, and interaction work.
Buttons, lists, tables, forms, and status states are built consistently and reused.
The surface shows real loading, error, empty, and success states from backend data.
Accessibility, performance, visual consistency, and tests are developed with the interface.
Related areas showing how mobile apps, React web systems, AI agents, and controllable automations fit together.