Role: Product Designer & Developer Timeline: 2025 Tools: Vanilla JavaScript, n8n, CSS Grid, WebSocket Streaming

Most AI chat interfaces are locked into specific platforms or require heavy frameworks. Teams building custom AI agents or workflows need a lightweight, flexible front-end that can connect to any backend — without the bloat of enterprise chat SDKs or the limitations of hosted solutions.

Built a production-ready chat UI that works with any webhook-based AI service. Clean, fast, and fully customizable — designed specifically for teams using n8n or custom AI workflows who need a polished interface without the overhead.

Multi-modal input: Text, images (drag-and-drop, paste, upload)

Real-time streaming: Natural conversation flow with token-by-token display

Session management: Persistent chat history across browser sessions

URL parameters: Share specific prompts via links (?p=your prompt)

Slash commands: Quick actions (/help, /history clear, /tools)

Dark mode: Auto-adapts to system preferences

Zero dependencies: Pure vanilla JavaScript, no frameworks

Responsive: Works seamlessly on desktop and mobile

Modular JavaScript structure (components, core, utils)

CSS Grid/Flexbox responsive layouts

CSS variables for easy theming

ES6 modules for clean separation of concerns

Webhook-based AI connection (works with OpenAI, Claude, Ollama, n8n, custom APIs)

Configurable endpoints for text and image processing

Streaming response support

Session ID tracking for conversation continuity

Simple config file for webhook URLs

One-click Replit deployment

Modular CSS structure for easy customization

Clear component patterns for extending functionality

Custom agent interfaces without building from scratch

Rapid prototyping of conversational AI experiences

White-label chat UI for client projects

Front-end for n8n AI workflows

Interface for custom RAG systems

Multi-modal input handling for image + text processing

Learning resource for vanilla JS chat implementations

Base template for custom AI interfaces

Example of clean, framework-free architecture

Most companies building AI agents either settle for generic chat UIs or spend months building custom interfaces from scratch. Steve Chat bridges that gap — it's production-ready but fully customizable, framework-free but feature-complete.

No framework lock-in: Works with any backend, any AI service

Multi-modal from the start: Image support isn't an afterthought

Developer-friendly: Clear structure, easy to modify, well-documented

Performance-focused: Vanilla JS means fast load times and simple debugging

👉 GitHub Repository 👉 Deploy-ready on Replit

I understand the full stack of building custom AI chat experiences — from designing intuitive multi-modal inputs to architecting clean, maintainable code. I know what teams building AI agents actually need: flexibility, performance, and the ability to customize without fighting a framework. This isn't a demo — it's a foundation for production AI interfaces.