OpenClaw Developer Achieves AI Agent Breakthroughs with Uber and Restaurant Booking Automation
An OpenClaw developer has made significant progress in browser automation, moving beyond the limitations that previously blocked AI agents from interacting with real websites. The developer has successfully created agents that can autonomously complete complex tasks on live sites without scripted demos.
What Actually Works Now
The developer has achieved successful completion of full flows on two major platforms:
- Uber: The agent opens the app, enters pickup and destination locations, selects ride type, and reaches the confirmation screen
- Restaurant booking: The agent finds a restaurant, fills out reservation forms, and confirms bookings
These aren't scripted demonstrations. The agents navigate real websites, handle dynamic elements, and successfully bypass bot detection systems.
Current Technical Stack
The working solution consists of several integrated components:
- Stealth browser with persistent profiles and fingerprinting
- Residential proxy routing
- CAPTCHA solving integration
The developer notes this is functional but not yet a polished product—it's currently "a bunch of pieces duct-taped together that require manual setup."
Development Direction and Community Input
The developer wants to transform this proof-of-concept into something usable by any OpenClaw user, but is seeking community feedback before building the "ideal" version. The long-term vision is "install a skill, your agent gets a full browser environment with your saved sessions, and it can go do things on the web autonomously."
For immediate development, the developer is asking the community specific questions:
- What specific automation tasks have failed due to browser limitations?
- What sites/services do you wish your agent could use? (Uber, Airbnb, LinkedIn, government portals, food delivery, etc.)
- What format would be most useful right now?
The developer presents several format options for community consideration:
- a) An OpenClaw skill that gives your agent a stealth browser
- b) A standalone tool you run on a VPS and connect your agent to
- c) A desktop browser app that handles anti-detection, sessions, and fingerprinting out of the box
- d) Just a setup guide so you can wire the pieces together yourself
- e) Something else
The developer also asks whether users would accept a VPS requirement or need local machine functionality.
📖 Read the full source: r/openclaw
👀 See Also
Open source Next.js starter kit adds guardrails and agent instructions to prevent AI slop
A new Next.js boilerplate includes auth, database, CI, tests, and Claude Code instructions out of the box, aimed at developers using AI coding agents to build production apps faster.
Using a Local LLM as a Claude Code Subagent to Reduce Context Usage
A Reddit user demonstrates how Claude Code can delegate tasks to a local LLM running via LM Studio, keeping file content out of Claude's context. The setup uses a ~120-line Python script with LM Studio's tool-calling API to handle file operations locally.
Parallel Sub-Agents in Claude Code: When They Save vs. Burn Tokens
Anthropic reports multi-agent systems use ~15× more tokens than a single chat, but prompt caching offers 90% discount on tokens. Whether sub-agents save or burn money depends on cache hit rates.
Open-source Specialist Dispatch adapter delegates complex tasks to Claude Code
expert-dispatch is a ~500-line bash script that lets a cheap AI assistant delegate complex coding tasks to Claude Code CLI. It uses commands like dispatch-cc run to send tasks and maintains per-project directories with CLAUDE.md for persistent context.