OpenClaw user automates dating app interactions with AI agent
Automating dating app workflows with OpenClaw
A user on r/openclaw shared their experience building an AI agent to automate interactions on dating apps. The agent was created using OpenClaw to reduce time spent manually managing dating app activities.
Agent capabilities
According to the source, the agent performs these specific functions:
- Swipes based on user preferences
- Starts and continues conversations
- Personalizes replies using information from bios
- Filters matches
- Helps set up dates
Results after one week
The user reported these metrics after approximately one week of using the automated agent:
- 500+ swipes per day
- 3 times more matches compared to manual use
- Approximately 40% reply rate to messages
- 10+ active conversations running simultaneously
This type of automation demonstrates how AI agents can handle repetitive interface interactions and conversation management. The approach could potentially be adapted to other platforms requiring similar interaction patterns.
📖 Read the full source: r/openclaw
👀 See Also
How Cheap AI Agents Stress-Tested Claw Earn Marketplace Development
The Claw Earn team intentionally used cheaper, less capable AI agents during development, which exposed failures related to outdated scripts, stale memory, and incorrect assumptions. These failures forced improvements to documentation and platform robustness.
OpenClaw Bot Automates KMZ Data Extraction and Spreadsheet Merging
A user reports using OpenClaw bot to parse KMZ files, extract eight specific data points including mile markers, calculate decimal mile positions with high accuracy, and merge new data into existing spreadsheets without overwriting. The process took 5 minutes of processing time and 15% of a $100 max plan session budget.
Non-coder builds live MLB dashboard using Claude AI and Claude Code on GitHub Codespaces
A user with no coding experience used Claude chat and Claude Code on GitHub Codespaces to build a live MLB dashboard with injury reports, game scores, and team stats, deploying it to Vercel.
Non-Coder Builds AI Prompt Diagnostic Framework with Claude Over Many Sessions
A non-coder built SMARRT, a diagnostic framework that audits AI prompts before generation, entirely through conversational collaboration with Claude over many months.