Is anyone enjoying the process of deploying agentic AI for clients/employers? I have been working on stuff in the space ever since a senior exec at a client became enamoured with OpenClaw and I had the choice of either letting her go full foot-gun or enabling her to do what she wanted with agentic AI. I built a fair bit of stuff that sounds like this project to try and put some guardrails, observability, security, etc., around OpenClaw, but I have to say that the flakiness of the overall system is a huge turnoff for me.

The lack of predictable output/outcomes, the number of things that can go wrong (rate limits, this or that service stopping, a "cron" job seemingly disabling itself, permissions that don't stick, on and on it goes), does not make for an enjoyable development experience. People are getting value from it and on some level it's quite remarkable what can be done, but never in my life have users of my software had such little faith that what worked properly yesterday will work properly today. I have had far better results using LLM APIs.

I keep seeing these "Claw deployment" solutions, which is fine, but I am yet to see anyone who has deployed a claw solution and is directly making a lot of money from it.

It only seems to be the companies with hosted solutions themselves only making money and not the users. This resembles the people selling OpenClaw courses in how to use OpenClaw that are making money and not the users.

I keep seeing these "Claw deployment" solutions, which is fine, but I am yet to see anyone who has deployed a claw solution and is directly making a lot of money from it.

Deploy and manage AI agents in seconds

Overview

ClawRun is a hosting and lifecycle layer for open-source AI agents. It deploys agents into secure sandboxes (Vercel Sandbox, with more providers coming) and manages their full lifecycle, including startup, heartbeat keep-alive, snapshot/resume, and wake-on-message.

Learn more at clawrun.sh.

Features

🚀 Deploy any supported AI agent with a single command
💤 Persistent sandboxes that sleep when idle and wake on message
💬 Connect messaging channels like Telegram, Discord, Slack, WhatsApp, and more
🖥️ Web dashboard and CLI for real-time chat and management
💰 Cost tracking and budget enforcement across all channels
🔌 Pluggable architecture for agents, providers, and channels

Getting Started

npx clawrun deploy

The deploy wizard walks you through:

Choosing an LLM provider and model
Configuring messaging channels
Setting cost limits and network policy
Deploying to your chosen provider (e.g. Vercel)

Once deployed, chat with your agent from the terminal:

clawrun agent my-instance

Or open the web dashboard:

clawrun web my-instance

For full setup guides, framework examples, and configuration reference, see the docs.

Contributing

Report issues and suggest improvements on GitHub: Issues.

Join the community: Discussions.

License

Apache-2.0

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