All in one hosting infrastructure for long running agents
My Agentic Coding Setup, July 2026
With the right tools, coding agents can run autonomously, in parallel, and be reachable from anywhere. Here's how I've stitched them together.
Claude on Twitter / X
With self-hosted sandboxes, you can run agents in any environment you control: your own infrastructure, or managed providers like Cloudflare, Daytona, Modal, or Vercel. pic.twitter.com/OELUCt7QRf— Claude (@claudeai) May 19, 2026
Where Should the Agent(s) Live? – OpenComputer
Isolation models, agent placement tradeoffs, credential design, and sandbox lifecycle patterns for agentic systems.
Herdr: one terminal for the whole herd
To coding agents what tmux is to terminals. Runs where your agents run: close the laptop, ssh from anywhere, nothing dies.
Coasts — Containerized Hosts for AI Agents
Free, open source parallel runtimes for AI agents. Run multiple isolated environments on your machine — no cloud, no conflicts.
dagger/container-use
Development environments for coding agents. Enable multiple agents to work safely and independently with your preferred stack.
Container Use for Locally Sandboxed, Background Agents in Zed
From the Zed Blog: Run AI agents in parallel without interference using containerized environments and Git Worktrees.
Shared Server · Omnigent
Deploy the Omnigent server so your agents are reachable from your phone, shareable with teammates, and running while your laptop sleeps.
shepherd-agents/shepherd
A runtime substrate that turns an agent's execution into a reversible, Git-like trace, so meta-agents can observe, fork, replay, and revert any run. Couples agent and environments in a copy-on-write fork ~5x faster than docker commit, with ~95% KV-cache reuse on replay. Framework built for meta-agents to supervise, optimize, and train other agents
A Web Terminal for My Homelab with ttyd + tmux
How I run terminal.mrkaran.dev with ttyd + tmux and tune it for agentic workflows
New capabilities for building agents on the Anthropic API | Claude
Claude now offers code execution, MCP server connections, file storage, and extended prompt caching through the API—giving developers powerful tools to build agents that analyze data, connect to external systems, and maintain context for longer periods of time.
Multi-agentic Software Development is a Distributed Systems Problem (AGI can't save you from it)
Recently, I've been thinking a lot about scaffolding and languages for managing systems of LLMs coordinating with each other — new programming languages might be the ideal solution for this area.