Use MyClaw as a no code AI automation platform for developer work: describe the routine, connect GitHub and team tools, and let an always-on OpenClaw agent review code, write tests, debug builds, and route updates.
Choose the workflow to automate
Step 1
Lite
2 CPU
Pro
4 CPU
Max
8 CPU
Start with automated code review, test generation, release notes, CI debugging, or ticket-to-PR routines.
Engineering teams adding automated code review
Founders who want no code automation tools for developer workflows
Ops teams building low code workflow automation across GitHub, Linear, and Slack
Teams that need a no code AI automation platform with real repo access
01
Ask the agent to scan pull requests, compare changed files against project context, flag risky logic, check missing tests, and summarize what needs human attention. Automated code review becomes a first pass that reduces queue time without replacing final engineering judgment.
02
Many low code automation builders can move a ticket or send a notification, but they cannot inspect a repo, run commands, or prepare a patch. MyClaw gives OpenClaw a hosted workspace where low code workflow automation can trigger real development work and return reviewable results.
03
Create routines in plain language for tests, release notes, build debugging, backlog cleanup, dependency checks, and Slack summaries. Your no code automation tools can start the workflow, while the agent handles the code-aware steps that need terminal, browser, and GitHub context.
Combine repo-aware coding skills, GitHub workflows, terminal control, browser access, memory, and review helpers inside one persistent no code AI automation platform.
Delegate implementation, test writing, refactoring, and pull request preparation to Codex, Claude Code, or other coding agents.
Open Coding Agent →Turn GitHub issues into plans, code changes, review notes, and pull requests that can be triggered from low code workflows.
Open GitHub Issues Agent →Add a second model review for automated code review findings, sensitive changes, architecture tradeoffs, or release decisions.
Open Oracle →Reuse prior coding sessions, project decisions, fixes, and preferred review rules when the agent handles similar work later.
Open Session Logs →Keep long-running tests, builds, monitors, and background code automation processes alive in the hosted workspace.
Open tmux Control →A few X posts we collected from users building with coding agents, repo automation, and always-on developer workflows.
Delegated coding agent management overnight — better context awareness than running agents solo.
Agent debugged a failed deployment, reviewed logs, fixed configs, and redeployed — all via voice.
Rebuilt an entire site via Telegram: Notion to Astro migration with 18 posts — all through chat.
Cleaned Linear issues, wrote emails, opened PRs, and prospected signups — all from one chat.
Manages calendar, contributes to Obsidian notes, commits to GitHub, and sends reminders.
Takes notes on app improvements, builds lists, writes reports, and kicks off Codex agents.
Turned an idea into a project pulling 4 million posts across 100 top X accounts.
Configured an OpenClaw instance hooked to a Telegram group for on-the-go development help.
Built a complete UI entirely from WhatsApp messages — sends back output screenshots for review.
Built a GA4 analytics skill in ~20 minutes and published it to ClawHub.
Delegated coding agent management overnight — better context awareness than running agents solo.
Agent debugged a failed deployment, reviewed logs, fixed configs, and redeployed — all via voice.
Rebuilt an entire site via Telegram: Notion to Astro migration with 18 posts — all through chat.
Cleaned Linear issues, wrote emails, opened PRs, and prospected signups — all from one chat.
Manages calendar, contributes to Obsidian notes, commits to GitHub, and sends reminders.
Takes notes on app improvements, builds lists, writes reports, and kicks off Codex agents.
Turned an idea into a project pulling 4 million posts across 100 top X accounts.
Configured an OpenClaw instance hooked to a Telegram group for on-the-go development help.
Built a complete UI entirely from WhatsApp messages — sends back output screenshots for review.
Built a GA4 analytics skill in ~20 minutes and published it to ClawHub.
Start with automated code review, test generation, release notes, CI debugging, or ticket-to-PR routines.
Link GitHub, Linear, Slack, browser sessions, MCP tools, and the destinations where results should be routed.
Let the agent execute the routine in a hosted workspace and keep approvals around code, comments, and production changes.
Recommended Plan
Start with automated code review, then add low code workflow automation for tests, CI recovery, release notes, and backlog cleanup.
Built for always-on AI agent workflows with human review where it matters.