#automation

Meta Muse needs you to personally confirm every public action, like posting to Instagram or replying to comments, and there's no setting to loosen that. The easier approach is to have it write a batch of posts and stop before publishing, then approve them all at once.

Intermediate tutorial: Put a team of AI agents on shifts, one job each: morning briefings, group chat triage, X growth, content repurposing, competitor watch, lead hunting, subscription audits, a second brain, multi-agent coordination, and small tool building. Start with the morning briefer, add two roles a week after that, and keep every message, payment and post waiting for your OK. Includes 10 role briefs you can copy and paste.

Six bots with clear roles research and trade on a fixed schedule. Every decision is logged. Real-money trading expands one step at a time, and each trade waits for a human approval.

Advanced tutorial: Borrow Posteady's five-module split to set up a local content workspace with Claude Code or Codex. Collect material daily, score topics, write one draft for many platforms, schedule posts, and review weekly to feed the next topic picks. The publish button always stays with you. Includes 5 prompts you can copy and paste.

Six bots with clear responsibilities run on a fixed rhythm: data drives ad and product changes, every deliverable comes with evidence, and spending and releases wait for human approval.

A set of specialized bots, each handling one area: automatically summarizing email, news, and traffic every day, watching competitor activity, drafting content before anything is published, and coordinated by a manager bot.

An advanced developer tutorial: how browser agents read pages, click buttons and extract data; when to use an agent approach versus precise control; and the safety guardrails to set up before going live.

Tutorial: Add a Gmail Connector to Meta's Muse, set its permissions to read-only, then use one sentence to schedule daily or weekly tasks that have it automatically read new emails and send a summary report sorting them into three groups: needs a reply, bills, and can be ignored. Steps and screenshots come from Meta's official Help Center.

Beginner tutorial: you can write a Skill without coding. Step 1 is finding your repetitive work, step 2 is running it through manually first, step 3 is explaining the requirements to AI so it writes them into SKILL.md, step 4 is running and refining it, and step 5 is sharing it with others to use.

Intermediate tutorial: Don't have the Agent run scheduled tasks by hand every day. Have it write the task as one Python script, hand it to the system's built-in cron or Task Scheduler, and run it at 0 Tokens per run. When the script finishes, it sends you a message saying whether it succeeded or failed.

Zoho International has a CLI, so an Agent can easily take over sending and receiving mail. Zoho China has no CLI and only a limited API. The workaround: CC the mail to Gmail, have the Agent read it with gws and write a draft, then you review it and send it to the client yourself.

AI is advancing quickly in CAD work: reading drawings, producing drawings, revising drawings and annotation have largely been solved. We expect repetitive drafting roles to be replaced first. What remains are people who understand the industry, know how to use AI, and can communicate with clients.

Automation agents most need stable execution and deterministic output, and OpenClaw falls short on both: the same task gives different results, failures go unreported, and success cannot be guaranteed. Our fix is to add inspection logs and failure notifications, script the processing steps, templatize prompts, and make outputs JSON with strict validation.

One command runs the full process and produces a daily research report and dashboard that can be cross-checked, viewed locally or published as a static site.

A general-purpose skill for Codex and local creative workflows that turns a product brief, reviewed narration, digital human or real-person on-camera speech, real product footage, and motion graphics into a deliverable video with review gates. It is not tied to any brand or script; product facts, copy, media, and vendor parameters live in the project directory. Multi-file repository, installed via git clone. Use case: Combines a product brief, narration, and digital human on-camera speech into a deliverable product video with review gates.