A 30-minute video is too long for one conversation. This guide walks the 8-step Skill that locks the narration and one look, then gives each 3-minute segment to a fresh sub-agent, five at a time, and polishes the cut in an empty-context session.
The folder structure behind my AI agent team, the Herdr setup where Grok Build, Claude Code and Kimi Code work side by side, and the two live tasks from the video: an article published by voice and a three-model front-end test.
Eight folders of plain Markdown, a CLAUDE.md index in each, and seven prompts that make your agent interview you. Every prompt, template and command from the video, in order.
Agents that do the work on their own: skills, subagents, loops, multi-agent setups, deployment
The folder structure behind my AI agent team, the Herdr setup where Grok Build, Claude Code and Kimi Code work side by side, and the two live tasks from the video: an article published by voice and a three-model front-end test.
The same request gives a different answer every run because the agent fills every gap with the average of its training data. Three Markdown standards fix that: a meta standard, an eight-part prompt standard and a Skill standard. Free repo, one-prompt install.
Gloves on, tape measure in hand — nobody types a query. Three voice surfaces for ai automation tools (terminal, Telegram, Discord), 10 TTS and 6 STT providers compared on cost and latency, plus a setup that costs nothing.
One number hides more than it shows. This Claude Code Skill scores US equities across 10 dimensions, from earnings surprise to peer comparison, with confidence scoring and 5 safety valves that flag thin data. A coding tutorial, not financial advice.
A Skill is an operating manual, not a plugin. The five-layer architecture behind workflow automation that survives context compression, session crashes, and handoffs: SKILL.md as the single entry point, deterministic scripts, run state for crash recovery, and a resource layer.
Code volume grew 180%. Shipped output grew 30%. That gap is the price of never defining what done means. After pulling apart 136 open-source loops, the failure was identical every time, no terminal condition, and the fix turns out to be a business question rather than a technical one.
Buy the model and you have bought the smallest part. Tool injection, permission enforcement, context compression and validation loops are where the measurable gains sit — and where workflow automation software vendors say the least.
One controller AI orchestrating parallel coding agents across machines, using nothing but SSH and tmux. Compares three workflow automation patterns — subagents, MCP, and cross-machine orchestration — then deploys the third, which is where most developers hit a wall.
Most standard operating procedure template downloads assume a person will read the result. Here is what changes when the reader is an AI agent.
The best AI agent for small business is the one you can walk away from. Here is the switch test: one folder, three tools, four columns to fill in.
Most AI workflow automation advice says add another agent. Anthropic's own numbers say that costs 15x the tokens. Here is the folder layout instead.
Most AI persona tools invent a customer for you. This does the reverse: your trade's names, formats, forbidden lines, escalation path — three you can copy.
When I figure out how to get something real done with AI, you get the write-up — every step, including the parts that didn't work.