The argument in one line.
Building AI agents that can automate your entire content and marketing operation requires stacking reusable skills—grounded workflows that combine external APIs, your personal knowledge base, and design tools into a single interface where both you and the agent can work together.
Read if. Skip if.
- A content creator or marketer with an existing audience who spends significant time on repetitive tasks like research, scheduling, and asset creation.
- Someone already comfortable with AI tools like Claude or ChatGPT who wants to systematize their workflow into reusable skills rather than starting from scratch each time.
- A creator scaling from thousands to millions of followers who needs to automate marketing operations without hiring a full team or learning complex coding.
- You're looking for a beginner's introduction to AI or marketing fundamentals — this assumes you already know your content strategy and just need the execution layer.
- You work primarily in non-technical platforms like Instagram-native tools or TikTok Studio — this is built around desktop apps and APIs that may not integrate with your workflow.
- You've already built custom automation and tool stacks — this is a walkthrough of one specific setup, not a comparative analysis of alternatives.
The full version, fast.
Codex becomes a true marketing operating system once you wrap it in skills � repeatable instruction files an AI agent can execute � and plugins, which bundle related skills together. You invoke plugins with @ and skills with /, and you compose them: ground a script in YouTube transcripts with the YouTube Researcher skill, then ground ideation in your own bookmarks via the Readwise CLI, then chain Excalidraw or Paper for diagrams, Remotion or Hyperframes for motion graphics, and a FAL-powered gen-media mini-app the agent and you both operate on. Build a workflow manually first, ask the agent to save it as a skill, then promote it to a scheduled automation. The leverage is stacking skills and running parallel chats with sub-agents.
Chat with this breakdown.
Modern Creator members can chat with any breakdown — ask for the hook, quote a framework, find the exact transcript moment. Unlocks at T2: refer 3 friends + add your own API key.
Create a free account →Where the time goes.

01 · Intro: What Codex is and how skills work
Overview of Codex as a super-app, plugin vs skill distinction, slash vs at-sign syntax.

02 · Skill 1: YouTube Researcher (Grounding)
Pull any creator transcript via SupaData to generate content in their voice. Also used to learn topics in Karpathy style.

03 · Skill 2: Readwise CLI (Second Brain)
Bookmarked tweets sync to Readwise. Codex generates 30 content ideas and automates the output at 8AM daily.

04 · Skill 3: Excalidraw Diagrams
Auto-generate visual outlines using parallel sub-agents. Edit directly on Excalidraw canvas.

05 · Skill 4: Paper
HTML-based MCP tool for animated explainers, landing pages, lead magnets, and thumbnails with live MCP steering.

06 · Skill 5: Remotion and Hyperframes
Code-driven motion graphics for YouTube overlays. Time-coded edits, reusable compositions, 4-scene variants.

07 · Skill 6: Gen Media (FAL API mini-app)
App wrapping every FAL model. Both human and agent drive it. Agent generates; human edits the final 10 percent.

08 · Skill 7: Email Manager / Brand Deal Researcher
Gmail plus Calendar plus YouTube Researcher combined. Scores brand deals, builds priority table, suggests meeting times.

09 · Bonus: Buffer Publisher and Chorus tease
Codex scans its memory and pushes 5 ideas to Buffer. Soft pitch for Chorus cloud agent.
Lines worth screenshotting.
- Grounding an AI agent means pointing it at a specific high-quality reference — without grounding, the model generates scripts based on OpenAI's taste, not yours.
- Skills are instruction files for an AI agent; plugins are bundles of skills — the slash command activates a specific skill while the at-sign activates the entire plugin.
- A YouTube Researcher skill that fetches real examples before generating content produces output calibrated to what actually works, not what a generic model thinks works.
- Readwise as a second-brain grounding layer lets the agent draw from your own highlights and notes instead of the open internet, which changes the quality of ideation fundamentally.
- The difference between a creator at 1.5 million followers and one at 10 million is almost never the quality of the AI — it is how the AI is grounded and what it is pointed at.
- Buffer as a publishing skill inside Codex closes the loop from idea to scheduled post without leaving the agent environment.
- A FAL API generative media skill inside a super app turns the agent from a text tool into a full production pipeline — writing, generating, and publishing from one conversation.
Build a team, not a chat window.
Every skill is a job description for a specialist, and specialists compound when you stack them.
- Pick one repeatable task and run it in Claude Code until you love the output.
- Tell the agent to turn the output into a skill file: one .md per workflow.
- Set an 8AM automation for your highest-value daily task.
- Once you have 3 skills, run them together using sub-agents in a single chat.
- For media generation, build a mini-app both you and the agent drive. Never let the AI be the last hand on the output.
Terms worth knowing.
- Codex
- OpenAI's all-in-one desktop app that combines chat, agent workflows, and coding into a single interface. The agent can read, edit, and create files on your computer and produce documents, spreadsheets, slide decks, or web apps in a live preview pane.
- Claude Code
- Anthropic's command-line coding agent that runs locally and can execute, edit, and create files on your machine. Skills built for it are portable to other agent environments like Codex.
- Skill
- A reusable instruction file that teaches an AI agent how to perform a specific workflow, including the steps, references, and tools it should use. Invoked in Codex with a slash command.
- Plugin
- A bundle of related skills and capabilities an agent can call, often wrapping an external service like Gmail, Calendar, or Vercel. Invoked in Codex with an @-mention.
- Automation
- A scheduled or triggered run of a prompt or skill that fires on a recurring basis, such as every morning at 8 AM. Used to turn a manual workflow into a hands-off routine.
- Computer use
- An agent capability that lets an AI model directly control the desktop, clicking, typing, and navigating apps on the user's behalf. Browser use is the same idea constrained to a web browser.
- Grounding
- The practice of connecting an AI model to a specific external reference, such as a transcript or document, so its output is shaped by that source rather than only its training data.
- Reinforcement learning
- A training method where a model's outputs are repeatedly rated as good or bad, nudging it toward responses the trainers prefer. It shapes a model's default style and taste.
- API
- A programmatic interface that lets one piece of software request data or actions from another, usually authenticated with a key. Skills use APIs to pull transcripts, generate media, or post to social platforms.
- Supadata
- A third-party service that exposes an API for pulling transcripts and metadata from YouTube, TikTok, Instagram, and X videos. Skills like a YouTube researcher use it to fetch source material on demand.
- Readwise
- A read-it-later and highlight-syncing service that aggregates saved articles, tweets, and book highlights into one searchable library. It functions as a personal second brain that agents can query.
- CLI
- A command-line interface — a text-based way to control a program by typing commands. A CLI tool lets an AI agent script and automate that software without a graphical UI.
- Second brain
- A personal database of saved notes, bookmarks, and highlights used to offload memory and feed future thinking. Connecting it to an AI agent lets the agent draw on your own curated material.
- Excalidraw
- A free web-based whiteboard tool for sketching hand-drawn-style diagrams and flowcharts. Its file format is text-based, which makes it easy for AI agents to generate diagrams programmatically.
- Paper
- An HTML-based design canvas built for AI agents to create and edit, comparable to Figma but optimized for agent control. It supports animated diagrams and live updates while the agent works.
- MCP
- Model Context Protocol — an open standard that lets AI agents connect to external tools and services through a consistent interface. Tools like Paper expose an MCP endpoint so agents can call them directly.
- Sub-agents
- Smaller AI agents that a main agent spawns to work on separate parts of a task in parallel. They speed up multi-step workflows by running independent steps simultaneously.
- Steering
- Injecting a new instruction into a running agent to redirect its work mid-task without stopping it. Useful for correcting formatting or scope as soon as the agent goes off course.
- Remotion
- A framework for making videos with React code, where compositions are defined in code and rendered to MP4. It is well-suited to AI agents because edits are made by changing code rather than dragging clips on a timeline.
- Hyperframes
- A motion-graphics plugin for Codex aimed at richer, more physics-driven animations than Remotion. Used for product demos and animated overlays.
Things they pointed at.
Lines you could clip.
“95% of the tasks that I do on my computer for content and marketing is inside Codex.”
“Do a useful thing, and once you create an output that you like, say please turn this into a skill. Once that happens, say I want you to do this every day at x time.”
“What separates an app that you create and a mini app is that the agent can also use it.”
“I wanted to create a bunch of options, and then take it the final 10% because that is where all the value is.”
Word for word.
The bait, then the rug-pull.
A quiet confession delivered cold: ninety-five percent of his entire computer workflow runs through one app. No disclaimer, no soft open, no intro card. Riley Brown drops the number at second eight and dares you to doubt it. The next fifty minutes are the proof.
Named ideas worth stealing.
The Grounding Stack
Before generating content, point the AI at a high-quality reference: a creator transcript, your bookmarks, your past videos. Output quality jumps because the model is calibrated to a specific taste.
Skill-First Automation Loop
- Run the task manually until you love the output
- Tell the agent: turn this into a skill
- Iterate until repeatable
- Then automate it on a schedule
Never automate before validating the output. Build the skill first, then the automation.
Mini-App Architecture
Build apps both the human and the AI agent can drive. Agent generates into a shared grid; human does final selection and polish.
Skill Stacking
Combine multiple skills using sub-agents in one chat. YouTube Researcher feeds Excalidraw; Readwise feeds hook writing. Skills compound.
How they asked for the click.
“All of these skills can be found on chorus.com/skills. You can use them in Codex or Claude Code.”
Soft and brief, mentioned twice, no hard sell. Also teases a free Chorus cloud trial.







































































