10-lesson course · about 18 hours

Hand recurring content prep to proactive agents and stay the author

For Creators, educators, influencers and personal-brand teams responsible for useful content, audience trust and a consistent production practice

Everything for Creators

Build and supervise agents in OpenAI Dots or Claude Duet that keep your idea queue, research, scripts and edit prep moving between reviews. Nothing is released until you approve it.

Try lesson 1 freeSee what you’ll learn

What you’ll be able to do

By the end, you can…

Define an agent role you can superviseTurn a recurring prompt into a standing goal for a named role such as Editorial Desk. Give it a scope, approved sources and connections, an agreed report, a human owner and a rule for stopping, pausing or retiring it. Then decide whether it should be a single run or a continuing brief.
Keep an idea queue sorted by what viewers needRun a scheduled intake agent that groups audience questions by viewer need. It merges duplicates and attaches your earlier answer, and it flags stale ideas. It never ranks by provocative wording or predicted reach, and it collects no personal data the answer doesn't need.
Get research packets that hold up when a source changesDirect a research agent to build claim-to-source packets with links, dates and the exact statement each source supports. When a newer source contradicts an older one, the agent stops the scripts that depend on it and brings the conflict to you.
Get script drafts that still sound like youSupervise a scripting agent that drafts a small batch from your voice guide and your accepted packets. Your corrections go into its standing instructions, so accepted passages stay as they are. Conflicting notes come back to you instead of being averaged.
Keep edits, captions and adaptations tied to the scriptCoordinate CapCut edits, SRT captions and permitted Higgsfield assets through a production agent. It keeps a versioned edit queue, marks the export steps you do by hand, and checks that no adaptation drops a qualifier or changes a fact.
Approve a release queue and read the results honestlyPut together an approval packet with scripts, sources, exports, disclosures and open permissions. Mark each piece ready, returned or held, and record who may publish it. Then read a small performance report, keeping results apart from hypotheses, and plan the next run as a small test.

How it works

A tutor that meets you where you are

  1. Lessons that adapt to your levelEach lesson starts from what you already know, which is briefing a single AI task well, and adjusts its pace and depth as you go. If something is already familiar you can move on. If it's new, you can slow down.
  2. An AI tutor you can ask anythingType or speak your questions while you work. The tutor can help you test a standing goal, look at a research packet, or think through whether a job should go to an agent or stay with you.
  3. Practice on a running case and your own channelOne case runs through every lesson: a parent asks whether their children, six and eight, can manage a cliff walk. A 5:30 last-shuttle time sits in every version of the answer, until a newer park notice contradicts it. You apply each step to your own series alongside the case.
  4. Quizzes and flashcards for each lessonShort checks tied to each lesson help you remember the rules that matter, such as why a citation next to a claim isn't proof that the source supports it.
  5. Progress tracking and a certificateSee which lessons and outputs you've finished. When you complete the course, you get a certificate of completion.

Curriculum

The curriculum

The course has ten lessons in five modules. They follow the order of the work itself: intake, research, scripts, production, then release and review. Each module adds one agent to a workflow that ends with a release queue you approve piece by piece.

Module 1Build a useful idea queue.2 lessons

  1. 1Sort incoming topic ideas
    • Run the last-twenty-posts audit and sort your preparation work into agent jobs and jobs that stay with you
    • Write a standing goal for an intake role, with role name, scope, approved sources and connections, agreed report, human owner and stop, pause and retire rules
    • Choose between Dots and Claude Duet, and between a single run and a continuing brief, and give reasons for both choices
    • Build and test an intake agent that groups approved question exports by viewer need into a question-clusters report
  2. 2Handle duplicates and stale ideas
    • Configure the intake agent to merge duplicate questions across platforms and attach your earlier answer for recheck
    • Define what 'stale' means for your series and have the agent flag stale ideas without deleting them
    • Produce a trend-relevance report and an audience brief (CSV) that hold no unnecessary personal data or information about minors
    • Test the pause and retire rules on a live brief

Module 2Keep the evidence behind each piece current.2 lessons

  1. 3Prepare a bounded research packet
    • Write a bounded research brief with approved topics, approved sources, a stop rule and an agreed packet format
    • Build a claim-to-source packet that keeps sourced facts, unknowns and your own observations apart
    • Test each citation to see whether the source actually supports the claim
    • Explain why a generated answer is not verification
  2. 4Recheck changed evidence
    • Set up a scheduled recheck of approved sources, with clear triggers
    • Build a dependency list that shows which drafts and edit items use each claim
    • Test that the agent stops and reports a contradiction instead of choosing a winner
    • Record your resolution in the packet, with the old evidence kept

Module 3Prepare scripts that belong in the same series.2 lessons

  1. 5Draft the next script batch
    • Write a scripting brief that limits inputs to an approved batch, your voice guide and accepted packets
    • Choose honest hooks from a set of options and reject any that promise more than the piece delivers
    • Check that every factual line in a draft links to a packet claim and that no personal experience was invented
    • Explain which parts of each script remain yours
  2. 6Apply review without flattening the voice
    • Turn review notes into standing instructions instead of one-off edits
    • Lock accepted passages so later passes don't rewrite them
    • Test that the agent sends conflicting notes back to you instead of averaging them
    • Run a read-aloud check and accept, return or hold each script

Module 4Keep edits and adaptations tied to the script.2 lessons

  1. 7Prepare the edit requests
    • Write a production coordinator brief that names its human owner and marks which steps are manual in CapCut and Higgsfield
    • Build an edit request that shows filmed versus illustrative material, exact on-screen text and platform formats
    • Produce a storyboard sequence and SRT caption drafts from an accepted script
    • Test each platform adaptation for dropped qualifiers or changed facts
  2. 8Track returned edits and fixes
    • Build a versioned edit queue with status, version and owner for every item
    • Register returned edits with reasons and carry each fix to every affected version
    • Check exported files so that captions, on-screen text and spoken lines agree with the script and packet
    • Explain why a corrected script does not correct a video

Module 5Prepare a release queue you can approve.2 lessons

  1. 9Assemble the approval packet
    • Connect the four agents into a recurring workflow in which each report is the next agent's input
    • Build an approval packet and a disclosure checklist for each piece
    • Mark each piece ready, returned or held, and record who may publish it
    • Create a publishing queue (ICS) that reminds people to publish and never publishes automatically
  2. 10Use feedback to plan the next run
    • Separate results from hypotheses in a supplied performance report
    • Explain why a single metric can't show why a piece performed
    • Plan the next run as a small test that changes one thing
    • Decide for each agent whether to continue, revise, pause or retire it

Who it’s for

Made for you if…

Made for: Creators, educators, influencers and personal-brand teams responsible for useful content, audience trust and a consistent production practice

Solo creators with a recurring series on several platforms

Audience questions are arriving faster than you can answer them by hand. You want intake, research packets and first drafts handled by agents, with every role written down as yours.

Educators who publish explainers and answer learner questions

Your audience acts on what you say. You need every factual line traced to a dated source, and work that pauses when the evidence changes.

Small personal-brand teams with a part-time editor or manager

You need to know which person each agent answers to. The editor owns manual edits and exports, the manager handles brand questions, and the creator owns the facts, the voice and the release.

Questions

Good to know

What should I be able to do before I start?

You should be able to brief a single AI task with a clear output, constraints and format, and check the result line by line. You should also be able to write a script from sourced facts kept separate from your own marked observations. You'll need a channel or series with real audience questions arriving on two or more platforms, a short voice guide or a few past scripts, and working familiarity with CapCut.

Do I need OpenAI Dots or Claude Duet?

Yes, you need access to one of them, plus permission to connect the apps you plan to use. The course teaches the two as equals, and you choose which one fits your work.

Will the agents publish posts or reply to my audience?

No. The course doesn't cover auto-publishing or agents that send audience replies for you. The publishing queue you build reminds people to publish. It never publishes on its own, and you record who may publish each piece.

Will any agent use my face or voice?

No. The course rules out any synthesis or alteration of your face, voice or likeness, including digital twins. Spoken lines stay with you.

Does the course cover sponsorship and AI disclosure?

Yes, as a working disclosure checklist that draws on FTC rules and YouTube's GenAI disclosure policy. It isn't legal advice on endorsements or contracts, and it doesn't cover negotiating or pricing brand deals.

Will this help me grow my reach?

The course doesn't teach growth tactics, algorithm optimization or reach forecasting. You'll learn to read a small performance report without claiming a cause from a single metric, and to plan your next run as a small test.

Do I need to write code?

No. You set up and supervise agents in Dots or Claude Duet. You don't write code or build custom agent software.

How long does it take?

Plan on about 18 hours across ten self-paced lessons.

Influencer AI Intensive: Proactive Agents for Content Preparation

$397

One payment · lifetime access

  • 10 self-paced lessons in five modules, about 18 hours in total
  • Hands-on agent setup in OpenAI Dots or Claude Duet, taught as equals
  • Outputs you build: question clusters, an audience brief (CSV), research packets, voice-matched scripts, a storyboard sequence, SRT caption drafts, a disclosure checklist and an ICS publishing queue
  • A running case about one fact that changes, and how to stop it before it spreads
  • An AI tutor you can ask by typing or out loud, with quizzes and flashcards for each lesson
  • Progress tracking and a certificate of completion

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Refunds: Full refund if you ask before you open your first lesson. Once you’ve started, purchases aren’t refundable, except where the law gives you that right.

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