WEBVTT

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My Own AI Labs

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is soft-launching the AI

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Content Engine. It's a

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customer-run workflow for executives

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and developers, from your

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first brief to reviewed

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content and audience feedback.

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Here's how it works.

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Your expertise deserves a

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clear path to an

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audience. The Signal Engine

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brings research, newsletters, video,

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review and follow-up into

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one harness that you

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run. Executives describe the

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result they want. Developers

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connect the tools that

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make it happen. Both

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work with the same

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engine.

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Start with one page

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about your audience, topics

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and goal. Choose one

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or several agents, such

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as Codex and Claude

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Code. They share your

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workspace, guide setup and

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ask for missing details.

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Choose whether you represent

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yourself or an organization,

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and whether another person

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reviews the work.

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Choose trusted sources, prioritize

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useful topics and exclude

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noise. Your rules guide

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which stories you cover.

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Source links, visual checks

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and transcript matching make

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the evidence easier to

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inspect. Failed checks stay

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visible. These controls support

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responsible use of AI;

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human judgment still matters.

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Start with narrated slides

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in your own authorized

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local voice. Your sources

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and review notes stay

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with your private draft.

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Or choose a presenter-only

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video. The presenter in

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this sample is fictional

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and AI generated. A

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mixed layout puts the

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presenter alongside your slides.

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Presenter production is a

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proposed Pro service, with

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setup handled behind the

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scenes.

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Your first draft is

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private: a newsletter and

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video you can review

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together. Connect several publishing

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channels when ready. Approve

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the exact version in

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your browser, then explicitly

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authorize each delivery. Changed

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content needs fresh approval.

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Agents can prepare the

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work; they cannot approve

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it for you.

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Track delivery and audience

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results. Review questions, prepare

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useful replies, and approve

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the wording before sending

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through a supported channel

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or manual handoff. Recorded

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writing-model usage shows reported

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costs and missing prices.

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It does not include

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charges from every service.

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Use the results to

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guide your next edition.

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For developers, the MIT

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source provides a shared

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connector using the Model

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Context Protocol. Named tools

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handle setup, sources, drafts,

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status, analytics and engagement.

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Native plugins, local configuration

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and a Pi extension

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reach the same backend.

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Replace model, source and

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delivery adapters to fit

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your product.

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Workspace permissions, workers, locks

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and job receipts keep

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actions inspectable. Remote access

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uses scoped authorization, expiry

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and revocation through a

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connection that you manage.

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The connector exposes no

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arbitrary shell or approval

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executor. Fourteen host adapters

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are included; account and

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platform verification varies. Cloud

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account support still needs

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verification.

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Free includes connectors, basic

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voice and existing workflows.

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Pro is proposed at

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ninety-nine dollars a month,

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with Executive Briefing and

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Audience Engagement packs, presenter

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production, guided setup, updates,

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a monthly clinic and

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defined support. Customers fund

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agent, model, media and

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tunnel usage. Checkout and

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final commercial terms are

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still being prepared.

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Start by watching Jordan

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take the complete journey

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on this website. Then

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bring your one-page use

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case to a demo.

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We will map the

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path for your audience,

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your agents and your

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review process. Select Book

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a demo at My

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Own AI Labs dot

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com.

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Explore the AI Content

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Engine at my own

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AI labs dot com.

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Free beta access will

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be by invitation. If

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you're interested, request a

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demo.