Leveling Up with Eric Siu

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More AI tools won’t fix a broken workflow. You need a system for handing off work, reviewing important decisions, and checking what actually happened.

I share the AI operating models we use across our companies: a bot fleet with a human in charge, the 1-3-1 decision rule, Trusted Continuation, recruiting, our AEO / SEO content loop, and daily workflows for review, content, and sales calls.

The diagrams show how these workflows are organized. Recruiting goals and content volumes include targets and tests, not guaranteed results. Important decisions still require human approval.

CHAPTERS

00:00 AI operating models across the business

02:17 The 1-3-1 decision rule

03:05 Trusted Continuation

04:24 SingleBrain — implementation

05:17 Recruiting funnel

06:47 AEO / SEO content loop

07:55 Storage and safety rails

08:39 SingleBrain Gateway

10:14 Daily review, content and sales workflows

11:58 Building AI fluency

How to Connect

IG: https://www.instagram.com/ericosiu/

X: https://x.com/ericosiu

👉 Single Grain — AI marketing firm https://www.singlegrain.com

👉 Growth Newsletter for top marketers: https://levelingup.beehiiv.com/subscribe

Why buying AI tools and running training sessions only solve part of the adoption problem. Eric walks through the recruiting workflow and seven screening questions his team uses to find AI-native people, including real-work demonstrations and learning habits. Screening rates discussed are his company’s reported experience, not a population benchmark.

SingleBrain: https://singlebrain.com

SingleBrain Gateway: https://singlebrain.com/gateway

CHAPTERS

00:00 Why recruiting matters

00:29 What AI-native means

02:13 The recruiting workflow

04:18 SingleBrain

05:27 Seven questions

09:02 SingleBrain Gateway

09:32 Screening rates and context

09:56 Tools and judgment

12:01 Closing takeaway

How to Connect

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X: https://x.com/ericosiu

👉 Single Grain - AI marketing firm https://www.singlegrain.com

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Eric walks through business and marketing workflows for content production, recruiting, outreach, speed to lead and design. See how the workflows gather inputs, check work and keep human review in the process.

The 80-hour figure is Eric’s reported estimate; no recurring time period is specified.

00:00 How we cut 80 hours of work

00:28 Workflow outputs and AEO/SEO

07:32 Recruiting workflow

08:01 Single Grain

08:32 Recruiting checks and outreach

12:43 Speed to lead

13:59 Workflows and the content engine

16:14 Careers

16:50 Content engine, design and adoption

How to Connect

IG: / ericosiu

X: / ericosiu

👉 Single Brain - Revenue agents to scale faster using our unified intelligence layer. https://www.singlebrain.com

👉 Single Grain - AI marketing firm https://www.singlegrain.com

👉 Get 25k Words of AI-Powered SEO Content: https://clickflow.com/

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What does a forward-deployed marketer actually do? In this walkthrough, Eric shows how to build marketing workflows, give AI agents clear roles, and improve their output through team feedback.

Topics include workflow ownership, Dots as a chief of staff, Meta Muse, context management, and why human judgment and editorial taste still matter.

Recorded October 7, 2026.

CHAPTERS

00:00 Build. Then Delegate.

00:25 The forward-deployed marketer

01:10 Build a workflow your team can improve

09:52 Give the workflow an accountable owner

13:26 Assign each agent a clear role

15:05 Using Dots as a chief of staff

16:33 Protect your number-one priority

17:02 AI usage × good judgment

18:02 Human taste still matters

19:56 Keep agents focused

20:23 Where Muse fits—and its limits

22:06 Should you switch agents?

23:57 How do you manage context?

24:50 How do you help a team adopt AI?

25:58 Choose one useful next action

How to Connect

IG: / ericosiu

X: / ericosiu

👉 Single Brain - Revenue agents to scale faster using our unified intelligence layer. https://www.singlebrain.com

👉 Single Grain - AI marketing firm https://www.singlegrain.com

👉 Get 25k Words of AI-Powered SEO Content: https://clickflow.com/

👉 Growth Newsletter for top marketers: https://levelingup.beehiiv.com/subscribe

I show the AI skill workflow I use to run my YouTube channel: titles and thumbnails, long-form editing, timestamped feedback, and preparing a video for upload.

The 50x comparison is my reported experience with average views per video. The examples in this recording do not establish a matched before/after baseline or prove that the skill alone caused the change. My focus is on qualified leads, and human taste and review still matter.

Get access to the skills: https://skillsdojo.com/

AI marketing skills: https://www.singlegrain.com/skills

Work with Single Grain: https://www.singlegrain.com/

Full-time creator and editing roles discussed in this episode: https://www.singlegrain.com/careers

This walkthrough includes a recorded example from a Cody Schneider webinar edit, plus the marketer and founder videos used to demonstrate the workflow.

CHAPTERS

00:00 Reported results and the focus on leads

01:54 Thumbnails first

02:58 Directing the packaging

03:31 From packaging to the full edit and human taste

03:55 Reviewing a real edit

04:45 The timestamped review workspace

05:07 Join the Single Grain team

06:01 Review, repurpose and iterate

08:18 Specific thumbnail feedback

09:04 The improved result

09:45 A repeatable handoff

10:15 Work with Single Grain

10:38 Getting the edit ready to upload

11:11 YouTube Studio and upload friction

12:41 Operator, creator and team workflow

14:07 The business payoff and skill access

How to Connect

IG: / ericosiu

X: / ericosiu

👉 Single Brain - Revenue agents to scale faster using our unified intelligence layer. https://www.singlebrain.com

👉 Single Grain - AI marketing firm https://www.singlegrain.com

👉 Get 25k Words of AI-Powered SEO Content: https://clickflow.com/

👉 Growth Newsletter for top marketers: https://levelingup.beehiiv.com/subscribe

AI agents are changing how marketers work. I walk through the content loops, team bots, repurposing workflows, and paid-media preparation I use across Grokbot, OpenAI Dots, Codex, and Meta Muse—and where marketing judgment still matters.

Get the skills mentioned: https://skillsdojo.com/

Join our team: https://www.singlegrain.com/careers

Chapters

00:00 Results, then the workflow

02:19 Find demand and build the content loop

08:57 Put agents inside the team

10:03 Join Single Grain

16:02 Repurpose with taste

19:54 Work with Single Grain

20:18 Work across tools with OpenAI Dots

21:44 Apply marketing judgment to AI output

24:32 Prepare paid media with Meta Muse

27:13 Marketing fundamentals are the advantage

How to Connect

IG: https://www.instagram.com/ericosiu/

X: https://x.com/ericosiu

👉 Single Brain - Revenue agents to scale faster using our unified intelligence layer. https://www.singlebrain.com

👉 Single Grain - AI marketing firm https://www.singlegrain.com

👉 Get 25k Words of AI-Powered SEO Content: https://clickflow.com/

👉 Growth Newsletter for top marketers: https://levelingup.beehiiv.com/subscribe

👉 Single Brain - Revenue agents to scale faster using our unified intelligence layer.

https://www.singlebrain.com

I use Grok Bot and Jev to find content gaps, review drafts, and measure our AEO and SEO work. In this walkthrough, I show the routines, real WordPress drafts, citation checks, human review, and a mistaken hold I had to correct.

I also show how Muse and Codex help turn ideas into a landing-page draft. This rollout is early. I explain the indexation issue and what I am measuring before scaling.

00:00 Show the system

00:15 Inputs and routines

01:40 Decide what to draft

05:09 Human review

05:59 Real draft outputs

07:41 Search fundamentals

08:17 Measure and correct

11:49 Repurpose with judgment

13:11 Muse to Codex handoff

16:07 Build, measure, iterate

👉 Single Grain - AI marketing firm

https://www.singlegrain.com

👉 Get 25k Words of AI-Powered SEO Content:

https://clickflow.com/

👉 Growth Newsletter for top marketers:

https://levelingup.beehiiv.com/subscribe

👉 Single Brain - Revenue agents to scale faster using our unified intelligence layer. https://www.singlebrain.com

I was using Jev after the expensive model had already done the work. In this video, I show the mistake, the filtering workflow I changed, and how I define criteria before trusting the output.

We walk through real content examples, Grill Me versus Grill Me Overview, pre- and post-work checks, and why a human still needs to inspect the evidence. In one batch, Jev passed 189 of 517 chunks to the costly model. That is a filtering result, not a measured percentage of money saved.

Clarifications: The 198/225 and 189/517 figures come from different datasets, not a controlled before-and-after test. Jev’s Noul returns the probability of yes; Choice selects an option; Score rates against ordered criteria. Score is not a confidence score.

Chapters:

00:00 The biggest Jev mistake

00:14 Filter before the expensive model

01:07 Define the right criteria

02:23 Grill Me: questions one at a time

02:43 Work with Single Grain

03:05 Grill Me Overview: batch the questions

04:36 Add pre- and post-work gates

05:15 The real article and evaluation path

06:08 Keep a human in the loop

06:52 Teach your team the workflow

Footage and sources: Eric Siu’s original camera and screen recording. Single Grain website footage is retained from the original edit. Grill Me is credited in the narration to Matt Pocock; the article and workflow excerpts appear within Eric’s recorded screen demonstration.

How to Connect

IG: https://www.instagram.com/ericosiu/

X: https://x.com/ericosiu

👉 Single Grain - AI marketing firm https://www.singlegrain.com

👉 Get 25k Words of AI-Powered SEO Content: https://clickflow.com/

👉 Growth Newsletter for top marketers: https://levelingup.beehiiv.com/subscribe

👉 Connect your tools with Single Brain Gateway: https://www.singlebrain.com/gateway

👉 Single Brain - Revenue agents to scale faster using our unified intelligence layer. https://www.singlebrain.com

I was using Jev after the expensive model had already done the work. In this video, I show the mistake, the filtering workflow I changed, and how I define criteria before trusting the output.

We walk through real content examples, Grill Me versus Grill Me Overview, pre- and post-work checks, and why a human still needs to inspect the evidence. In one batch, Jev passed 189 of 517 chunks to the costly model. That is a filtering result, not a measured percentage of money saved.

Clarifications: The 198/225 and 189/517 figures come from different datasets, not a controlled before-and-after test. Jev’s Noul returns the probability of yes; Choice selects an option; Score rates against ordered criteria. Score is not a confidence score.

Chapters:

00:00 The biggest Jev mistake

00:53 Filter before the expensive model

01:33 Define the right criteria

02:49 Grill Me: questions one at a time

03:09 Work with Single Grain

03:31 Grill Me Overview: batch the questions

05:03 Add pre- and post-work gates

05:41 The real article and evaluation path

06:35 Keep a human in the loop

07:19 Teach your team the workflow

Opening example footage: Simon Scrapes, “Jev for Claude is INSANE (Every Jev Concept Explained),” September 23, 2026: https://www.youtube.com/watch?v=D-Z5HnLW_ho

How to Connect

IG: https://www.instagram.com/ericosiu/

X: https://x.com/ericosiu

👉 Single Grain - AI marketing firm https://www.singlegrain.com

👉 Get 25k Words of AI-Powered SEO Content: https://clickflow.com/

👉 Growth Newsletter for top marketers: https://levelingup.beehiiv.com/subscribe

👉 Connect your tools with Single Brain Gateway: https://www.singlebrain.com/gateway