Leveling Up with Eric Siu

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

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

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

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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

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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

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

I compare OpenAI Dots, Grok Bot, and Muse for real business work. We look at Slack policies and handoffs, content workflows, shared agents, and marketing and sales use cases.

Grok Bot is my current personal choice for the way I work. The best fit depends on your task, budget, and team. Keep a human in the loop and inspect the results.

Chapters:

00:00 Which agent wins for work?

00:15 How the three agents compare

01:41 Dots: business tasks

03:02 Dots: Slack policy and handoffs

06:02 Where Dots fits

07:04 Muse: content workflows

07:16 A message from Single Grain

07:46 Muse: proof and human review

11:54 Grok Bot: shared agents

13:00 A message from Single Brain

13:29 Grok Bot: real business use cases

16:07 My current choice and best use cases

Opening Dots footage: OpenAI, DevDay 2026. https://openai.com/index/devday-2026-recap/

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

OpenAI's DevDay 2026 opens new ways for marketers to get discovered and build useful workflows. I walk through Dots, plugin discovery, Sign in with ChatGPT, the enterprise Marketplace, Decisions API, and Agents API, then explain what these changes could mean for AEO, SEO and paid media.

The opportunity: turn a workflow people need into something they can find and use. Access depends on the product, plan, partner and market. The enterprise Marketplace is a procurement channel; plugin discovery and paid ads are separate routes. Examples and forecasts are my analysis, not a promise of rankings or revenue.

Chapters:

00:00 Why marketers should care

00:34 Plugin discovery

02:26 Sign in with ChatGPT

02:59 Single Grain

03:28 A LinkedIn advertising workflow

03:46 The enterprise Marketplace

04:11 A broader discoverability playbook

04:58 Decisions API

05:17 Agents API and computer use

06:32 Package a useful workflow

07:18 AEO, SEO and paid media

Source and on-screen launch material: OpenAI's official DevDay 2026 recap

https://openai.com/index/devday-2026-recap/

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

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

I walk through nine ways I use Jev for marketing and business: SEO and AEO triage, draft quality checks, Instagram follower sorting, organic posts into ads, customer-call mining, recruiting, genuine-news outreach, LinkedIn engagers, and checks before an agent sends as me.

Plus the mistake to avoid: waiting until the expensive work is finished to classify what was worth doing. These are my workflows and reported early batches, not guaranteed results.

Chapters:

00:00 Jevmaxxing: the quality bar

00:31 1. SEO and AEO opportunity triage

02:39 2. Draft quality gates

04:34 Single Brain Gateway

05:01 3. Find useful Instagram connections

07:30 4. Turn organic posts into ads

09:44 Single Grain

10:14 The mistake: classify before costly work

11:00 5. Mine customer calls and measure hit rate

12:00 6–7. Recruiting and genuine-news outreach

12:43 8. Route LinkedIn engagers

13:34 9. Check before sending

13:51 What will you build with Jev?

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

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

How to Connect

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

X: https://x.com/ericosiu

Cody Schneider joins Eric Siu to walk through how he builds AI marketing workflows: customer research to ad scripts and voice tracks, LinkedIn engagement to outreach, and a LinkedIn article to a live Google ranking check. We also cover the infrastructure, brand checks and testing process behind the work.

The 250,000 monthly LinkedIn DMs mentioned in the conversation are a Nick Abraham example Cody cites. The live demo shows leads and a sequence prepared, not messages sent. The ad videos were still rendering at the end. The ranking and client performance figures are examples from the conversation, not guaranteed results.

Chapters

00:00 11,000 ads: volume and brand checks

00:19 Ad workflow: research, scripts and voice tracks

09:24 LinkedIn outreach: targeting, offers and scale

20:23 SEO workflow: write, publish and check the ranking

26:11 The infrastructure behind all three workflows

32:27 Test ad creative and improve what works

34:31 Build, measure and next steps

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

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

I use Jev with Grokbot to screen the work our agents handle across recruiting, outbound sales, website leads, speed to lead, LinkedIn outreach, content and software renewals.

In this walkthrough, I show the checks we use, the actual content review queue, and a mistake I made: letting the expensive model read everything before asking which passages deserved attention. The useful change is to screen the inputs earlier, inspect the evidence and decide what happens next.

Chapters:

0:00 Jev + Grokbot = Superpowers

0:17 How the classifier works

0:59 From inputs to decisions

1:45 Recruiting and AI-fluency questions

3:33 Single Brain Gateway

3:58 Outbound: check the relationship first

5:00 Website lead qualification

5:12 Speed to lead

5:41 LinkedIn outreach

5:53 Content and AEO

7:14 Single Grain

7:38 The actual content review queue

8:27 Software renewal recommendations

9:01 Screen before expensive model work

10:01 Hold weak evidence

10:12 Ready is not permission to act

10:24 Your next step

These are workflows and recommendations discussed in the recording. Illustrative lead counts and model scores are not measured accuracy, savings or business results. Jev provides judgments; the connected agents perform the next actions, with human review where needed. Image and video review still requires checking the actual media.

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 put Claude Opus 5.5 and GPT-6 Astra through seven work tasks with the same prompts at medium settings. We compare YouTube packaging, ad teardowns, lead journeys, stalled deals, case studies and proposals, video editing, and AEO.

Watch the actual outputs, follow the running score, and see where each model was useful. These are my results from these tasks. I still use and pay for both models.

CHAPTERS

00:00 Opus 5.5 vs. GPT-6 Astra: the test

00:58 API token pricing

01:11 Round 1: YouTube packaging

03:10 Round 2: Ad teardown

06:17 Round 3: Lead journey

07:19 Single Grain

07:38 Lead journey: Opus results

09:24 Round 4: Stalled deals

12:50 Round 5: Case study and proposal

15:35 Single Brain Gateway

16:19 Round 6: Video editing

18:38 Round 7: AEO engine

20:57 Final score and which model to use

The benchmark chart is from Artificial Analysis. Wispr Flow ads appear as examples in the ad teardown. Proposed ads shown are concepts, not campaign results.

👉 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

How to Connect

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

X: https://x.com/ericosiu