The AI SEO Playbook for 2027 (AEO, GEO + AI Agents)

👉 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

👉 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

👉 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