Marketing School - Digital Marketing and Online Marketing Tips

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1. This Company Spends $32m Per Year On Claude Code!?

   5 november 2026 · 21 min

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   Eric opens with Spawn, a company with 10 people that spends about 30 times its payroll on AI, and what an AI-native team looks like in practice. They cover iterating fast while changing less, the Money Prompt, and why experience still matters when AI does the work. Eric runs through Jen Abel's list of what startup sales teams get wrong and the advantage of founder-led sales. Neil explains why a win rate over 50% is a warning sign, often that you are not charging enough. Then GPT-6 Astra being distilled, what that means for IP, and how to make your offer a no-brainer for buyers. Speed and a strong offer beat protecting IP.

   Key takeaways◾AI-native teams can spend far more on AI than on payroll◾A win rate over 50% is a warning sign, not a win◾When IP is easy to copy, the offer and the speed win

   Chapters00:00 Spawn: 10 people, 30x payroll on AI02:05 Iterate fast, change less03:49 Money Prompt and experience05:17 Jen Abel's startup sales list07:48 Founder-led sales advantage10:46 Win rate over 50% is a warning14:23 GPT-6 Astra distilled: IP is dying16:16 Make the offer a no-brainer

   𝗔𝗕𝗢𝗨𝗧 𝗧𝗛𝗘 𝗖𝗛𝗔𝗡𝗡𝗘𝗟Welcome to Marketing School, one of the top business podcasts with over 61 million downloads. Each episode delivers actionable marketing tips and strategies from two entrepreneurs who truly practice what they preach. The show is hosted by Eric Siu, founder of Leveling Up and Single Grain, and Neil Patel, co-founder of Neil Patel Digital and recognized by Forbes as a Top 10 Marketer.

   🎙️ Learn More About the Hosts Eric Siu – Leveling Up: https://www.youtube.com/@LevelingUpOfficial Neil Patel: https://www.youtube.com/@neilpatel

   📩 Free Resources Ubersuggest: https://www.ubersuggest.com/ Answer The Public: https://www.answerthepublic.com/

   ✅ Subscribe fo…

2. Google Stock Fell 12%. 99% Of People Don't Understand What This means!

   4 november 2026 · 20 min

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   Need marketing help? Visit: https://www.singlegrain.com/ and https://npdigital.com/Want to recruit great marketers? Find them here: https://marketingschool.io/hire

   Neil starts with Google's stock falling 12% after earnings, the biggest drop he has seen after a report, and what it says about search. Eric walks through Granola's AEO workflow and how his team moved fast on a trend with an AI summit, plus why being too early can hurt. Neil shares tests on how AI agents pick local businesses, using a water softener search: review volume, fresh reviews, consistent messaging and comparison articles all shape who gets recommended. Eric demos the free AI visibility report, what it costs to run, and why Neil thinks fewer charts convert better. They finish on enterprise sales and booking more calls. AI search rewards brands that stay fresh and consistent.

   Key takeaways◾AI agents lean on review volume, freshness and consistent messaging◾Comparison articles help you get picked in AI answers◾Simpler reports with fewer charts can convert better

   Chapters00:00 Google stock falls 12% after earnings01:15 Neil on Google's valuation02:42 Granola's AEO workflow04:32 Hit trends fast: Eric's AI summit07:03 How AI agents pick local businesses09:00 Reviews: volume and freshness10:56 Why comparison articles win12:41 Free AI visibility report13:46 What the report costs to run14:45 Fewer charts convert better15:51 Enterprise sales and booking calls

   𝗔𝗕𝗢𝗨𝗧 𝗧𝗛𝗘 𝗖𝗛𝗔𝗡𝗡𝗘𝗟Welcome to Marketing School, one of the top business podcasts with over 61 million downloads. Each episode delivers actionable marketing tips and strategies from two entrepreneurs who truly practice what they preach. The show is hosted by Eric Siu, founder of Leveling Up and Single Grain, and Neil Patel, co-founder of Neil Patel Digital and recognized by Forbes as a Top 10 Marketer.

   🎙️ Learn More About the Hosts Eric Siu – Leveling Up: https://www.youtube.com/@Levelin…

3. Why You Should Give Away All Your Workflows

   3 november 2026 · 23 min

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   Neil opens with HighLevel's announcement that it is giving AI away for free, and why so few founders make big, expensive bets like that. Eric argues the bets are getting cheaper: anything you build now is out of date fast, so giving away workflows and bots buys mindshare that turns into service work. They weigh the real risk of not knowing your AI cost cap, rising compute and hardware prices, and Meta's open-ended AI spend. Eric shares why so few people use AI the way Andrej Karpathy describes, and what that means for AI-native firms hiring talent. Then a MacBook Pro quote, a Chinese glass company that got free advertising from the Paris riots, and what Black October's hacks mean for security and passkeys. Free value is still a strong growth lever.

   Key takeaways◾Giving AI tools away free can win mindshare that turns into paid work◾Know your AI cost cap before you make usage unlimited◾Being transparent after a security problem builds trust

   Chapters00:00 HighLevel gives AI away free02:31 Give your workflows and bots away04:30 AI costs, DGX Spark and Anthropic-SpaceX06:57 Meta's open-ended AI spend07:41 Andrej Karpathy: only 0.2% use AI this way09:08 Scale founder's big bet11:18 MacBook Pro $14K quote13:38 Chinese glass company and the Paris riots15:38 Neil's bulletproof windows17:23 Black October hacks and passkeys18:53 Be transparent when things go wrong

4. HighLevel Is Giving AI Away Free. Neil Patel Calls It a Bold Bet (Full Episode)

   2 november 2026 · 1 uur 24 min

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   Neil Patel opens on HighLevel giving AI away free, and why its CEO says that sometimes you just have to eat the cost. Eric Siu explains why he gives his own workflows and bots away too, now that an AI visibility report that once cost dollars costs 18 cents. They cover what AI compute costs now, from Eric's DGX Sparks to a MacBook Pro quote of about $14K, Andrej Karpathy's 0.2% figure, a Chinese glass company's Paris riots post, and simple security steps for Black October. Then how AI agents pick local businesses, Spawn's 10-person team spending 30x payroll on AI tokens, Jen Abel's startup sales list, and why GPT-6 Astra being distilled means your IP is dying. They finish on the FlexJet CEO's view of M&A, the listen-to-talk ratio on sales calls, daily AI performance reviews, pay-for-performance risk, Granola's AEO workflow, and Google stock falling 12% after earnings. AI keeps getting cheaper, so the bold move is to give more of it away.

   Key takeaways◾Giving AI tools and workflows away for free builds mindshare and leads◾Move fast on trends, from events to security news to earnings◾Use AI for daily feedback instead of waiting for yearly reviews

   Chapters00:00 Neil's week: HighLevel, Experian, Milan01:00 HighLevel gives AI away free03:33 Give your workflows and bots away05:32 AI costs, DGX Spark and Anthropic-SpaceX08:43 Andrej Karpathy: only 0.2% use AI this way10:10 Scale founder's big bet12:01 MacBook Pro $14K quote14:21 Chinese glass company and the Paris riots18:06 Black October hacks and passkeys20:30 Hit trends fast: Eric's AI summit23:01 How AI agents pick local businesses28:23 Free AI visibility report32:58 Spawn: 10 people, 30x payroll on AI35:10 Iterate fast, change less36:54 Money Prompt and experience38:22 Jen Abel's startup sales …

5. $1M Revenue, $5K salary? Time To Get a Job?

   29 oktober 2026 · 26 min

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   Neil Patel pays a content agency $17,000 a month. Then they asked for another 10 grand a month.Eric Siu and Neil ask why agency owners taking home $5,000 a month should not just get a job, then react to Gary Vee on the monetization of random content. Lees meer

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   Eric and Neil start with a content agency Neil pays $17,000 a month, which asked for 10 grand more a month and then changed the price an hour later. Neil asks why a team that takes home about $5,000 a month each on over a million dollars in revenue does not just get a job, and Eric says there is no shame in a salary after 10 years without traction. They contrast that with an agency that grew for roughly 38 years with few acquisitions. Then they react to a Gary Vee clip about the monetization of random content, with Neil explaining how algorithms now find interested viewers and Eric adding that authenticity matters. They close with Neil's dislike of being filmed constantly and a bakery post that drew 130,000 likes. Pick the marketing style that fits you.

   Key takeaways◾Charge what you want and pay what makes sense, without lectures◾If the business has not scaled in 10 years, a job is a fine option◾Random content works best when it is authentic and fits you

   Chapters00:00 A $17K a month helper asks for more01:45 Charge what you want, pay what makes sense03:18 What the helper's team takes home03:53 Why not just get a job?05:54 Under $100K a year for years07:00 No shame in getting a job07:21 Equity upside at fast-growing companies08:45 Editing skills can earn more inside a company09:38 An agency that kept growing for decades10:36 How a 38-year agency grew without acquisitions12:47 No right or wrong way to build a business13:46 Gary Vee: the monetization of random content16:33 How algorithms find inte…

6. AI Layoffs Backfired For This Marketing Agency

   28 oktober 2026 · 22 min

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   An internet marketer cut his team from a couple hundred people to under 100 and credits AI and OpenClaw with the work. Eric Siu and Neil Patel explain why AI cannot handle marketing work alone.Then Neil shares why he walked away from buying a European agency that is cutting staff to run on AI. Lees meer

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   Eric and Neil start with a well-known internet marketer who cut his team from a couple hundred people to under 100 and says AI and OpenClaw now do 20 to 30 times more work. Eric says that claim hurts the marketer's credibility, and that AI should elevate capabilities rather than eliminate jobs. Neil describes a call with a European e-commerce agency he decided not to acquire, because it planned to shrink to eight to ten people, said two or three people could run its ad spend, and had lost three of its four biggest clients. Eric lists where AI output still needs a human editor, including his YouTube channel, ad creative, AEO and SEO content, and X posts. They also cover AI metrics that do not match business results, and how to handle client expectations and feedback. Human judgment still decides marketing results.

   Key takeaways◾Cutting staff and crediting AI for it can hurt a marketer's credibility◾AI output still needs human taste and an editor in the loop◾Optimize for business results and client value, not AI-suggested views

   Chapters00:00 Internet marketer says AI replaced his staff00:58 Does cutting jobs hurt credibility?01:46 OpenClaw is unreliable03:16 Marketers who talk about AI without knowing it03:45 Neil's call about acquiring an agency04:33 The agency plans to shrink to eight or ten people06:22 Why the agency is losing clients08:11 Up or out, and selling a company09:08 AI cannot handle marketing work alone10:20 How Eric's view of AI has shift…

7. How to Get Meta Muse to Recommend Your Product or Service

   27 oktober 2026 · 19 min

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   Meta Muse is now recommending products, and in one example it picked Beehiiv over Substack for a newsletter. Eric Siu and Neil Patel break down how to get recommended by AI: keep doing AEO and SEO, and get into new AI marketplaces and plugins early.Plus how Grok helped Neil's co-founder beat a $7,600 Google quote with one under $5,000. Lees meer

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   Eric and Neil start with Rob Hoffman's example of Meta Muse recommending a client's product as the best option on the market, and Muse choosing Beehiiv over Substack for a newsletter. Eric says to get listed you still have to do more AEO and more SEO, and calls Muse, Grok and OpenAI the next surface for it. Neil shares how his co-founder got a $7,600 water softener quote from Google, then had Grok find more companies and chose a quote under $5,000. He says most businesses never see that revenue because they do not track it. They debate whether AI platforms will sell paid leads, and Eric says to get into new marketplaces and plugins the moment they open. They then turn to Meta's AI spending, the data center race, Karpathy's numbers on AI users, and AI capital spending as a share of GDP.

   Key takeaways◾To get recommended by AI, you still have to do more AEO and SEO◾Get into new AI marketplaces and plugins as soon as they open◾AI-driven leads are hard to track, so many businesses miss the revenue

   Chapters00:00 Meta Muse picks Beehiiv over Substack01:01 Muse, Grok and OpenAI: the next surface for AEO01:09 The revenue lost by not optimizing for AI01:46 A $7,600 Google quote vs a Grok quote under $5K03:16 The cost of not optimizing for new channels04:36 Will AI tools offer businesses more leads?06:07 Paid marketplaces inside AI platforms06:56 Will AI platforms keep results pure?08:13 Get into new marketplaces and pl…

8. Why AI Can't Replace Marketers, Gary Vee's Random Content and Meta Muse AEO

   27 oktober 2026 · 1 uur 22 min

   Afspelen
   An internet marketer cut his team from a couple hundred people to under 100 and credits AI and OpenClaw. Eric Siu and Neil Patel explain why AI cannot handle marketing work alone, and why clients pay for results, not effort. Lees meer

   They cover a $17K a month content agency, Gary Vee on the monetization of random content, and how Meta Muse recommended a client's product, which is why getting recommended by AI is the new AEO. They also get into paid marketplaces inside AI platforms, Zuckerberg's all-in data center bet, marketing to robots and agents, Forrester's prediction that agents will influence 75% of B2B buying, and Marc Andreessen on the AI-native gap.

   They close on hiring people who are AI native and why the biggest AI ROI is getting recommended.

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   Need marketing help? Visit: https://www.singlegrain.com/ and https://npdigital.com/Want to recruit great marketers? Find them here: https://marketingschool.io/hire

   Key takeaways◾AI cannot handle marketing work alone, human judgment still matters◾Getting recommended by AI is the new AEO and the biggest ROI◾Hire for AI fluency, and spend on AI where it makes money

   Chapters00:00 Internet marketer says AI replaced his staff01:46 OpenClaw is unreliable03:45 Neil's call about acquiring an agency06:22 Why the agency is losing clients08:47 AI cannot handle marketing work alone11:21 AI feedback creates a bias toward views13:57 Clients pay for results, not effort16:23 Two types of consultants18:38 A $17K a month helper asks for more21:56 What the helper's team takes home24:32 Under $100K a year for years25:59 Equity upside at fast-growing companies28:16 An agency that kept growing for decades31:25 No right or wrong way to build a business32:24 Gary Vee: the monetization of random content35:11 How algorithms find interested viewers38:25 Being filmed at Web Summit40:58 A bakery's authentic viral post41:53 Meta Muse recommends a client's product43:38 A water softener searc…

9. The Truth About Corporate AI Spending (It's Not What You Think)

   23 oktober 2026 · 21 min

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   Accenture found some staff spending $1,000 a month on AI, so it set a $29 monthly limit per employee, and Eric and Neil both think the cap is smart. They point out that reported AI revenue can be gross rather than net, then cite Ramp's AI spend index, where the median is $11. They agree a policy needs exceptions for people who prove value, while Neil shares how he downgraded his ChatGPT plan. The back half covers two-slice teams, Bending Spoons' model of cutting most of a company, and Evernote going from 433 staff at its peak to about 30 today. They close on Berkshire Hathaway's $330M stake in Bending Spoons and the 41% jump in the stock. Spend with a reason.

   Key takeaways◾Accenture's $29 cap is smart, but proven high spenders should get exceptions◾Most people pay for top models to do basic work, so match the model to the task◾Evernote went from 433 staff at its peak to about 30 under Bending Spoons

   Chapters00:00 Accenture caps AI spend at $29 a month00:23 Did staff really spend $1,000 a month?01:53 Reported AI revenue is often gross, not net03:31 Ramp's AI spend index: median is $1104:14 Set a policy, then talk to top spenders04:56 Exceptions for people proving value05:45 Neil downgrades his ChatGPT plan06:39 A 45-minute AI session that is worth it08:26 Two-slice teams, not two-pizza teams09:30 Pirate and architect: coordination drag10:25 Small teams ship faster12:00 Meta's 200 people out of 70,00012:39 Bending Spoons: a private equity model14:04 A layoff post that also launches features15:24 Evernote: 433 staff at peak, about 30 now16:18 Why public markets accept deep cuts17:07 Berkshire's $330M stake, stock up 41%

   𝗔𝗕𝗢𝗨𝗧 𝗧𝗛𝗘 𝗖𝗛𝗔𝗡𝗡𝗘𝗟Welcome to Marketing School, one of the top business podcasts with over 61 million downloads. Each episode d…

10. The Rule of 7 Is Dead: Why You Need 28 Touches Now

    22 oktober 2026 · 18 min

    Afspelen
    Eric and Neil say the rule of 7 has grown toward the rule of 28, and that buyers touch a brand 8 times for a sub-$100 B2C buy and 23 times at $10K-plus. A gelato shop stranger who knew them from different places makes the case that you never know where people will find you. They cover why YouTube drives leads that nobody can attribute, then Meta's $14.9B deal for 49% of Scale AI and the 200-person AI team that Alexander Wang, the former Scale AI CEO, leads. Zuckerberg's line that talent density beats big teams for AI is tested against Meta's 70,000 staff. Neil explains his private equity mindset and his debt at SOFR plus 2%, and they close on the failures that come with big bets. Attention, talent and the cost of big bets. Lees meer

    Key takeaways

    ◾Buyers touch a brand 8 times for a cheap B2C buy and 23 times at $10K-plus

    ◾Meta built a 200-person AI team out of 70,000 staff, which Zuckerberg calls talent density

    ◾Meta paid $14.9B for 49% of Scale AI, and Eric says the bet looks like it is paying off

    Chapters

    00:00 Rule of 7 is now the rule of 28

    00:44 Touches before buying: 8 cheap, 23 at $10K+

    01:34 A gelato shop stranger, and where people find you

    03:53 YouTube drives leads you cannot attribute

    04:27 Platforms stop sharing data

    06:23 Meta's 200-person AI team, talent over size

    07:36 Neil's private equity mindset

    09:18 Zuckerberg asks peers what they would do

    10:44 Neil's debt: SOFR plus 2%

    13:14 Pain now for a bigger company later

    14:17 Failures: rockets, timelines and the metaverse

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