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Eric shows the Jev use cases he is running for his teams, from classifying every Instagram follower to scoring hooks and offers across competitors for a few dollars. Neil explains how his Muse agent now writes the follow-ups on M&A deals he first discussed two or three years ago, and why he gives Meta access he would never give the AI labs. Eric predicts Google and Apple will each ship their own Muse, and they compare it with OpenClaw. Then the story of an AI answer nobody checked and why Neil told them he would fire the person, followed by the core idea: AI is leverage, and leverage on a bad position just loses you money faster. They close on an $80M real estate pitch Neil walked away from. A practical episode on putting AI agents to work.

Key takeaways
◾Classification at scale now costs dollars, not an analyst's week
◾The deals you close come from follow-ups on talks two or three years old
◾AI is leverage: it multiplies good judgment and bad judgment equally

Chapters
00:00 Jev use cases for marketers
02:50 Neil's AI writes his M&A follow-ups
06:02 Prediction: Google and Apple ship their own Muse
07:53 OpenClaw vs Muse
11:13 'I would fire you': AI output nobody checked
13:07 Slop cannons in an AI-native company
13:54 AI is leverage
15:11 The $80M real estate pitch
17:12 Location, location, location

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Eric brings Peter Diamandis's take that Nvidia's greatest moat, CUDA, is leaking now that AI can port code to any chip, and why Jensen bought Mellanox years ago to own the interconnect instead. They debate the three moats that survive: speed of reinvention, capital velocity and brand. Neil keeps brand, drops capital after Harry Stebbings' three rounds in three weeks, and adds talent density, showing six of the top ten companies come from the Bay Area. Then Meta Muse: the $14B Scale bet Neil admits he would never have made, Eric's bot Doodoo picking his wardrobe, and Muse plus Jev sorting 116,000 followers for $3.30. It ends on the personality test that explains the show. A sharp episode on what still protects a business.

Key takeaways
◾Your moat lasts until the next one; speed of reinvention is the durable edge
◾AI shoppers still buy brands, because people tell them what status looks like
◾Neil waits for proof, then bets big; Zuckerberg bet first and won

Chapters
00:00 Nvidia's CUDA moat is leaking
02:29 Neil: brand is a moat, capital isn't
03:35 Harry Stebbings: three rounds in three weeks
05:07 Six of the top 10 companies come from the Bay
07:02 The three moats that survive
09:13 Neil: AI shoppers still care about brand
11:46 Meta Muse and Scale's $14B bet
12:16 Doodoo picks Eric's wardrobe
13:04 Muse + Jev sort 116K followers for $3.30
14:29 Neil's influential followers
15:43 Why Neil waits for proof, then bets big
18:11 Why this podcast works: persist vs change
19:03 The personality test: 99% vs 1%
20:50 Empathy at work

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Shopify's Tobi Lutke has a name for AI work nobody reviewed: a slop grenade. Eric explains how it lands on your desk and blows up your day, and Neil says AI simply reveals who is lazy and who is great. At his conferences almost everyone uses AI, but fewer than 5% edit what it writes, which is why so much marketing now looks the same. They build a policy on air: an emailed warning, then a write-up, then termination, and Eric argues growth only comes from discomfort, from SpaceX to training to failure. The episode closes on a 64-year-old SEO who spent $40K on his own AI rigs because nobody had to tell him to. A blunt episode on standards in the AI era.

Key takeaways
◾AI amplifies what is already there, good work and lazy work alike
◾Fewer than 5% of people edit AI output; that is why it all looks the same
◾Put a paper trail on slop grenades: warning, write-up, then out

Chapters
00:00 Slop grenades: AI work nobody reviewed
01:56 Neil: AI shows you who's lazy
04:35 Thinking Machines: AI amplifies intelligence
06:36 Less than 5% edit what AI writes
08:43 The 'is this your best work?' rule
10:38 Warning, write-up, termination
12:28 Growth comes from discomfort: SpaceX
13:24 Train to failure, work to failure
15:39 The 64-year-old SEO who spent $40K on AI rigs

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Neil explains why he despises coaches who sell how to get rich, and Eric separates them from the Bill Campbells and Matt Mocharys who coached Apple, Google, Coinbase and OpenAI without charging founders. Neil reads a cold pitch promising him an extra million a year and Eric dissects why it fails before the first reply. Then the two ideas Eric wants every operator to react to: supermemory killed its viral company brain to protect its core, because unshipping matters more than shipping when anyone can build anything, and Paul Jun of Ramp's brand as software, where a design file carries the brand into every asset so designers do the new work. Neil's take on ChatGPT agent ads, and BugBasher, the Devin agent Ramp gave a card and a phone that made $75 selling pest-control leads in four weeks. A sharp episode on focus, coaching and what AI agents can already do.

Key takeaways
◾If someone doesn't do the research before your check, it gets worse after it
◾When you can ship anything, unshipping is the discipline that keeps you extraordinary
◾Codify the brand as software so creative people spend their time on what a system can't predict

Chapters
00:00 Coaches who sell 'how to get rich'
00:48 Two kinds of coaches: Bill Campbell vs the funnel
02:03 People who are good at it, do it
02:42 The Trillion Dollar Coach and Matt Mochary
03:56 Neil reads the cold pitch
05:14 What's wrong with that message
06:00 No research before the check? It gets worse after
07:03 The legendary coaches never charged founders
08:25 Proven track record vs get-rich promises
09:21 Unshipping beats shipping
11:06 Shipping too much makes products harder
11:41 supermemory's conflict of interest
12:35 Content that wins on X and LinkedIn
13:14 Brand as software: Paul Jun of Ramp
15:25 Are you working like this? Design files and AI-pilled designers
16:10 Boomerang employees prove the vision
17:02 ChatGPT agent ads are coming
17:35 BugBasher: the AI agent that made $75
19:36 Agents that lose you money

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Eight Sleep's co-founder says the company does close to $100 million in email marketing with a team of zero after his co-founder built the bots in three days. Neil calls spades spades: email is harvesting demand that other channels paid for, and one person plus AI would beat both. Eric's version is the agent manager, the job he now interviews for. They scroll Harry Stebbings' Instagram, built on tech's most controversial stories, and debate whether that brings a VC the right deal flow. Eric demos Instinct, the $10 billion iMessage agent that planned his travel and got him onto a waitlist that morning, and the pair take apart Roy Lee's Cluely content and the cold TikTok bio a fan made of Neil. The close: Elon, Buffett and Rockefeller became brands by doing the work. A candid episode on headlines, hype and what content is actually for.

Key takeaways
◾'No employees' is a headline; the channel mix and the humans behind it are the real story
◾Sensational content grows an account fast and rarely brings the right customer
◾If the product were crushing it, the founder wouldn't have time for viral content

Chapters
00:00 $100M in email with no employees
00:54 Neil: email isn't doing that alone
02:29 The agent manager: everyone's next job
03:51 Harry Stebbings' Instagram
04:46 500 views to 40K: scrolling Harry's reels
06:38 Will controversial content bring the right deal flow?
07:09 The $10B iMessage startup
08:11 Instinct: booking travel and skipping a waitlist
10:03 Deal flow vs views: Neil's take
10:50 Put your hand on the stove
11:14 Accenture doesn't do sensational
11:43 Roy Lee (Cluely): 'global rank #1 entrepreneur'
14:02 Juiced numbers, and content as a tell
15:22 The rich people Neil knows don't make content
15:49 A fan's TikTok bio of Neil
17:22 Elon, Buffett, Rockefeller: brands from the work

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Eric opens with Bryan Johnson's team telling creators to forget the content calendar and iterate, and how he now rewrites and reposts flopped posts by voice on the walk to the gym. Neil's newest test asks viewers to comment for a free audit, and the pairing metric he wants on every social hire is leads, not views. Then enterprise specifics: a three-year contract that grew out of work in one region, why only two to three percent of NP Digital's enterprise revenue traces back to Neil's personal brand, and how ten-person search agencies quietly decide the biggest marketing contracts. Eric opens his Leveling Up channel to show the wide-TAM experiment, 8.9 million views on one short and interviews that got praise from entrepreneurs' spouses but no leads, before Neil explains the acquisition lesson that grows a bought agency's EBITDA 40 to 60 percent in a year and why he follows up with everyone. A grounded episode on measuring what actually pays.

Key takeaways
◾Pair views with leads for every social hire, or the team optimises for likes
◾Wide-TAM content brings views and comments, not enterprise leads
◾Buy the specialist that big brands already call; the follow-up is where the deals are

Chapters
00:00 F your content calendar
01:36 Comment-to-lead: the 37-places reel
03:34 Every metric needs a pairing metric
04:17 NP Digital vs NP Accel: where SMB leads go
04:53 A format library your agent keeps fresh
06:09 A 3-year contract from one region's work
07:56 Stop creating content for 90 days?
08:22 6% of enterprise leads come from Neil's brand
08:58 70% of SMB leads, 50% of SMB revenue
10:17 Procurement, RFPs and the search agencies
11:56 Dan Martell's formats and wider TAM
12:52 Seminars and ascension funnels
13:34 Eric's wide-TAM experiment on Leveling Up
15:17 The shorts: 3.9M, 2.7M, 2.1M views
17:02 Why Eric stopped: no leads
17:37 Distribution beats content when you have leverage
18:44 The acquisition lesson: 40-60% EBITDA growth
21:21 The fortune is in the follow-up
22:07 'How are things going?' scheduled for March 2027

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Eric and Neil open on Meta Muse, Meta's new autonomous agent, and Neil explains why he trusts Meta with it more than OpenAI or Anthropic: Meta has held everyone's data for years and people already live inside its products. Eric shows what his own Muse did in minutes, pulling Ryan Deiss's best Instagram formats and rewriting them for his channel, and argues that formats are now the job. Then the real debate: Neil says almost all of their content is still too broad, that specific content for a specific buyer drives revenue even at a fifth of the views, and that a room of enterprise marketers in Ecuador proved it when two or three percent knew he ran an agency. They land on a secondary hook, one line that says who you are and what your company does, placed wherever it sounds natural. A practical episode on trust, formats and making your content pay.

Key takeaways
◾Trust decides which AI agents win, and Meta starts with more of it than the labs
◾Let an agent keep your format library fresh so you can just record
◾Specific content converts; add a one-line credibility hook so buyers know who you are

Chapters
00:00 Meta Muse: Meta's autonomous agent
00:34 Why Neil trusts Meta more than OpenAI
02:35 Eric, the GrokBot team and Ryan Deiss
03:49 Ryan's Instagram: niche or broad?
05:46 Tier lists and reactions: the formats that work
06:49 Eric's Muse rewrites Ryan's formats
08:01 Neil: all three of us are still too broad
09:50 Danger gets views: Nick Shirley
10:47 A 100K-view video can be a great video
11:44 Ecuador: 3% of the room knew Neil had an agency
13:25 Accenture, TAM and who you're really selling to
15:22 The secondary hook: say who you are
16:50 Where the mention goes: wherever it's natural
17:27 Test it: from 3% to 10% in a year

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It took 64 clicks to buy a Tesla online, 30 of them signing loan documents. Eric explains the five-step algorithm from the book of the same name (question, delete, simplify, speed up, automate) and how it 20x'd Tesla's website sales. Then the data: AI-generated ads are beating human creative on completion rate (92% vs 90% on connected TV), Shopify's Q2 shows $116 billion in GMV and a platform built for AI agents, and Neil's case that SEO and GEO are merging into one thing, brand. Eric on the new agents he is testing, Instinct and Meta Muse, and the week's grand finale: Rohan Nayak's post on how Pocket FM went from zero to $500 million in ARR with an AI ad machine that makes 17,500 ads a month.

Key takeaways
◾Question, delete, simplify, speed up, then automate; most people automate first and fail
◾SEO or GEO, the long game is brand; you have to show up everywhere
◾A 2% to 2.25% CTR lift cut Pocket FM's CAC by 30%; build the ad machine around that insight

Chapters
00:00 Tesla 20x'd website sales: 64 clicks to 3
01:35 Buying a car on a website
02:55 AI ads beat human creative on completion
04:19 Shopify Q2: $116B GMV and AI commerce
05:38 SEO and GEO are merging into brand
08:04 Search everywhere optimization, again
10:49 A SaaS company diversifying off SEO
11:46 Instinct and Meta Muse agents
14:15 Pocket FM: $0 to $500M ARR with 17,500 ads a month
17:11 Build your own ad machine

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Eric and Neil open up their own marketing week. Eric's $250 test assignment that turned into a $2,000 quote, the GrokBots he built in his free time (a call bot that phoned a spa and confirmed a booking, a haggle bot renegotiating every software bill, and a speed-to-lead bot that calls every form fill within 60 seconds), and the 2x2 he uses to decide which agency work becomes a reusable workflow and which gets killed. Neil on speed to learning, why wins on one channel take too long to reach the rest of the company, and how he finds agencies that stopped growing and buys the ones losing deals only because they are too small. Then the social tests: Neil's new screen-share format and LinkedIn engagement scraping, Eric's comment-to-DM flow with Lead Shark and Goji Berry, and the YouTube video that was edited entirely by AI.

Key takeaways
◾Every lead gets a call within 60 seconds; a bot can do it and sound good
◾Speed to learning is the bottleneck: move a win from one channel to every channel fast
◾Reusable workflows beat custom premium work; build them, then hand them to the team

Chapters
00:00 Our marketing week: the $250 test that failed
02:42 The GrokBot that booked Eric's massage
04:17 Haggle bot and speed-to-lead in 60 seconds
05:18 Neil: speed to learning
07:46 Buying agencies that stopped growing
10:24 Eric's 2x2: reusable workflows
13:14 Neil's new screen-share format
15:40 Scraping your LinkedIn engagers
16:38 Comment-to-DM with Lead Shark and Goji Berry
18:21 YouTube: relevant views beat viral views
19:54 A fully AI-edited video
22:16 AI thumbnails that actually look like you

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Nike's market cap peaked at $280 billion in 2021 and has lost $223 billion since. Eric walks through Trung Phan's breakdown of how it happened: McKinsey advised Nike to eliminate its running, basketball and soccer categories, the marketing budget moved from brand advertising to programmatic retargeting, and hundreds of wholesale partners were cut for a direct-to-consumer bet that collapsed when shoppers went back to stores. Neil on why consultants who never ran a business should not be running yours, and why a kid asking for Nikes is what good brand advertising looks like. Then LeBron James' Polymarket partnership and why both hosts call it brand eroding, and the shirtless YouTuber Eric calls the Sam Sulek of e-commerce.

Key takeaways
◾Nike cut what worked (categories, brand ads, retail partners) for what was easier to measure
◾A brand is what people say about you when you're not in the room; retargeting does not build it
◾It takes decades to build a brand and five minutes to erode it

Chapters
00:00 Nike lost $223B: McKinsey killed the categories
01:32 Consultants who never ran a business
04:06 Locked in: adapt or die
04:34 Nike swapped brand ads for retargeting
06:36 Why kids wanted Nikes
07:59 Neil's Tesla
09:16 Nike burnt its wholesale partners
10:07 LeBron x Polymarket: a brand-eroding move
13:07 The Sam Sulek of e-commerce
15:22 What views actually matter