エピソード

  • How to Get Ahead of 99% People in Podcasting

    How to Get Ahead of 99% People in Podcasting
    2026/05/18
    Neil and Eric break down the etiquette of podcast collaborations, why giving raw recordings drives reach, and how a give-to-get mindset shapes long-term wins. They share lessons from speaking at the Social Commerce Summit, including QR code lead capture tactics, why case studies supercharge AI sales presentations, and how to calculate ROI on paid speaking gigs. A practical episode on collaboration, lead generation, and choosing the right events to grow your business. Key takeaways ◾Give raw recordings to maximize podcast reach ◾QR codes turn talks into qualified leads ◾Pay-to-speak events can deliver 40x returns Chapters 00:00 Podcast collaboration etiquette 03:00 Give-to-get philosophy 06:26 Social Commerce Summit recap 06:46 QR codes for lead capture 09:00 Lead qualification tradeoffs 11:52 Community in the AI era 12:17 ClickFlow AI content break 12:48 Conversion stats from the event 14:14 Single brain and AI implementation 16:01 Adding case studies to presentations 19:30 Getting paid to speak 20:33 Paying to speak for ROI 22:36 Criteria for paid speaking events 24:11 Calculating speaking ROI 26:04 HubSpot Inbound and brand-building events 27:29 Repurposing speaking clips 𝗔𝗕𝗢𝗨𝗧 𝗧𝗛𝗘 𝗖𝗛𝗔𝗡𝗡𝗘𝗟 Welcome 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 for Daily Marketing Insights!
    続きを読む 一部表示
    29 分
  • Why One-Person Teams Win

    Why One-Person Teams Win
    2026/05/14
    Neil and Eric break down the rise of one-person startup teams, Coinbase’s “pod of one” model, AI-native company structures, and how AI agents are reshaping product, marketing, and service businesses. They discuss judgment as the ultimate competitive advantage, Amazon’s new supply chain services, China’s growing tech influence, and how startups can use AI automation to move faster, scale leaner, and build modern revenue systems powered by agents and infrastructure. Key Takeaways: ⬛️ One-person AI teams are changing startup operations ⬛️ Judgment becomes the most valuable business skill ⬛️ AI agents + automation drive scalable growth Chapters: (00:00) One-Person Startup Teams (00:34) Coinbase Pod Of One (01:48) AI Agents And Judgment (03:04) AI-Native Agency Models (06:23) Automation And Margins (07:25) Uber Growth Strategy (09:18) Amazon Supply Chain Service (10:48) AI Agents And Logistics (11:20) Favorite Snack Recommendations (14:00) Marketing Expansion Into China (16:12) SingleBrain AI Revenue Agents (18:46) OpenAI Symphony And AI Automation
    続きを読む 一部表示
    20 分
  • Google Search Is Winning Again

    Google Search Is Winning Again
    2026/05/13
    Neil and Eric break down why autonomous AI commerce is accelerating after Stripe introduced agentic payments and Cloudflare enabled AI agents to create accounts, buy domains, and deploy apps autonomously. This episode explores AI agents with spending power, Google’s continued search growth in the AI era, hiring elite talent, scaling marketing channels, and the future of AI-driven business operations. Learn how companies like Google, Robinhood, and Coinbase are adapting to the AI economy. ⬛️ Stripe and Cloudflare unlock autonomous AI commerce ⬛️ Google search keeps growing with AI Mode ⬛️ A-player hiring creates massive business leverage Chapters: (00:00) Stripe gives AI agents spending power (00:40) Autonomous commerce and AI workflows (01:24) AI travel and bookkeeping agents (02:40) Future of fragmented AI ecosystems (04:25) Jevons paradox and AI demand growth (05:06) Brian Chesky on hiring elite talent (07:24) Google AI Mode revenue growth (09:45) The Hudson creator growth method (11:23) Why A-players change everything (17:13) Coinbase vs Robinhood crypto economics (20:25) Scaling marketing through expansion (23:24) Optimization versus premature scaling
    続きを読む 一部表示
    25 分
  • The AI Spending Trap

    The AI Spending Trap
    2026/05/12
    Neil Patel and Eric Siu break down the rise of “token maxing,” why AI token spend without ROI is dangerous, and how companies like Anthropic, OpenAI, Google, and Microsoft are battling for AI dominance. They also cover TBPN’s X growth strategy, AI-powered advertising, enterprise AI services, and the marketing playbook behind Grüns’ $1.2B exit. A must-watch for marketers, founders, and AI operators looking to scale with smarter distribution, AI adoption, and performance marketing strategies. Key Takeaways: ⬛️ Token maxing without ROI creates dangerous incentives ⬛️ Google and Microsoft may dominate AI through distribution ⬛️ Grüns scaled to a $1.2B exit with message-match funnels Chapters: (00:00) TBPN’s X Ad Strategy (00:33) Mid-Form Content Growth (01:41) Monetizing Podcast Impressions (03:00) What Is Token Maxing? (04:08) AI Spend vs ROI Debate (05:10) Cutting AI Token Costs (06:16) Anthropic vs OpenAI (09:50) Why Distribution Wins AI (10:49) Anthropic’s $1.5B Venture (12:03) Why Services Businesses Win (13:32) OpenAI Enterprise Growth (14:21) Grüns’ $1.2B Marketing Playbook
    続きを読む 一部表示
    19 分
  • Why AI Won't Kill Jobs

    Why AI Won't Kill Jobs
    2026/05/11
    Neil and Eric break down why the AI job apocalypse narrative is wrong, using fresh data on software engineering demand, AI-powered productivity, product manager hiring trends, and the rise of “AI-pill” talent. They discuss how AI is increasing output instead of replacing workers, why companies still need top engineers and marketers, and how AI is reshaping business efficiency, hiring, and organizational structure. They also debate bloated corporations, eBay’s spending problem, and why technology historically creates more opportunity than destruction. Key Takeaways: ⬛️ AI-powered workers are becoming 100x more productive ⬛️ Software engineering and PM jobs are rising again ⬛️ AI is increasing workloads, not eliminating teams Chapters: (00:00) AI Job Apocalypse Is Wrong (00:42) Software Engineer Demand Rising (01:07) The Rise of AI-Pill Engineers (02:02) AI’s Impact on Marketing Teams (03:49) One-Person Product Teams (04:47) Software Jobs Growing Again (05:32) AI Wage Growth Trends (05:47) Why Technology Creates More Jobs (08:55) Work, Family, and Productivity (12:38) AI as an Equalizer (13:13) Product Manager Hiring Rebound (14:57) AI Adoption in Marketing (15:49) GameStop vs eBay Debate (18:15) Why Big Companies Are Bloated (21:11) The Problem With Growth at All Costs
    続きを読む 一部表示
    22 分
  • What Founders Can Learn From Students Cheating With AI

    What Founders Can Learn From Students Cheating With AI
    2026/05/07
    Eric and Neil break down 3 marketing roles they believe AI will kill first, why entry-level execution work is getting compressed fast, and what marketers need to do now to stay valuable. They also cover why specialists are likely to beat generalists, why human judgment matters more than ever, and how AI is reshaping the structure of marketing teams. They also get into what separates unacceptable, capable, adaptive, and transformative AI users, why most teams are still behind, and how marketers can move beyond basic prompting into real workflows that actually save time and drive results. Key takeaways ◾ Entry-level execution-heavy marketing roles are under the most pressure from AI. ◾ Specialists with strong judgment are becoming more valuable than generalists. ◾ Most teams are still early in their AI adoption and workflow maturity. ◾ Prompting matters less than context, systems, and human review. ◾ AI can increase output fast, but teams still need people who can think strategically. Chapters (00:00) 3 marketing roles AI will kill first (02:42) Why data analysts, junior writers, and generalists are at risk (05:25) The 4 levels of AI marketing maturity (08:07) Why most teams still feel behind (09:40) Why mental health is becoming a bigger AI issue (13:25) The AI tools that can augment your content team
    続きを読む 一部表示
    17 分
  • How I Cut My $7,500 Claude Cost To Almost $0

    How I Cut My $7,500 Claude Cost To Almost $0
    2026/05/06
    Eric and Neil break down how Eric cut his AI token spend from around $7,500 a month to nearly $0 by changing his model hierarchy, fixing fallback issues, and reducing unnecessary API usage. They also get into why usage-based AI pricing is changing software, why some tools become more valuable in an agent-driven world, and what founders, marketers, and agencies need to understand as AI costs shift from seat-based pricing to usage-based pricing. Key takeaways ◾ You can dramatically reduce AI token spend by fixing model hierarchy and fallback logic. ◾ AI costs need to be actively monitored because broken workflows can quietly burn cash. ◾ Usage-based pricing is becoming a bigger part of software economics. ◾ Some tools get more valuable in an agent-first world, while others matter less. ◾ Agencies that help companies become AI-readable may have a major opportunity. Chapters (00:00) How Eric cut his $7,500 AI token spend (03:25) Why usage-based AI pricing is going up (05:08) Why some software matters less in an agent world (08:11) ClickFlow ad break (12:29) Why AI-readable brands matter more (17:19) What this means for agencies and founders
    続きを読む 一部表示
    19 分
  • 6 Signs Your Agency Is About To Fire You As A Client

    6 Signs Your Agency Is About To Fire You As A Client
    2026/05/05
    Eric and Neil break down how AI is changing software and what founders need to understand as user behavior, distribution, and product expectations keep shifting. They unpack why building around websites, dashboards, and traditional UI patterns may matter less going forward, and what happens when people increasingly want outcomes instead of more clicks. They also get into what this means for marketers, agencies, and SaaS companies, why old funnels may become less effective, and where founders should focus if they want to stay relevant as AI changes how people discover, use, and buy software. Key takeaways ◾ AI is changing what users expect from software. ◾ Founders may need to build for outcomes, not just interfaces. ◾ Websites, funnels, and traditional SaaS UX may matter less over time. ◾ Marketers need to think beyond clicks and landing pages. ◾ The companies that adapt faster will have a major advantage. Chapters (00:00) How AI is changing software (03:12) Why traditional UI matters less (06:48) What this means for founders (10:21) Why websites and funnels may lose value (14:37) What marketers and agencies should do now
    続きを読む 一部表示
    21 分