『GTM AI Podcast with Coach K and Jonathan Moss』のカバーアート

GTM AI Podcast with Coach K and Jonathan Moss

GTM AI Podcast with Coach K and Jonathan Moss

著者： AI Business Network
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 Welcome to the GTM AI Podcast, your go-to independent resource to help GTM Professionals become AI Powered. We will cover strategies, new AI tools, AI news and trends, all for the purpose of helping you create real measurable business impact and help your life be easier. We do weekly episodes ranging from interviews to updates to strategy sessions. Sponsored by the AI Business Network www.aibusinessnetwork.ai and GTM AI Academy www.gtmaiacademy.com2025 経済学
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  • Google's AI Is Judging Your AI: The Email Deliverability Wake-Up Call Every Sales Team Is Missing

    Google's AI Is Judging Your AI: The Email Deliverability Wake-Up Call Every Sales Team Is Missing
    2025/12/19
    www.gtmaiacademy.com www.gtmaipodcast.com www.aibusinessnetwork.ai YouTube Description Google's AI Is Judging Your AI: The Email Deliverability Wake-Up Call Every Sales Team Is Missing Every third email you send lands in spam. That's 40-50% of your pipeline that never even sees your outreach. In May 2024, Google quietly switched to AI-based spam detection. Not keyword filters. Not rule-based systems. Actual AI deciding whether your AI-written emails sound human enough to reach an inbox. Most sales teams have no idea this happened. They're still running the same playbook while their domain reputation burns. Anastasiia Ivannikov, CEO of Folderly and former sales leader at unicorn Macpaw, breaks down exactly what changed and what to do about it. We get into the mechanics—spintax, sending velocity, behavioral signals—and the bigger strategic problem: teams using AI as a brain replacement instead of a thinking partner. If you're running outbound, managing SDRs, or building AI-powered GTM motions, this one's required listening. TIMESTAMPS 0:00 - Intro 1:00 - Anastasiia's background (started in sales at 14, joined Folderly with a 3-week-old baby) 3:00 - The problem: every third email lands in spam 5:00 - Cold outreach vs email marketing—same problem, different mechanics 7:00 - How Folderly works with AI SDRs and automation tools 8:00 - Is email dead? (Spoiler: no, but it's changing) 10:00 - The data: what actually impacts deliverability 11:00 - Google's AI shift in May 2024—AI judging AI on humanness 12:00 - Spintax explained: why copy variation is now survival mechanics 13:00 - Sending velocity: why your sequencing tool's defaults are killing you 14:00 - Value-based email content vs lazy blasting 15:00 - AI as thinking partner vs AI as brain replacement 17:00 - Why single-LLM dependency creates strategic blind spots 18:00 - The future of Folderly and multichannel outreach 19:00 - The new math: 5 touches to convert → now 17 21:00 - Why offline and physical channels are making a comeback 22:00 - Detecting AI content (the M-dash and "fluff" triggers) 23:00 - What Anastasiia's excited about: smaller teams, faster MVPs 26:00 - The value of human oversight when AI does 95% of the work 28:00 - Prompting still matters even as models improve 29:00 - Anastasiia's AI tool stack: Gamma, Midjourney, Clay, n8n, Instantly, Descript KEY TAKEAWAYS → Google switched to AI-based spam detection in May 2024 → Spintax variations are no longer optional—they're table stakes → Sending velocity matters as much as copy quality → Use multiple LLMs to avoid strategic blind spots → 17 touches to convert now vs 5 a few years ago CONNECT Anastasiia Ivannikov: https://www.linkedin.com/in/anastasiia-ivannikova/ Folderly: https://folderly.com Coach K (Jonathan Kvarfordt): https://www.linkedin.com/in/jonathankvarfordt/ SUBSCRIBE for weekly conversations with GTM leaders on AI, sales, and revenue operations. Drop a comment: What's your current email deliverability rate? Most teams don't even know
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    31 分
  • How to Actually Implement AI That Works (Not Another Failed Pilot)

    How to Actually Implement AI That Works (Not Another Failed Pilot)
    2025/12/10
    www.gtmaiacademy.com www.aibusinessnetwork.ai Ghost Team co-founder Elliot Garreffa breaks down why most companies struggle to see ROI from AI—and what to do about it. This conversation cuts through the hype to reveal the unglamorous truth: successful AI implementation isn’t about buying licenses or running proofs of concept. It’s about understanding your actual workflows, identifying where AI creates 10x (not 2x) improvements, and building systems that your teams will actually use. Elliot shares real examples of SEO systems that compress months of agency work into minutes, and explains why human-in-the-loop isn’t a compromise—it’s best practice. “If you just go and prompt an LLM and try to create some content, it might make incremental improvements, but it’s actually not that good. Where we come in is building systems that create 10x, 100x improvements.” “You have to really understand the problem before you tackle it. Any good technology implementation does that step upfront, and we’ve found it incredibly true for the AI space.” “Don’t think about using AI to do this part of this process. You can just do an entirely different process. That gets far better results than just slapping things on top.” “The kind of thing that would’ve taken months to get back from an agency—we’re doing it directly within the chat window. That obviously changes a lot in terms of a typical process.” “When you add that human touch, it is significantly better. Regardless of how much training data you have, you can still really tell whether something has been AI-generated or not.” “One of the best things you can do when first getting started: look at things you’re spending a huge amount of time on. Focus on automating those first. They save you time, which means you can focus on more valuable tasks.” “People see these workflow automations on LinkedIn and they want them. But whether these systems work is all about the detail under the hood—the prompting, the training data, the customization to your brand.” This conversation goes deep on MCPs, context engineering, and the technical stack that actually delivers results. Listen to the full episode to hear Elliot walk through a live demo of automated SEO research and strategy that would take traditional agencies weeks to produce and learn why starting with Lindy or n8n beats jumping straight to building custom SDR systems.
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    1 時間 9 分
  • Why 93% of Your Team Uses AI But You Think It's 30%

    Why 93% of Your Team Uses AI But You Think It's 30%
    2025/12/04
    www.gtmaiacademy.com www.aibusinessnetwork.ai https://www.futurecraftai.media - Kens podcast Connect with Ken on Linkedin: https://www.linkedin.com/in/kenroden/ The Leadership Blind Spot That’s Killing Your AI Strategy If you’re a GTM leader who thinks roughly 30% of your team is using AI, I have uncomfortable news: 93% of white-collar professionals are already using it. That’s not a typo. That’s the finding from Ken Roden’s doctoral research at Temple University, surveying 200 professionals with statistically significant results The gap between what’s actually happening and what leadership perceives is now the single biggest barrier to AI execution. And it gets worse. The Real Reason Your AI Pilots Are Failing Every headline screams that 95% of AI pilots are failing. MIT published research. Consultants are writing case studies. Everyone assumes the problem is employee resistance, inadequate technology, or change management failures. They’re all wrong. Ken’s research reveals the actual failure point: employees don’t trust their leadership’s vision for how AI will be implemented. It’s not that people won’t use AI - they’re already using it extensively. It’s that they don’t believe leadership understands what they’re doing or has a coherent strategy for scaling it. Think about what that means. Your team is running shadow AI operations right now. They’re using ChatGPT, Claude, and dozens of other tools to do their jobs better. But when you announce your official AI initiative, they don’t trust it enough to adopt it at scale. Key Quotes That Reveal the Pattern On the confidence-competence gap: “There was definitely a correlation between people who said they use AI regularly and them saying that I am confident in my abilities to use AI. And I would say that’s dangerous. Because what, to your point exactly, you might think you’re good at this, but you’re actually maybe not as good as you think.” On what’s actually working: “The stuff that works, the people have the most success with, it’s the most boring stuff. It’s how do we get data from our Slack channel about customer insights into Salesforce... One of the most interesting use cases I saw... saved 20 hours a week per rep.”
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    35 分
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