GTM AI Podcast with Coach K and Jonathan Moss

www.gtmaipodcast.com For more from Ryan: https://superhumanrevenue.beehiiv.com/p/hiring-an-ai-transformation-leadAnd Ryans Linkedin: https://www.linkedin.com/in/ryan-staley/Ryan Staley built a division from zero to $30M with four salespeople and no marketing budget. He's taught 800+ CROs how to use AI. On this episode, he pulled back the curtain on the agentic operating system he built to run his entire business — from CEO decision-making to content creation to pipeline management — using Claude Code, Obsidian, and API-connected tools like Fathom and HubSpot.This wasn't theory. Ryan screen-shared his actual system, showed real outputs, and walked through the folder structures, memory layers, and agent orchestration that let him operate "at the speed of thought."

www.gtmaipodcast.comArup Linkedin: https://www.linkedin.com/in/arupchakravarti/Most Clay users spend $2K/month to build prettier ZoomInfo clones. Arup Chakravarti is doing something different.Arup is a 20-year RevOps and Enablement veteran, Fellow at the Institute of Sales Professionals, and one of the sharpest operators in the UK GTM space. He spent the last two months going deep on Clay, not as a GTM engineer, but as an enablement brain. The result is a psychographic prospecting system that identifies sales leaders who actually care about developing their teams, not just ones who match a firmographic ICP.In this episode, Arup shares his live Clay build on screen. You'll see:How he built a UK Healthcare Providers list with confidence-scored strategic priority analysis (green/amber/red), pulled from the last 10 articles per company, parsed in JSON, and filtered into meaningful themes.The "PDP Advocacy" column. A psychographic classifier that scores every sales leader as a Strong / Moderate / Weak advocate for professional development based on their LinkedIn profile, posts, comments, and likes. This is the column most Clay users never build because they don't have the enablement lens to know it exists.The iteration that unlocked it. Arup initially scoped the prompt too narrowly ("advocate for the sales function") and broadened it to "advocate for professional development." One word change. Massively bigger qualified pool.Clay's hidden edge: the Google Maps integration that finds mom-and-pop businesses (lawyers, solicitors, local firms) who aren't on LinkedIn at all. If you sell to local SMBs, this is the unlock.Honest data: Clay vs. LinkedIn for employee count accuracy. Spoiler: Clay is closer to actual reported figures than LinkedIn for private companies, because LinkedIn inflates headcount through tagged resellers and influencers.Arup also shares his Clay difficulty rating (middle of the pack, "a little fiddly"), what he had to learn on the fly (JSON structures), and why Clay University is the free onramp most people skip.The throughline of the whole episode: the quality of your Clay output is capped by the domain expertise behind your prompts. A GTM engineer can build a bigger list. An enablement vet, a CS leader, or a product marketer can build a smarter one, because they know which soft signals matter.Connect with Arup: https://www.linkedin.com/in/arupchakravarti/Connect with Coach K: https://www.linkedin.com/in/jonathankvarfordt/CHAPTERS:00:00 — Intro and reunion with an old enablement friend02:25 — Arup's background: 20 years in RevOps, enablement, and the North London pivot04:05 — What you'll learn: Clay for GTM outreach from an enablement lens06:50 — How Arup describes Clay: the online spreadsheet that operates on itself09:35 — The Google Maps integration nobody talks about (mom-and-pop targeting)11:40 — The use case: UK Healthcare Providers + the ISP case study12:45 — The psychographic targeting breakthrough15:45 — Future trend: LinkedIn political drift and prospecting risk18:10 — LIVE: Walking through the UK Healthcare table19:20 — Pre-built Clay AI columns (the ones with the tiny hat logo)20:50 — JSON parsing and pulling thematic insights from the last 10 articles22:30 — Strategic Priorities with confidence scoring (green/amber/red)23:35 — Building the Sales Leaders sub-table24:00 — Data accuracy: Clay vs LinkedIn for private companies25:30 — The PDP Advocacy column (the one nobody builds)26:00 — Structured prompting inside Clay27:30 — Coach's take on context-in-prompt vs prompt bloat30:25 — Live email generation from the full signal stack31:10 — Email walkthrough: "Strengthening talent via strategic partnerships"31:40 — The honest answer on results (Arup hasn't operationalized yet)32:30 — Clay difficulty rating on a 1-10 scale33:55 — Wrap-up, next roles, and the 6-month follow-up pact

www.gtmaipodcast.comwww.spara.coTo connect with David: https://www.linkedin.com/in/davidwalker4/David Walker is the co-founder and CEO of Spara, the conversational GTM agent platform powering inbound motions for some of the fastest-growing B2B companies. In this episode, he makes a case most GTM leaders are dodging: for the last 20 years, your revenue was capped by how many humans you could put on a phone. That constraint is gone. And if your front door is still a static website with a "Contact Us" form, buyers are already treating you like a dead end.David breaks down:Why the old front door (your website plus an SDR team) no longer matches how buyers actually buyThe "10X Horsepower" thought exercise that reframes AI strategy from "automate a task" to "redesign the motion"Why 99% of Spara customers now lean INTO telling prospects it's AI (up from 50/50 at launch) and why buyers get MORE direct, not lessLive demos: inbound web form to phone call in 2 seconds, agentic email that replies back at 11pm, prompt tuning with an AI that tunes your agentThe Kayak vs Wedding Planner filter for deciding which GTM moments should be human and which should be AIReal customer results: 3X MQL rate, 80% drop in unqualified leads, doubled sales team headcount BECAUSE the agent workedWhy narrow point-solution demos look sexier but platforms are what actually move KPIs (A/B testing tone and prompt down to conversion)Where the roadmap goes next: agent-to-agent selling, co-pilot reps, and browser/computer-use agents that actually run the demoIf you are rethinking inbound, debating whether to replace or augment your SDR team, or trying to figure out what a "GTM AI motion" actually looks like in 2026, this is the most direct, founder-grade breakdown you'll get.Timestamps:00:00 — Intro and who David is beyond the resume02:00 — The one takeaway: if you're not using conversational agents, you're missing the boat03:00 — The core problem: GTM has been capped by sales team capacity for 20 years04:15 — Why the old front door is no longer enough04:45 — What Spara is and who it's built for05:00 — Clay vs n8n vs Spara: how the market splits up06:00 — Agent-to-agent selling and the new top of funnel07:00 — LLMs as the new discovery layer and what that means for your website08:30 — Live demo: web form fills to phone call in 2 seconds09:45 — Why 99% of customers now say "this is AI" (up from 50/50)11:00 — Agentic email: replying at 11pm and progressing the deal overnight13:00 — Knowledge retrieval (RAG), prompting inside the product, and why "answering questions" is the easy part15:00 — Optimizing agents: prompt tuning, red-teaming, simulated personas16:00 — Post-sale and PLG upsell workflows across chat, email, and voice19:30 — The roadmap: sales rep assist, co-pilot agents, and browser/computer use for live demos22:30 — What Spara, Clay, and Agency do for David internally24:00 — The mistake David sees most: "I just want to automate one small piece"25:00 — The 10X Horsepower thought exercise28:00 — Kayak vs wedding planner: the hybrid motion filter31:00 — Case study: 3X MQLs, 80% drop in junk32:00 — Case study: doubled sales team BECAUSE the agent worked33:00 — Why point-solution demos mislead and platforms move KPIs34:45 — Close and where to find David

www.gtmaipodcast.com Marchelle: https://www.linkedin.com/in/marchelle-renee-mooney-87918a39/Mangomint: www.mangomint.comMarchelle Rooney didn't learn to code. She learned to talk to Claude Code. And now her non-technical sales team is building tools that make their engineering team do a double-take.In this episode, the VP of Sales at Mangomint ($25M ARR, salon and spa SaaS) shows exactly how her team:→ Built a custom LMS for product training using Claude Code + Notion MCP (no developers involved)→ Analyzed 212 BDR cold call transcripts in 3.5 minutes to rebuild their entire outbound playbook→ Created a Golden Script system that drove an 8% win rate increase (29% → 37%)→ Automated post-call task extraction and hardware ordering from call transcripts→ Solved a data import problem in one week that a senior engineer said was impossibleMarchelle's background: competitive dancer → precision haircutter → salon owner → hawking $2,200 hair extensions → VP of Sales at a vertical SaaS rocket ship. Her team runs a 2-day sales cycle and closes 20-30 new logos per month per AE.Her philosophy: "Micromanage the data, not the people." Give non-technical operators Claude Code and a mandate to find friction. The best solutions bubble up. Then engineering hardens what works.KEY TIMESTAMPS:0:00 - Intro + Marchelle's wild career path (salon to SaaS)8:00 - The custom LMS her Director of Onboarding built in Claude Code13:00 - Post-call automation: transcript extraction + one-click hardware ordering17:00 - The Golden Script project: analyzing transcripts to rebuild the sales playbook21:00 - 8% win rate increase results22:00 - BDR transcript analysis: 212 calls scraped in 3.5 minutes27:00 - Build vs. Buy: why she doesn't wait for vendor integrations31:00 - The junior analyst who solved the "impossible" import problem34:00 - Selective hiring: why she doesn't start with headcount plans37:00 - The daily AI discipline and the future of sales leadershipTOOLS MENTIONED:Claude Code (Anthropic)Notion (with MCP integration)Momentum (call intelligence)Nooks (dialer + sequencer)Avara (AI sales simulator)Mangomint (their product)#GTMAI #ClaudeCode #SalesLeadership #AITools #RevenueOperations #SalesEnablement

www.gtmaipodcast.com Account planning used to take 2 quarters of change management. Justin Driesse built a Notion AI agent that does it in 90 seconds. His CRO saw the output and asked, "Is this real?"In this episode, Justin Driesse (Director of Sales Enablement at Legora) walks through how he built an agentic account planning workflow using 5 chained prompts in Notion AI. No code required. No engineering team. Just a Notion page, clear prompting, and the right knowledge base already in place.We cover:How the "Yes, Chef" agent generates detailed account plans with tiered stakeholder maps, competitive intel, and inline footnoted sources in 90 secondsWhy Notion is the ultimate RAG system (and how that changes the agent-building game)The death of the 2-quarter account planning rolloutWhy enablement needs to break up with content and focus on processHow Legora ran their Stockholm SKO with AI-generated team certifications built overnight from workshop contentThe macro intelligence unlock: running agents across hundreds of account plans to find deal patterns before they closeJustin's background spans teaching high school English, training accountants at a global firm, enablement at Amazon/Twitch, Slack/Salesforce, Writer, and now Legora. His perspective on compressing learning time with AI is one of the most practical I've heard.== CONNECT ==Justin Driesse on LinkedIn: https://www.linkedin.com/in/justin-driesse-361943159/Legora: https://legora.com/== GTM AI PODCAST ==Website & Podcast: https://www.gtmaipodcast.comSubscribe to the GTM AI Newsletter for weekly actionable intelligence on AI for go-to-market teams== ABOUT ==The GTM AI Podcast is where go-to-market leaders learn how to actually use AI to drive revenue, pipeline, and team performance. No hype. No fluff. Just what works.#GTMAI #SalesEnablement #AIAgents #AccountPlanning #NotionAI #GTMAIPodcast

https://www.gtmaipodcast.com https://www.gtmaiacademy.comRoman Linkedin: https://www.linkedin.com/in/rom%C3%A0n-czerny-11b773199/https://www.gojiberry.aiIn this episode, Roman walks through the entire system live on screen. You'll see how Gojiberry's signal agents identify warm leads in real time, how Claude ranks and personalizes every message, and the multi-channel marketing machine Roman runs across 7 LinkedIn accounts, 3 X accounts, YouTube, and Reddit.The numbers speak for themselves: 50% reply-to-blueprint rate, 70% demo close rate, 35% trial-to-paid conversion.Key takeaways from this episode:00:00 — Intro & Roman's journey from engineer to SaaS founder01:30 — What Gojiberry AI does and how it's different04:00 — Live demo: How AI finds and scores high-intent leads08:00 — Why Gojiberry vs. building your own with Claude Code09:00 — Signal agents: configuring ICP and intent tracking12:00 — The full funnel: leads → blueprint → demo → close14:00 — Conversion metrics breakdown (50% / 70% / 35%)15:00 — Multi-channel strategy: LinkedIn, cold email, YouTube, Reddit, X17:00 — Managing 7 LinkedIn accounts with AI content tools18:30 — Using Gemini + Whisper for content creation at scale19:00 — YouTube SEO hack: competitor review videos21:00 — AI agents talking to AI agents: the future of outreach24:00 — Why targeting active LinkedIn users doubles your results25:30 — The blueprint strategy: give value before asking for demos27:00 — How a lead magnet went viral and became Gojiberry's growth engine🔗 Resources:→ Gojiberry AI: https://gojiberry.ai→ Coach K's viral LinkedIn post about Gojiberry + Cowork: [link]📩 Want the AI Lead Gen Blueprint?Download our free guide on how to use AI to find, score, and convert high-intent leads across every organic channel. Get it at www.gtmaipodcast.com🎙️ GTM AI Podcast Subscribe for weekly episodes on AI-powered go-to-market strategy.#AILeadGeneration #LinkedInOutreach #GTMAIPodcast #SalesAI #Gojiberry #B2BMarketing #ColdOutreach #AIForSales

www.gtmaipodcast.com www.gtmaiacademy.com Find Victor on LI: https://www.linkedin.com/in/victoradefuye/ Newsletter: https://superintelligentsales.beehiiv.com/ Victor website: www.dana-consulting.com Victor Adefuye built 7 Make.com automations FAST. He's not a developer. He used Claude Cowork. In this episode, Victor (former MD at Winning by Design, now running Dana Consulting) walks through 3 live workflows that show what's actually possible when you combine 10+ years of GTM enablement expertise with agentic AI: What you'll see: 🔍 Lead Research & Prioritization at Scale Victor feeds 360 conference leads into Cowork, which spins up parallel sub-agents to research 15 companies simultaneously, scores them against his ICP, and writes personalized nurture emails pulling from his 110-page content library. The prompt? Three sentences. 📞 Mass Call Analysis with MEDDPICC Scoring A custom skill scores 7+ sales calls in parallel using a calibrated 0-2 scoring system. Individual scorecards with timestamps and direct quotes. A synthesis report showing team-wide skill gaps. What used to take days happens while you grab coffee. ⚙️ Building Make.com Automations (Zero Code) Victor gave Cowork a folder of automation ideas he brainstormed over Christmas. It reviewed them, picked the ones it could build, opened Make.com in the browser, and started configuring modules. Call transcript processing, trigger-based prospecting for newly hired CROs... all built through conversation. Key insights discussed: Why enablement professionals are the best-positioned to build AI agents How skills (packaged expertise) make 3-sentence prompts more powerful than 3-paragraph ones Why parallel sub-agents change the math on what's possible at scale The case for monetizing skills as productized consulting IP Why the chat interface might be going away Connect with Victor: 🌐 dana-consulting.com 📧 superintelligentsales.ai (newsletter) 💼 LinkedIn: Victor Adefuye Connect with Coach K: 🌐 gtmaiacademy.com ⏱️ Timestamps: 0:00 - Intro & Victor's background 3:55 - Victor's GTM enablement journey (Winning by Design → Dana Consulting) 7:30 - Live Demo: Lead Research & Prioritization with Cowork 9:23 - What are Skills? Victor's explanation 14:00 - The power of simple prompts with deep context 16:10 - Parallel sub-agents explained 17:06 - Will Cowork replace the chat interface? 20:48 - Live Demo: Mass Call Analysis with MEDDPICC 22:40 - Building a calibrated scoring system (0-2 scale) 27:15 - How sub-agents solve the context window problem 29:07 - Lead research results walkthrough 31:49 - Can skills be monetized? The productized consulting play 35:19 - Email quality self-checking and the Victor voice filter 40:00 - MEDDPICC synthesis report and team-wide gap analysis 43:50 - Live Demo: Building Make.com Automations with Cowork 46:37 - Trigger-based prospecting for newly hired CROs 50:03 - "It's the creativity that matters" 51:20 - Ethan Mollick's "Invite AI to Everything" 53:23 - Where to find Victor

www.gtmaipodcast.com for full AI playbook For Scott's company: https://gtmify.io/ Scott's linkedin: https://www.linkedin.com/in/scottwueschinski/ He built $100M in qualified pipeline in 3 months using partnerships, intent data, and duct-taped automations. Now Scott Walinski (serial entrepreneur, 4x exit founder, co-founder of GTMFI) has productized that playbook with AI. In this episode, Scott demos three live builds: An AI onboarding agent that builds your entire GTM foundation in under 5 minutes. ICP, buyer personas, use cases, competitive positioning, qualifying questions. What agencies charge $5K-10K and take weeks to produce. A specialized agent architecture for outbound. Not one AI writing everything. Separate purpose-built agents for email (onsite intent vs. offsite intent), LinkedIn, SMS, WhatsApp, and even handwritten mail. All orchestrated from a single platform so you don't need to be a GTM engineer or manage 30 tools. A meeting follow-up automation that drafts your emails before your next call starts. Circle Back captures the transcript, n8n routes it, Anthropic extracts action items, and a draft email appears in Slack for you to approve or edit. No more 6 PM email scrambles. Scott's thesis: The modern GTM flywheel is content + intent + outbound, all running on a foundational AI layer. Most teams have the pieces but no orchestration. This episode shows you exactly how to build it. Scott Walinski is a serial entrepreneur who has grown, scaled, and exited four businesses. He's currently co-founder of GTMFI (gtmi.io) and part of the retail advisory group at Genpact. He's also an instructor in the AI Go-To-Market School at Pavilion. CHAPTERS: 00:00 - Intro and Scott's Background 02:00 - From $100M Pipeline to GTMFI 05:00 - The Modern GTM Flywheel: Content + Intent + Outbound 07:30 - Why GTM Tools Fail Non-Technical Users 10:00 - LIVE DEMO: AI-Powered Onboarding Agent 16:00 - Building Buyer Personas and Use Cases with AI 20:00 - From Onboarding to Campaign: The Full Workflow 24:00 - LIVE DEMO: Campaign Builder and Specialized Outbound Agents 28:00 - Intent-Driven Content Generation with Purpose-Built Agents 31:00 - LIVE DEMO: Automated Meeting Follow-Up (Circle Back + n8n + Slack) 35:00 - Wrap-Up and Where to Find Scott #GTM #AI #GoToMarket #B2B #SalesAutomation #AIAgents #Outbound #Pipeline #GTMAIAcademy #MarketingAutomation #SalesTech

www.gtmaipodcast.com www.gtmaiacademy.com www.thrivestack.ai Guru Linkedin: https://www.linkedin.com/in/gururajp/ For the goodies, the Newsletter breakdown, and playbook go to www.gtmaipodcast.com A bootstrapped founder replaced his AI SDR budget with a $3.5K newsletter engine. The ROI: 551%. In this episode, Guru Raj (Founder & CEO of ThriveStack.AI) breaks down the exact content-to-pipeline system that gets buyers 80% of the way to purchase before a single demo call. Guru built two VC-backed startups before this. Both acquired. Both burned 60-65% of all spend on GTM. His third company is fully bootstrapped, and the GTM engine he built should make every funded startup nervous. We cover: Why AI SDRs from Artisan, 11X, and Instantly failed (and what replaced them) The 5-stage warm pipeline engine that turns newsletter readers into paying customers How to unify marketing, product, sales, billing, and CS signals into one correlation chain The churn intervention tipping point (and the exact month it hits) Building product with a lean AI team using Claude Code and Google AI Studio The $800K analytics tax most B2B SaaS companies are paying for tools that don't talk to each other Key metrics from the episode: 551% ROI on $3.5K email spend 90% open rate on warm outbound 15-20% click rate 80% sign up without needing a demo 23-26% churn reduction from right-timed interventions 30-40% team size reduction using AI 📩 Get the free Content-to-Pipeline Playbook in our newsletter: www.gtmaipodcast.com 🔗 ThriveStack.AI: https://thrivestack.ai ⏱️ Timestamps: 00:00 - Intro 02:15 - Why Guru's first two startups burned 60-65% on GTM 05:30 - The AI SDR experiment that failed 09:45 - Building the $3.5K newsletter engine 15:20 - The 5-stage warm pipeline system 22:00 - Signal unification: connecting newsletter clicks to closed revenue 28:30 - The churn intervention playbook and tipping point 34:00 - Lean AI tech stack: Claude Code, Google AI Studio, Brevo 38:15 - Implementation sequence and key takeaways 🎙️ GTM AI Podcast The podcast for GTM leaders who want executable intelligence on AI in go-to-market. No hype. No fluff. Just the systems, metrics, and playbooks that actually work. Subscribe for weekly episodes. #GTMAI #B2BSaaS #RevenueOperations #ContentMarketing #AIinGTM #SaaS #StartupGrowth #ProductLedGrowth #EmailMarketing #ChurnReduction

Sendoso fired 73% of their BDR team. Pipeline DOUBLED. Here's exactly how they did it. In this episode of the GTM AI Podcast, I'm joined by not one, not two, but THREE members of the Sendoso leadership team — Kris Rudeegraap (CEO), Austin Sandmeyer, and the man they call the Secret Weapon, Egan Callahan — to break down how they rebuilt their entire GTM motion from the ground up using AI agents and internal data. This isn't theory. This is a live walkthrough of the actual systems, the N8N workflows, the Anthropic Agent Harness architecture, and the exact 6-month transformation timeline that took them from 15+ BDRs generating less than 15% of pipeline to 4 BDRs generating 30%+ — and still climbing. 🔑 WHAT YOU'LL LEARN: → Why external signals (job changes, funding rounds) are now TABLE STAKES — and what actually wins → The Internal Data Advantage Framework: Snowflake + Salesforce = your moat → The Anthropic Agent Harness: 5 architecture patterns separating production agents from expensive demos → 3 fully deployed AI agents: Contract Scraper, Deep Research Engine, AI Proposal Generator → The Build vs. Buy Decision Tree for GTM AI infrastructure → How one BDR used AI to find a prospect's dog's name (Butch) — and closed the deal ⏱️ TIMESTAMPS: 00:00 - Intro & Guests 02:30 - How Sendoso transformed their BDR team with AI 10:15 - The Internal Data Advantage (why your CRM is your competitive moat) 22:00 - Egan's Agent Harness Framework (live N8N walkthrough) 35:00 - Agent #1: Contract Scraper (45 min saved per renewal) 47:00 - Agent #2: Deep Research Engine (vector store + hybrid retrieval) 58:00 - Agent #3: AI Proposal Generator (live demo) 1:08:00 - Build vs. Buy Rubric + 30-Day Roadmap 1:18:00 - The future of the BDR role in an AI-native GTM org 📥 FREE RESOURCES (2 Playbooks from this episode): 🔹 The Internal Data Playbook → Comment "Sendoso" on our LinkedIn post 🔹 The GTM AI Agent Guide → Comment "Sendoso" on our LinkedIn post 🔗 Connect with the guests: → Kris Rudeegraap (CEO, Sendoso): linkedin.com/in/rudeegraap → Austin Sandmeyer: linkedin.com/in/austinsandmeyer → Egan Callahan: linkedin.com/in/egancallahan 🎙️ GTM AI Podcast | Hosted by Jonathan Kvarfordt (Coach K) and Jonathan Moss → Website: gtmaipodcast.com → Subscribe for weekly episodes on AI-native GTM strategy #GTMAI #SalesAI #AIAgents #BDR #GTMStrategy #Sendoso #SalesAutomation #RevenueAI #AIOutbound #SalesOps #AgentHarness #Anthropic

www.gtmaipodcast.com www.gtmaiacademy.com For SaaStr: https://www.saastrannual.com and get a coupon code talking to Amelia AI! or use the code: February26 before March 1 (or Amelia AI after March 1) For Amelia linkedin: https://www.linkedin.com/in/amelialerutte/ Amelia LaRute went from running SaaStr's demand gen and events to becoming their Chief AI Officer. In 8 months, she deployed 20+ AI agents across sales, marketing, events, and support, generating $5M in additional pipeline and closing $2.4M of it. SaaStr now operates with 3 humans, 1 dog, and an army of agents. In this episode, Amelia breaks down: Her full AI SDR stack and how she splits leads between AgentForce and Artisan based on where the data lives The exact Zapier workflow that connects form fills to Clay enrichment, Salesforce campaigns, Gamma presentations, and automated follow-up Why SaaStr's deal volume AND win rate both doubled (and the specific reason agents make sales calls more productive) The 90/10 rule for deciding when to buy an agent vs. vibe-code your own on Replit How she manages 20+ agents without losing her mind (spoiler: it's still messy) Live demo: vibe-coding a sponsor portal from Claude to Replit in real time Why "Amelia AI" and "Digital Jason" serve different purposes and how role-splitting your AI clones works The honest reality of being a 3-person team running a 10,000-person conference Whether you're deploying your first AI SDR or managing a multi-agent stack, Amelia's playbook is one of the most practical, real-world implementations we've featured on the show. 🎙️ Guest: Amelia LaRute | Chief AI Officer, SaaStr 🏆 GTM AI 25 Award Winner (Ones to Watch) ⏱️ Timestamps: 00:00 - Intro & Amelia's background 03:00 - From SVP to Chief AI Officer: the journey 06:45 - Overview of SaaStr's 20+ AI agents 08:00 - The AI SDR stack: AgentForce vs. Artisan 14:00 - How to think about splitting leads across agents 16:00 - The Zapier workflow connecting all agents 19:00 - Managing multiple agents day-to-day 23:00 - Results: $5M pipeline, 2.4M closed, doubled win rate 25:00 - Inbound agents: Qualified and Amelia AI 30:00 - Momentum.io for real-time sales intelligence in Slack 36:00 - Live demo: vibe-coding a sponsor portal 40:00 - The 90/10 rule: buy vs. build 46:00 - SaaStr Annual 2025: what's new 52:00 - What keeps Amelia going 🔗 Links & Resources: → SaaStr: https://www.saastr.com → SaaStr Annual (May 2025): https://saastrannual.com → GTM AI Podcast: https://gtmaipodcast.com → GTM AI Academy: https://gtmaiacademy.com → AI Business Network: https://aibusinessnetwork.ai Tools mentioned: Salesforce AgentForce, Artisan, Qualified, Clay, Zapier, Gamma, Replit, Delphi, Claude, Momentum #GTMAI #AIAgents #SaaStr #RevOps #SalesAI #AIinSales #GTMStrategy #AISales #VibeCoding #B2BSaaS

GTM AI Podcast: www.gtmaipodcast.com GTM AI Academy: www.gtmaiacademy.com AI Business Network: www.aibusinessnetwork.ai Steve Cunningham / Humans Plus Agents: https://humansplusagents.ai/ Steve on LinkedIn: https://www.linkedin.com/in/aisteve/ Steve Cunningham built a 10-year business around being the best in the world at summarizing business books. Then AI did it in 5 minutes. Instead of fighting it, he burned it down and rebuilt. Now he runs an AI agent operation inside Claude Cowork where 30 minutes of his time replaces 70 man-hours and $14,000 of agency work. In this episode, Steve walks through his exact setup: the folder structure that treats AI like a company, why HTML is replacing every other file format, the invoice method that rewires how you plan, and the overnight improvement loop that makes his system better while he sleeps. Plus, Steve is offering GTM AI Academy listeners access to his Black Belt AI Workflow Engineering training. Link in the show notes. 🔗 LINKS & RESOURCES GTM AI Podcast: www.gtmaipodcast.com GTM AI Academy: www.gtmaiacademy.com AI Business Network: www.aibusinessnetwork.ai Steve Cunningham / Humans Plus Agents: https://humansplusagents.ai/ Steve on LinkedIn: https://www.linkedin.com/in/aisteve/ 📌 TIMESTAMPS 0:00 - Intro and Steve's background 5:18 - How AI killed his dream job 8:57 - Simple Academy to Humans Plus Agents 10:11 - Claude Cowork setup and demo 14:03 - The org chart mental model for AI 15:34 - Why HTML beats Markdown and Office docs 22:43 - Folder structure walkthrough (advisors, agents, context, projects) 25:09 - The $14,000 in 30 minutes demo 27:04 - Treating every day like a quarter 28:11 - The continuous improvement loop 33:02 - What is actually NEW vs. just faster 34:15 - Distribution, deployment, and data framework 36:52 - Black Belt training offer 39:53 - The Bezos question: what will NOT change

www.gtmaipodcast.com www.gtmaiacademy.com www.aibusinessnetwork.ai For more From our Guest Scott Ewalt: https://www.cardinalelement.com/ Or his Linkedin: https://www.linkedin.com/in/scottewalt/ Most competitive intel sits on shelves collecting dust while your competitors ship faster. Your team spends weeks building battle cards. By the time they reach your reps, your competitor has shifted messaging. You find out three deals later when someone mentions it in a loss review. Your head of sales asks why competitive enablement is always behind. You don’t have a good answer. Scott Ewalt just demonstrated building a competitive intelligence engine from scratch in 4 hours. Zero Python experience. No developer hire. Just Claude Code and a clear outcome: turn scattered competitive signals into queryable intelligence. The result: 91 podcast episodes transcribed, where he uses our own podcast as the source, stored in a vector database, with a custom web UI that surfaces strategic insights competitors broadcast publicly but you’ve never synthesized. Guest: Scott Ewalt - Former product, marketing, and CX operator who’s spent his career finding “unfair advantages” through technology. Not a developer. Never wrote production code. Didn’t open a terminal before Q4 2025. The Demo: Building a competitive intelligence system that: Transcribes and stores 91 podcast episodes (81.2 hours of content) Creates a queryable vector database with zero hallucinations Builds a custom web interface for team queries Returns specific quotes with episode citations and timestamps

www.gtmaipodcast.com www.gtmaiacademy.com www.aibusinessnetwork.ai www.mindstudio.ai 5 AI Workflows MindStudio's GTM Leader Runs Daily to 3x Pipeline Most partnership and sales teams spend 60% of their week on research, prep, and administrative friction. The top 5% automated all of it. In this episode, I sit down with Dannielle Sakher, VP of GoToMarket at MindStudio.ai, who walks through the exact AI agent workflows she uses to close enterprise partnerships and deals. Not theory. Pure execution. These are the agents running behind the scenes at one of the fastest-moving AI platforms right now. What You'll Learn: LinkedIn Connection Crafter (4:22) - How to send 200+ personalized LinkedIn requests per week without sounding like a bot Rewrite Pitch Agent (14:09) - Pull live prospect research in real-time and transform generic pitches into targeted outreach Cheat Sheet Generator (22:17) - Collapse 3 hours of meeting prep into 2 minutes of automated research Contract Analyzer (31:19) - Flag high-risk contract terms without legal bottlenecks and move deals faster Launch Teaser Creator (37:11) - Make partnerships tangible before they exist with automated mock press releases The Big Insight: Dannielle isn't automating busywork. She's automating the high-value activities that made her successful in the first place. Personalized research, deep prep, creative pitch assets. Most people stop doing these when they get promoted because there's "no time." She built agents to do them at scale. Try All 5 Agents (Free) on the newsletter at www.gtmaipodcast.com Resources: → Sign up for MindStudio: https://www.mindstudio.ai/ → Join AI Agent Academy Bootcamp: https://mindstudio-academy.circle.so/ai-agent-academy Connect with Dannielle Sakher: → LinkedIn: https://www.linkedin.com/in/danniellesakher/ About GTM AI Academy: GTM AI Academy is where go-to-market leaders learn to leverage AI for revenue growth. Get actionable workflows, real implementations, and zero fluff. Timestamps: 0:00 - Intro 2:45 - Dannielle's background and why MindStudio 6:12 - LinkedIn Connection Crafter demo 14:09 - Rewrite Pitch agent walkthrough 22:17 - Cheat Sheet Generator for meeting prep 31:19 - Contract Analyzer demo 37:11 - Launch Teaser creator 47:09 - Building agents with natural language 52:30 - Wrap up and key takeaways

🎙️ www.gtmaipodcast.com 🎓 www.gtmaiacademy.com 🤖 www.aibusinessnetwork.ai The 5-Part Prompt Framework That Saves GTM Teams 15+ Hours Weekly Most GTM teams are still building complex workflows in Zapier when they could just describe what they want and let AI execute it. In this session, we demonstrate the shift from workflow builder to workflow director. The 5-part prompting framework (Objective, Constraints, Inputs, Output, Evaluation) that turns hours of technical setup into minutes of natural language. We show live examples: Data analysis: 6 hours → 5 minutes Competitive research + deliverables: 18 minutes end-to-end Interactive dashboards with zero coding The constraint isn't technical capability anymore. It's knowing what's possible. What workflow are you building manually that you could just describe instead? Drop it in the comments. #GTM #AIAutomation #RevOps #WorkflowAutomation Kept it under 200 words, action-focused, with clear value proposition.

GTM AI Podcast www.gtmaipodcast.com Guest: Justin Parnell (JustinGPT) 📬 Full breakdown + resources: www.gtmaipodcast.comJustin's site: https://www.justingpt.ai/ | YouTube: https://www.youtube.com/channel/UCov4kN0lK2A6O95ykql7cnQ Justin Parnell breaks down how to transform static PDFs into AI-powered, personalized lead magnets that adapt to each prospect's specific needs—automatically. Instead of sending everyone the same generic deck, his automation reads form submissions and generates custom branded proposals using Claude Opus 4.5, Gamma, and Make.com. The whole thing runs in under 60 seconds, costs about 20 cents per prospect, and his clients are seeing 30% increases in MQL-to-SQL conversion rates. As Justin puts it: "Who wouldn't spend 20 cents to send an MQL a customized piece of content and enhance those conversion rates?" The magic is in Claude's "Skills"—custom instruction sets you create once that Claude follows perfectly every time, eliminating the need for prompt engineering on each run. The conversation got really interesting when we discussed agent-to-agent GTM. Justin predicts that within 18-24 months, buyers will deploy AI agents to evaluate vendors and compare proposals without human involvement until final decision time. His philosophy: "Create agents that do specific things and chunk those things out. Don't try to build one massive agent—build focused micro-agents that do one job exceptionally well, then chain them together." This isn't some crazy complex automation—it's six workflow steps doing one thing exceptionally well: making prospects feel understood before they ever talk to sales. Beyond lead magnets, this same framework works for post-demo follow-ups, competitive battle cards, role-specific buying committee decks, event recaps, and sales proposals. Get the full technical breakdown, Make.com blueprint, and all five use case playbooks at www.gtmaipodcast.com

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

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.

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.”

www.gtmaiacademy.com www.gtmaipodcast.com www.aibusinessnetwork.ai www.revic.ai Connect with Hussain: https://www.linkedin.com/in/halshorafa/ Hussain Al Shorafa’s team walked into a customer engagement that should have gone sideways. The company had a sophisticated rev ops function. They’d invested in Six Sense, Demandbase, ZoomInfo, or the full modern GTM stack. They had smart people running the operation. Revic’s assessment: 62% of the accounts this team was actively pursuing sat outside their actual ICP. The customer’s response was predictable. They told Hussain to pound sand. His company was eighteen months old. Theirs had been running this motion for years with serious investment in data infrastructure. Who was this startup to tell them their targeting was broken? Five months of friction followed. Revic kept showing evidence. The customer kept pushing back. Then something shifted. The CRO was at dinner when an email came through, which was another lost deal. Hussain pulled up the platform. Revic had flagged that account from the beginning. The system’s assessment: this deal never had a real chance. The signals weren’t there. The fit wasn’t there. The CRO asked the obvious question: where else is this true? The answer: $40 million in active pipeline. Hussain Al Shorafa started on the technical side before making a hard pivot into sales. The catalyst was a Lakers-Trailblazers playoff game in 2000, Game 7, Kobe to Shaq for the alley-oop dunk. The sales guy who gave him the tickets had a lifestyle Hussain wanted. He decided to chase it. What followed was fifteen-plus years progressing from individual contributor through sales leadership across public and private companies. He built teams. He hit numbers. He also watched the same dysfunction repeat everywhere he went. Sales would bring market signal back to the organization. The organization would push back. Internal friction would make an already difficult job harder. The people closest to the customer would catch heat from functions that had less direct exposure to what buyers actually said and did. Revic.ai came out of that frustration. The thesis: sales organizations generate enormous amounts of knowledge through customer interactions, but that knowledge evaporates constantly. Reps leave. Context disappears. The next person starts from scratch. What if you could capture that institutional memory and make it usable? Every sales organization has two real assets: the people and what those people know. The people churn. Industry average says you’re looking at a nearly net-new sales organization every three years. That’s not a bug in the system, it’s the actual system. Reps get promoted, poached, burned out, or restructured. They leave. When they leave, they take something with them that never gets captured in Salesforce notes or call recordings: context. The understanding of why deals worked. The pattern recognition that told them which accounts were real and which were theater. The instinct for which message landed with which persona and why. Hussain made a point that stuck with me: the most valuable information he ever received as a rep came from peers. Not enablement decks. Not marketing messaging guides. Other reps telling him how they won, why they lost, what competitors showed up, what objections hit hardest. That peer knowledge was gold.

www.gtmaiacademy.com www.aibusinessnetwork.ai www.yoodli.ai Connect with Varun: https://www.linkedin.com/in/varun-puri001/ Why Communication Is THE New Competitive Advantage for GTM Varun Puri, CEO of Yoodli, explains why AI role plays aren't just a feature—they're the future of how sales teams practice and win. From his days running special projects at Google under Sergey Brin to building a platform used by Fortune 50 companies, Varun shares what most AI misses about communication, why information commoditization changes everything, and why the best sales coaches are partnering with (not competing against) AI. If you're in GTM, enablement, or sales leadership, this is essential. TIMESTAMPS: 00:00 — Intro 00:30 — Varun's Journey: Google to Yoodli 02:00 — The Real Problem: Access Inequality in Communication Training 05:00 — What Is Yoodli? (Beyond the Hype) 06:00 — Why 90% of AI Role Plays Miss the Point 09:00 — The Technology Stack: Why It's Not Just a GPT Wrapper 11:00 — Enterprise Differentiation & Verticalization 14:00 — The Future of Learning: AI Tutors + Dynamic Coaching 16:00 — Augment, Don't Replace: The Philosophy Behind Yoodli 18:00 — How AI Amplifies Humans (Not Replaces Them) 20:00 — What Varun Actually Uses AI For 21:00 — His Real Conviction: Information Is Becoming Free 24:00 — Why Communication Skills Are the Last Moat 25:00 — The Deeper Problem: Behavior Change Over Tech KEY QUOTES: "Two out of three people struggle with communication confidence." "You can use Excel, but there's a reason you use a CRM." "When information becomes a commodity, the only thing that separates top performers is how they show up. More on AI + GTM: Intelligence Architecture Framework Why AI Role Plays Aren't Going Away The Future of Sales Enablement

www.gtmaiacademy.com www.aibusinessnetwork.ai www.evergrowth.io https://www.linkedin.com/in/jbdaguene/ In this episode of the GTM AI Podcast, host Jonathan Kvarfordt (Coach K) sits down with JB Degune, CEO and founder of Evergrowth. They discuss JB's journey into the SaaS business world, starting with his success at Trustpilot and leading up to the founding of Evergrowth. JB shares how Evergrowth leverages AI agents to enhance sales processes, making them more customer-centric. Listen in to learn about the challenges and breakthroughs in integrating AI into sales, the importance of having a clear value proposition, and how AI can significantly boost productivity and efficiency in GTM teams. Explore real-world use cases, compare Evergrowth’s solutions to other tools like Clay, and get insights into the future of AI in the sales industry. 00:00 Introduction and Guest Welcome 01:02 JB's Journey into SaaS and Trustpilot 02:56 Founding Evergrowth and Early Challenges 04:11 The Impact of AI on Lead Research 05:05 Evergrowth's GTM Strategy and AI Agents 16:57 Real-World Use Cases and Success Stories 22:05 Future of Sales with AI and Buyer Agents 25:05 Conclusion and Farewell

www.gtmaiacademy.com www.aibusinessnetwork.ai www.chilipiper.com Connect with Alina: https://www.linkedin.com/in/alinav/ In this conversation with Coach K, Alina—Co-CEO of Chili Piper—reveals the uncomfortable truth about AI that nobody's talking about: it won't replace your job, but it WILL force you to completely reinvent yourself. She walks through her journey from communist Romania with a "CEO or bust" mentality, to a devastating realization that she couldn't save everyone, to now leading a company navigating the biggest technological shift of our lifetime. But here's the thing—she's not afraid anymore. And she explains exactly why you shouldn't be either. WHAT YOU'LL LEARN: How Alina went from paralyzed confusion about AI replacing her employees to genuinely excited about what's possible. She breaks down the one thing most companies get wrong when building AI infrastructure (hint: it's not about the tools—it's about alignment). You'll hear the behind-the-scenes story of how Chili Piper unified their data across sales, marketing, and customer success into Snowflake, then used it to answer questions like "Why do buyers actually switch to us?" and "What messages actually move deals?" The answer? It took locking their team in a room and forcing executives to leave their egos at the door. Then she shares the framework for automating soul-crushing tasks without destroying your team—and why the future of GTM is actually MORE human, not less. THE MINDSET SHIFT: The biggest insight isn't about technology. It's this: AI amplifies what makes YOU unique. It can't replace you. It can augment you. And everyone who's terrified right now is missing the most important opportunity of their career. "We're all phoenixes in the ashes right now," Alina says. This is the conversation about what that actually means—and what you need to do about it. PERFECT FOR: GTM leaders, founders, SDRs, marketers, anyone feeling overwhelmed by AI and wondering where to actually start.

www.gtmaiacademy.com www.aibusinessnetwork.ai Connect with Hector: https://www.linkedin.com/in/hectorforwood/ In this episode, Jonathan Kvarfordt interviews Hector Forwood, CEO of Flooencer, about the explosive growth and chaotic pricing dynamics in B2B influencer marketing. Hector shares insider data from over 1,000 sponsored campaigns, revealing a 37% price increase in just 12 months and the "shockingly bad" CPM metrics that brands are willing to pay. The conversation explores the delicate balance between AI-powered content creation and authentic human storytelling, the death of traditional outbound marketing, and Hector's contrarian view that AI has already delivered 80% of its dramatic improvements. With insights from building companies from scratch using no-code tools and predictions about the future of SaaS pricing, this episode provides actionable frameworks for GTM leaders navigating the intersection of AI and human creativity.

www.gtmaiacademy.com www.aibusinessnetwork.ai Connect with Navin: https://www.linkedin.com/in/navinpersaud/ www.1password.com AI in Rev Ops: Insights from Navin Persaud, VP at 1Password - GTM AI Podcast In this episode of the GTM AI Podcast, host Jonathan Kvarfordt, aka Coach K, sits down with Navin Persaud, the VP of Rev Ops at 1Password. Navin shares his career journey from aspiring lawyer to tech enthusiast, his experiences at IBM, and his role in revolutionizing revenue operations at 1Password. The discussion delves into how AI is used in rev ops, the importance of defining problems before implementing AI solutions, and the criteria for selecting AI tech in a security-conscious environment. Navin also highlights the unmatched value of momentum in enhancing sales processes, offering product feedback, and improving sales coaching. This episode is packed with insights for anyone in rev ops, sales, and AI implementation. 00:00 Introduction and Guest Welcome 00:40 Navin Persaud's Career Journey 02:11 AI in Rev Ops: Opportunities and Challenges 04:46 The Importance of Empathy in Rev Ops 06:02 AI Implementation Strategies 09:13 Security Concerns with AI 12:36 Future of AI in Rev Ops 20:28 Momentum's Impact on Rev Ops 27:44 Closing Remarks and Appreciation

www.gtmaiacademy.com www.aibusinessnetwork.ai https://www.surepeople.com/ Russell-> https://www.linkedin.com/in/russell-mikowski-a349903/ GTM AI Podcast Episode: Russell Mikowski on AI-Powered Psychometrics and the Human Advantage In this episode, Jonathan Kvarfordt interviews Russell Mikowski, CEO of SurePeople, about revolutionizing workplace psychometrics through AI integration. Russell shares his unconventional journey from DJ and poker player to CEO, and reveals why personality-driven collaboration becomes MORE critical as AI automates routine tasks. The conversation explores how organizations can optimize human interactions, the "desk drawer problem" with traditional assessments, and the future of AI agents that understand personality psychology. Russell explains how traditional psychometric assessments fail to deliver ongoing value. Key Quote: "The results of those assessments are often metaphorically stuffed into our desk drawers, sometimes literally in Manila folders and kind of die there. Right? So sure people is looking to completely disrupt the traditional psychometric world by democratizing access to psychometrics across organizations." Discussion of SurePeople's approach to personality measurement and real-time application. Key Quote: "Prism is the most accurate psychometric on the market today. So we're comfortable that our tool is the appropriate vehicle for powering interactions that matter in moments that matter on platforms that you already use." Russell explains how personality insights drive tangible business outcomes. Key Quote: "Should they be leading with the why? Because the group leans towards Big picture thinking... Or should they get straight to the details and the data? Because this group doesn't care at all about how your kids are, or even why the company has made this decision." Key Quote: "Culture begets performance right. If people feel seen, heard, and understood, they're less likely to be flight risks, they're less likely to be quiet quitting, they're less likely to be negatively impacted by a slack message that they took the wrong way." Exploring how personality data could enhance AI communications and reduce "robot speak." Key Quote: "What if your personality, as determined by a psychometric, could be essentially fed into an agent to make the language that it uses sound more like you. And then there would be consistency, perhaps, between that initial automated outreach, and how you actually act when you get on a demo with someone." Russell's core thesis on why human interactions become more valuable, not less, as AI advances. Key Quote: "The expected output, and you know, in a related manner, the value of each human individual on teams is rising right?... So the optimization of the interaction, the communication, the collaboration between more valuable than ever human resources." Key Quote: "As a big picture thinker... I'm bad with details. I'm horrible with lists... But where AI can stay on top of those for me make reminders and keep me informed... That's freeing up my time to think creatively about what the next great product might be." Russell shares surprising findings about who adopts AI-powered personality tools. Key Quote: "A pattern is starting to form that would show people who have more what we would call precise personality types. So those are like your architects, your scientists, your research... are more likely to use our tools more often." Information on accessing the PRISM assessment and company contact details. Key Quote: "Any company that wants to deploy the assessment between 50 and a thousand employees just simply schedule a demo via our site, and we'll give you the option to roll it out for free forever to all of your employees."

www.gtmaipodcast.com www.aibusinessnetwork.ai www.gtmaiacademy.com For Harald go to : https://go.buroventures.com/ or Linkedin: https://www.linkedin.com/in/haraldroine/ The Genesis of a Marketing Innovator Harald's journey into the world of digital marketing began at the age of 11. Motivated by a passion for video games and a push from his father to develop productive skills, he taught himself to program and create websites. By 16, his interests had expanded to Bitcoin and digital innovation. Over the years, he has cultivated vast expertise in digital marketing, focusing on value-based approaches and technological advancements. Traditional marketing often hinges on showcasing product features or benefits. Harald, however, advocates for a "value-first" approach. This strategy focuses on offering genuine value to the audience before making any pitches. The idea is simple yet impactful—by providing valuable insights or resources, businesses build trust and reciprocity, which naturally encourages audiences to engage further. Harald envisions AI as a revolutionary tool in marketing, capable of automating numerous functions and processes. He outlines a future where AI will not just assist but transform how businesses interact with their audiences. The ability for AI to understand complex input-output processes within a company and mimic human strategic and creative tasks marks a significant shift. This perspective aligns with the belief that AI will soon facilitate AI-to-AI interactions, streamlining operations like marketing and customer relations. A key takeaway from the discussion was the application of AI in generating leads and engaging customers. Bureau Ventures leverages AI to automate content creation, enabling more efficient and effective marketing strategies. AI-driven systems can analyze a business's offerings, identify audience pain points, and produce content that resonates with potential customers. As a result, businesses can focus more on strategic growth and less on manual content development. With AI poised to redefine the landscape of business operations, Harald emphasizes the importance of building owned media channels that businesses control entirely. This strategy will help companies build digital real estate that withstand external changes, ensuring sustainable outreach and engagement. He also touches on AI’s potential to revolutionize client success systems through automated satisfaction and performance measures, enhancing customer experiences and outcomes. If you want to create a system that gathers hundreds of leads that come to you, Harald is the man to talk to. More details about Bureau Ventures and their innovative approaches can be explored through their website. As AI continues to evolve, the strategies shared by Harald offer a compelling direction for marketers seeking to stay ahead of the curve.

www.gtmaiacademy.com www.aibusinessnetwork.ai https://www.linkedin.com/in/sanderssays/ GTMAI PodcastJoin Jonathan Kvarfordt as he hosts Tim Sanders, the VP of Research Insights at G2, on the G-T-M-A-I podcast. Tim shares his personal journey, passion for AI and music, and insights from his career, including working with Mark Cuban at AudioNet and Yahoo. The discussion explores the transformative power of AI in marketing, differences between traditional search engines and AI-driven answer engines, and the importance of generative engine optimization. Tim also delves into the concept of trust in AI, the future of marketing strategies, and how businesses can leverage AI to enhance effectiveness and velocity. This episode is packed with valuable takeaways for marketers, sales leaders, and AI enthusiasts. 00:00 Introduction and Guest Welcome 00:31 Tim Sanders' Background and Passions 01:27 Career Highlights and Key Experiences 02:45 Analog Synthesizers and Music Passion 03:47 AI in Marketing and Sales08:14 Trust and Adoption of AI15:03 Generative AI and SEO Strategies 30:18 Closing Remarks and Contact Information

www.gtmaipodcast.com www.aibusinessnetwork.ai https://deephumanx.com/ Navigating the AI Revolution: Insights from Chad Sanderson of Deep Human X In this episode, Jonathan sits down with Chad Sanderson, co-founder of Deep Human X, to discuss the rapid advancements and applications of AI in the business world. Chad shares his journey from marketing and sales to digital and revenue operations transformations, and his deep dive into AI enablement. They delve into the importance of balancing human and AI collaboration, the impact of AI on critical thinking, and the need for businesses to adapt quickly to stay competitive. The conversation highlights key strategies for leaders and organizations to effectively integrate AI, along with the significance of fostering a community and mindset focused on innovation and agility. 00:00 Introduction and Guest Welcome 00:52 Guest Background and Career Journey 01:08 AI and Digital Transformation 03:31 Human-AI Balance and Critical Thinking 09:06 Tools and Techniques for AI Augmentation 13:19 Transformational Mindset Shift 14:48 Breaking Assumptions in Workshops 15:22 Leadership Conversations on AI and Operationalization 15:36 Physical Reactions and Realization Journey 16:38 Leaders' Initial Thoughts on AI and Productivity 17:18 Recent Layoffs and AI's Role 18:20 Speed of AI Revolution 20:09 Adoption Rates and Quantum Computing 21:21 Preparing Teams for AI 23:15 Finding Community and Overcoming Fear 25:28 Services Offered by the Agency 27:23 Final Thoughts and Appreciation

www.gtmaipodcast.com www.gtmaiacademy.com www.aibusinessnetwork.ai www.letter.ai Nate: https://www.linkedin.com/in/nate-varel/ Exploring AI-Powered Revenue Enablement with Nate Varel of Letter.ai – GTM AI Podcast In this episode of the GTM AI Podcast, hosted by Jonathan Kvarfordt (Coach K), we are joined by Nate Varel, the head of GTM at Letter.ai. Nate shares insights from his extensive career, including his experiences at Perro AI and Options Clearing Corporation. The discussion delves into the transformative impact of AI-native platforms in revenue enablement, the evolving role of sales and enablement professionals, and how AI can drive better customer experiences. Tune in for a thought-provoking conversation on the future of sales, AI in tech, and the seamless integration of AI with sales processes. 00:00 Introduction and Guest Welcome 00:31 Nate Varel's Career Journey 02:07 Transition to Tech and Algorithmic Trading 05:09 Joining Letter.ai and Role Overview 06:38 The Future of Revenue Enablement 10:57 AI's Role in Sales and Enablement 15:59 Discussing Competitors and AI Integration 16:18 Advantages of AI-Native Platforms 17:17 Legacy Platforms vs. AI-Native Platforms 18:19 The Future of AI in Sales Enablement 19:13 AI's Role in Sales and Enablement 21:20 The Shift in Sales Enablement 25:52 The Role of AI Agents 28:51 Evaluating Tech Stacks and AI Integration 30:36 Conclusion and Final Thoughts

https://www.gtmaiacademy.com https://www.aibusinessnetwork.ai https://www.gtmaipodcast.com https://www.linkedin.com/in/mattpaige/ I discovered Matt Paige when he had just 200-300 TikTok followers, and I've been following his AI journey ever since. Now he's VP of Strategy & Marketing at HatchWorks AI, and honestly, this conversation blew my mind with how practical and real his approach is to AI implementation. This isn't another "AI will change everything" conversation. Matt gets into the nitty-gritty of what's actually working for businesses right now. On the reality of AI adoption: "AI is easy to do. But it's hard to do well, right? It's easy for anybody to go talk to ChatGPT, write an email, do this, do that. But to actually build a system within your business, integrate with your business, start leveraging agents, automating things, entire job functions - that's not as easy to do." On the brutal truth about jobs: "Sometimes we tell ourselves AI won't take jobs because it sounds safe and nice. I think it is gonna take jobs. But I think it will open and create new things we never thought of before." On the democratization of building: "You could build for an audience of one being yourself. And it's okay, because it takes you an hour. This changes this whole shift in how we think about SaaS builders." The Tools Matt Actually Uses: His complete AI development stack (Lovable, Bolt, Cursor) Voice agents that handle "bland tasks" with decision trees, not rigid scripts Browser automation tools that can literally buy toilet paper on Amazon Open source alternatives to expensive AI platforms Real Implementation Stories: How he built a closet-sharing tracker for his wife in 2 days Custom ChatGPT doing K-means clustering on Airbnb data for market segmentation Why the old data request process (submit ticket, wait a week, get partial answer) is dead The Battle Between Incumbents and Startups: Matt breaks down why companies like Salesforce are struggling with their AI pivot while new entrants are building AI-native from day one. But here's the kicker - incumbents have massive proprietary data that startups can't touch. His Final Advice: "Go start playing with stuff on a daily basis. Habits build over time. Put yourself on the front end of that transformation so you have choices." Matt isn't selling you on AI dreams - he's showing you the actual tools, the real costs, and the honest challenges. He's in the trenches building this stuff for 200+ person organizations, and he shares what works and what doesn't. Plus, you'll hear about the Google Agent White Paper breakdown that explains exactly how to build effective AI agents (LLM + Orchestration + Tools), and why most people are thinking about this wrong. If you're tired of AI hype and want practical, implementable strategies, this conversation delivers. Listen now and let me know what resonates with you most. Connect with Matt Paige on LinkedIn or check out HatchWorks AI to see their approach to AI transformation. And if you found value in this episode, please share it with someone who needs to hear Matt's insights on getting AI implementation right.

https://www.gtmaiacademy.com https://www.aibusinessnetwork.ai https://www.gtmaipodcast.com https://www.linkedin.com/in/lizaadams/ AI, Marketing, & Personal Journeys: A Chat with Marketing Expert Lisa Adams In this episode, I have the pleasure of chatting with Lisa Adams, a seasoned marketing expert with a unique career path and keen insights on AI. We dive into various aspects of marketing, her journey from an electrical engineer to an AI advocate, and the transformative role AI can play in marketing strategies. Join us as we discuss how you can integrate AI tools into your marketing teams and the mindset shifts required for success. Timestamps: 00:00 - Introduction 02:15 - Lisa Adams' Background and Journey 07:00 - Transition from Engineering to Marketing 10:45 - The Importance of Storytelling in Marketing 15:30 - AI as a Thought Partner in Marketing 20:40 - Building AI Assistants in Marketing Teams 24:00 - Customer Behavior and AI Insights 30:00 - Tools and Strategies for AI in Marketing 38:00 - Leveraging AI for Enhanced Productivity 45:45 - Case Study: Transforming a Marketing Team with AI 55:00 - AI Tools and Their Applications 1:05:30 - Final Thoughts and How to Connect with Lisa Adams 00:00 Introduction and Greetings 00:26 Personal Anecdotes and Humor 00:49 Guest's Professional Background 01:14 Journey into AI and Marketing 04:23 AI's Impact on Marketing 06:44 AI Leadership and Organizational Transformation 09:52 AI Assistants and Team Augmentation 13:50 Implementing AI in Teams 14:23 Passion and Purpose in AI 14:50 Understanding Customer Behavior 15:43 AI Tools and Techniques 16:41 Creating Relevant Content 18:22 Hyper-Personalization and Prompting 19:24 Leveraging Customer Data 23:10 Favorite AI Tools 26:46 Interactive AI Applications 27:32 Conclusion and Contact Information

www.aibusinessnetwork.ai www.gtmaipodcast.com www.gtmaiacademy.com https://www.linkedin.com/in/kenbabcock/ https://www.tango.ai/ Ken Babcock, CEO of Tango, reveals how AI is solving sales teams' biggest pain point: administrative work that keeps reps away from selling. With 2M+ users and partnerships with Walmart and Nike, Tango evolved from documentation tool to AI automation platform. The CRM Problem: Sales reps spend 70%+ time on admin instead of customer-facing activities. "No one ever hired a sales rep because of how good they were with the CRM," Babcock notes. Speed 60 Method: Tango's approach compresses post-call work into 15-minute blocks: 45 minutes customer interaction, 10 minutes CRM updates, 5 minutes prep for next call. Trust Through Transparency: Unlike "black box" AI tools, successful automation requires human oversight and real-time visibility into processes. Competitive Advantage: Quick follow-up wins deals. One prospect told Babcock: "I forgot all those vendor conversations. The one that emailed me? I'm going with them." Start AI implementation with specific pain points like CRM updates Maintain human validation to build trust in automated processes Use data to identify low-adoption workflows for automation opportunities Quick response times after prospect meetings create momentum Build learning-oriented culture with regular career development conversations Focus on behaviors, not just values, when establishing company culture Tango's journey shows that successful AI adoption comes from solving real user problems while keeping humans in control of the process. Sales Reps Don't Wake Up Excited About CRM Updates: How AI Is Finally Fixing the Administrative NightmareKey InsightsMain Takeaways

www.gtmaipodcast.com www.aibusinessnetwork.ai www.gtmaiacademy.com Summary Ross Rich, CEO and co-founder of Accord, brings a unique perspective to sales technology after scaling Stripe's sales organization from three to 300 people. In this conversation from GoNimbly's RevFest, Rich reveals how execution excellence goes beyond doing more work to creating clarity, consistency, and reinforcing winning behaviors across the customer journey. The foundation of execution excellence starts with data and knowing exactly who you're talking to. Rich emphasizes that most sales teams fail because they engage with associates and below-the-line people rather than senior stakeholders and decision makers. At Accord, they track both the number of stakeholders and the frequency of engagement as primary indicators of deal health. This focus on stakeholder mapping becomes even more critical as buying committees expand and decisions require broader consensus. AI represents both an opportunity and a threat for sales professionals. The technology can handle transactional SMB deals, pushing human sellers toward more complex mid-market and enterprise opportunities. However, this concentration means top performers who previously closed one or two deals annually might now close three to five, potentially increasing the revenue contribution of the top 20% of sellers from 80% to 90% or more. Those at the bottom who rely on lucky breaks or helpful buyers will find their roles increasingly challenged by technology. The practical application of AI in sales focuses on two key areas. First, deep research that previously required hours of manual work analyzing 10-Ks, financial statements, and stakeholder backgrounds can now happen in seconds. This allows thoughtful sellers to craft more informed outreach and stand out from the noise. Second, AI helps identify and engage the right senior stakeholders with relevant messages. Counterintuitively, Rich finds higher response rates when reaching out to more senior executives because thoughtful, informed messages stand out more in a CEO's inbox than in a mid-level manager's cluttered email. The implementation of AI tools must meet sellers where they already work rather than asking them to become prompt engineers. Rich points out that if revenue operations leaders struggle to get representatives to input data into Salesforce, expecting them to master AI prompting is unrealistic. Instead, AI should be embedded into existing workflows like account research, stakeholder mapping, and business case development. This approach eliminates the need for additional tabs, tools, or manual updates while enhancing the work sellers already do.

www.gtmaipodcast www.aibusinessnetwork.ai www.gtmaiacademy.com https://www.getpeel.ai/ https://www.linkedin.com/in/brannon-santos/ The Genesis Story Brannon Santos brings a unique perspective as a founder - he's not a technologist who stumbled into sales problems, but a seasoned sales leader who deliberately chose entrepreneurship. His background includes choosing his college specifically for its entrepreneurship program and strategically entering sales to understand how businesses operate from the inside out. This sales-first DNA permeates Peel's entire approach. The conversation reveals a painful truth about modern B2B sales: the process is riddled with friction. Santos shares a perfect example - a CMO who hasn't spoken to a salesperson in 15 years because her calendar is perpetually full, yet she researches solutions at 11 PM when sales teams are offline. This temporal mismatch between when buyers want to engage and when sellers are available represents billions in lost opportunity. Peel positions itself as a "voice AI layer" that creates intelligent, conversational agents for brands. But this isn't your typical chatbot - these agents can: Conduct full discovery calls in 5 minutes instead of 30-45 minutes Generate detailed "tear sheets" formatted to match specific sales methodologies Create automated "Peel Rooms" (similar to deal rooms) with all conversation insights Enable stakeholders to have the same conversation asynchronously One of the most compelling use cases Santos demonstrates is Peel's ability to conduct mass qualitative research. A marketing agency used Peel to interview 38 sales professionals about lead quality, creating a study called "Do My Leads Really Suck?" What traditionally costs thousands of dollars and takes months can now be done in a day, with results that update in real-time as more participants engage. Santos reveals how Peel uses the Winning by Design bow tie framework, allowing companies to deploy conversational agents at every stage of the customer journey - from awareness through renewal. This strategic approach ensures conversations are contextually appropriate whether someone is just discovering the brand or negotiating renewal terms. The discussion unveils key insights for training conversational AI: Start with easy, closed-ended questions Include personal questions early (people enjoy talking about themselves) Focus on present challenges and near-term goals Build dynamically based on responses Santos predicts that within a year, the entire enterprise sales cycle could theoretically be handled by AI agents. He envisions a world of "agent-to-agent" commerce where your personal AI assistant negotiates with vendor AI assistants on your behalf. While acknowledging human relationship-building will remain important, he sees AI eliminating the mechanical, repetitive aspects of sales.

www.gtmaipodcast.com www.aibusinessnetwork.ai www.gtmaiacademy.com https://www.linkedin.com/in/anuraggoel2/ The Hidden Crisis: Why Your AI Investment Is Probably Failing (And How to Fix It) If you're like most executives diving into AI, you're doing it wrong. Dead wrong. And the numbers prove it. In this week's explosive episode of the Go to Market AI podcast, enterprise transformation expert Anurag Goel (Red Hat, Salesforce, Adobe) drops a truth bomb that should terrify every C-suite executive: 88% of AI pilots never make it to production. But here's the kicker – he also reveals exactly how his team turned a simple POC into a $5 million value driver. The Problem Nobody Wants to Admit Let's start with the uncomfortable truth. While everyone's racing to implement AI tools, Goel exposes the fundamental flaw in most approaches: "AI founders are so passionate about what they have built... they jump to the shiny object. Look at the features that my technology has. It's so cool. Guess what? Executive buyers don't care." This isn't just philosophical musing. BCG's research backs it up – 68% of AI pilots fail to scale because companies skip the critical step of defining clear objectives and success metrics. They're essentially burning money on technology theater. The Strategic Framework That Changes Everything Goel's approach flips the script entirely. Instead of starting with tools (the mistake 90% of companies make), he advocates for a three-phase transformation framework: Phase 1: Problem Archaeology Dig past symptoms to find root causes Map the actual business process (not the idealized version) Identify where value is being destroyed, not just where AI could be added Phase 2: The Hypothesis-Led Discovery This is where things get interesting. Rather than running blind pilots, Goel's team creates what he calls a "hypothesis business case" BEFORE touching any technology. In the energy company example he shares, they identified a million-dollar opportunity in incident resolution time – then exceeded it by 10% during the pilot. Phase 3: Power Dynamics Navigation Here's the brutal reality: Your POC champion isn't your buyer. Goel emphasizes the critical transition from "proof of concept" to "proof of value" – packaging results in a way that speaks to economic buyers who control budgets.

www.aibusinessnetwork.ai www.gtmaiacademy.com https://theaihat.com/podcast/ https://www.linkedin.com/in/mikeallton/ Just wrapped up an incredible conversation with Mike Alton, Chief Storyteller at Agorapulse, and my mind is still buzzing from all the AI gold he dropped. If you're feeling overwhelmed by AI or wondering how to actually use it in your day-to-day work, this one's for you. Here's what struck me most about Mike: he's a coder who speaks human. After 20+ years in digital marketing and a computer science background, he's become what I call a "translator" - someone who can take complex AI concepts and make them click for regular folks like us. Mike discovered something fascinating when he asked AI to analyze him based on their conversations. It identified his superpower: bridging the gap between highly technical concepts and simple, practical applications. And honestly? That's exactly what we need more of in the AI space. One of the biggest takeaways was Mike's RICC prompting framework. Here's the breakdown: R - Role: Tell the AI who it needs to be I - Instructions: What you want to accomplish C - Context: All the relevant background info C - Constraints: Any limitations or specific requirements But here's the kicker - Mike always adds "Take your time. Ask me whatever questions you need before we move on." This simple addition transforms AI from a one-way output machine into an actual collaborative partner. During our chat, I asked Mike about the small tweaks that make big differences. Beyond just using a framework, here's what moves the needle: Chain Prompting: Instead of asking for a finished product, break it down. For a blog post, start with topic ideas, then outline, then headline, then content. Each step builds on the last. Let AI Ask Questions: Most people don't realize AI won't push back unless you tell it to. Give it permission to clarify, and watch your outputs improve dramatically. Specific Use Cases: The magic happens when you show someone exactly how AI solves THEIR specific problem, not generic examples. The Bridge Between Tech and RealityThe RICC Framework That Changes EverythingThe 20% Game-ChangersReal-World Magic in ActionThe Creativity Factor That Blew My MindThe Agent Revolution Is HereThe Mindset Shift for Leaders and DoersMy Personal TakeawaysYour Next Steps

Part 2: Building Autonomous Businesses with AI Agents (Jonathan Moss Interview)Podcast Description Jonathan Moss welcomes Amos Bar Joseph, co-founder and CEO of Swan AI (getswan.ai), for a strategic discussion on the autonomous business model that's challenging Silicon Valley's traditional playbook. Having built and sold multiple startups, Amos explains why he's now focused on reaching $30M ARR with just three founders using AI agents. This episode covers the philosophical framework behind autonomous businesses, detailed breakdowns of Swan's agentic technology, and exclusive announcements about new tools that democratize access to AI-powered go-to-market strategies. 99% of companies fail chasing funding rounds Focus shifts from value creation to "valuation inflation" Building for investors rather than customers "These types of companies, they don't pursue value creation, but what they are actually focused is valuation inflation." "It's not the fault of the founders I've been there myself. It's just that it's kinda like the natural tendency of building for the next round all the time." Website: getswan.ai LinkedIn: https://www.linkedin.com/in/amos-bar-joseph/

Part 1: The Autonomous Business Revolution with Amos Bar Joseph (Coach K Interview)Podcast Description Join Coach K (Jonathan Kvarfordt) for an energetic conversation with his friend Amos Bar Joseph, CEO of Swan AI (getswan.ai), who's rewriting the startup playbook by building to $30M ARR with just three founders and AI agents. After burning out on the traditional "unicorn playbook" through two successful exits, Amos shares his revolutionary approach to scaling with intelligence instead of headcount. This episode features a deep dive into Swan's actual AI agent ecosystem, controversial takes on popular GTM tools, and a practical framework for implementing AI in any business. Companies focus on "valuation inflation" over value creation The VC route makes founders forget customers and employees Building on "sick foundations" by scaling before product-market fit "I'm sick of the unicorn playbook... It hasn't changed for the last 15 years. It's outdated, it's not relevant for 2025." "They forget about their customers. They forget about their employees, they forget about how to build a company." AI will create MORE jobs, not fewer Hundreds of thousands of new autonomous businesses will emerge SMBs can now compete at enterprise scale "A three person team could achieve what took a 1000 team before that." Website: getswan.ai Connect: https://www.linkedin.com/in/amos-bar-joseph/

www.aibusinessnetwork.ai www.gtmaiacademy.com www.gtmaipodcast.com https://www.linkedin.com/in/tasleem1/ Tas Newsletter: https://www.linkedin.com/newsletters/7245478675247173632/?displayConfirmation=true The Experiment That Exposed Everything When Tas Hirani, a veteran enablement leader with a Six Sigma background from GE, noticed her sales teams struggling despite having access to cutting-edge AI tools, she did something radical. She didn't run another survey or schedule more training sessions. Instead, she went undercover as a sales rep while maintaining her enablement role. What she discovered explains why companies are spending millions on AI tools that collect dust while reps continue drowning in admin work. The Brutal Truth About Sales AI Adoption "Everyone's got LinkedIn, LinkedIn Navigator, ChatGPT, Perplexity... but when I actually sat in the seat and tried to use these tools the way reps do, it was Pandora's box," Hirani reveals. The problem isn't the technology—it's how we're implementing it. Here's why 90% of sales AI tools fail: The "Dead Weight" Problem: Traditional tech forced salespeople to adapt their workflow to the tool. As Hirani puts it, "Technology was like dead weight that people were hauling up the hill... trying to get to this sale, but I can't get there because I have to go to 12 different places." The Generic Solution Trap: Companies throw in Microsoft Copilot or ChatGPT behind a firewall and declare themselves "AI-enabled." Hirani calls this "a recipe for failure" because it ignores business-specific context. The IT Power Play: When IT departments impose generic AI solutions because they have "those two magic letters," adoption inevitably fails. The tools that work are chosen by the business teams who actually use them. The Reality Check That Changed Everything During her time in the sales trenches, Hirani discovered something shocking. When she shared AI tools that worked brilliantly for her, the reactions from her team were mixed: "Some reps said, 'I don't have any confidence in AI. It doesn't sound like me. My prospect is gonna know that it's not me if I haven't felt the pain and written that email myself.'" This revelation led to a fundamental insight: Every rep is at a different point in their AI adoption journey, and one-size-fits-all solutions are doomed to fail. Visual learners needed completely different tools than text-based processors New reps loved real-time coaching popups; veterans found them distracting Some thrived with vanilla ChatGPT; others needed specialized solutions

www.aibusinessnetwork.ai www.gtmaiacademy.com https://www.linkedin.com/in/scott-martinis/ https://www.b2bcatalyst.com/ Breaking Down GTM Engineering with Scott Martinez: A Game-Changing Conversation Holy smokes, folks. I just had one of those conversations that makes you want to completely rebuild your entire go-to-market motion. Scott Martinez from B2B Catalyst dropped some absolute truth bombs that I'm still processing. Let me be straight with you - I've been in sales and enablement for years, and Scott's approach to GTM engineering is unlike anything I've seen. This isn't your typical "send more emails" or "hire more SDRs" playbook. This is surgical precision applied to revenue generation. Scott shared a story that stopped me in my tracks. He generated 700 MQLs across three companies - 180 for one, 90 for another, and 399 for the third. Guess how much converted to revenue? Zero. Zilch. Nada. Why? Because generating leads isn't the same as generating revenue. And that's where most of us get it wrong. Here's what blew my mind: While most RevOps teams are doing territory planning based on industry and company size, Scott's data shows that proper account qualification criteria can result in 2-5x higher close rates. Think about that. If you're targeting accounts outside your true ICP, you're operating at 50-80% reduced effectiveness. You could make 100 calls into qualified accounts and get 5x better results than the same effort into unqualified accounts. Interview your top 3 sales reps with a "Perfect Opportunity Worksheet" Ask them: "When you're researching the best prospect ever, what do you expect to see?" Look for specific signals: Scott's approach is brilliant here. Instead of trying to automate everything at once, he asks: "What's the one constraint that, if fixed, would unblock everything else?" Real example: An SDR team spending 2 hours per day on account qualification. Instead of replacing them with AI, Scott's team: Identified 13 discrete website signals Built a scoring rubric Automated the qualification process Ran 80% of their CRM through it Found all the whitespace in their market Result? SDRs got 2 hours back per day, marketing got proper targeting, and AEs could finally hit self-sourcing targets. Here's the exact math Scott uses (and you should too): To hit $10M ARR: Need: 180 new customers at $50K each At 25% close rate = 720 opportunities needed At 20% meeting-to-opp rate = 3,600 meetings needed At 20% conversation-to-meeting rate = 18,000 conversations needed At 20% contact-to-conversation rate = 90,000 dials/emails needed With 5 contacts per account = 18,000 accounts needed But here's the kicker - every 10% of unqualified accounts in this mix torpedoes your downstream metrics. Scott's take on AI is refreshingly practical: "AI on its own is useless. You have to target it, constrain it, focus it, and give it examples to mimic and scale." His process: Understand the manual process that works Document exactly how your best people do it Use AI to scale that proven process Never try to AI your way around a broken process Scott doesn't worship tools, but he's specific about what works: Phone data: You need 20%+ connect rates. If you're at 3%, your data sucks Email: Industry average is dying. Apollo worked a year ago, doesn't now Clay: Great for enrichment, but it's <50% of the actual work Dialer stack: Get your team having 3-5 conversations per hour Forget activity metrics. Here's what to track: Qualified account identification rate Contact-to-conversation rate (aim for 20% with good data) Conversation-to-meeting rate (10% minimum, fix messaging if lower) Meeting-to-opportunity rate Close rate by account qualification score

www.gtmaiacademy.com www.aibusinessnetwork.ai https://www.linkedin.com/in/lauren-schiavone/ https://www.wonderconsultingllc.com/ Navigating AI Transformation: A Conversation with Lauren Morgenstein Join host Jonathan Kvarfordt, AKA Coach K, in the latest episode of the G-T-M-A-I podcast, as he engages with Lauren Morganstein. Lauren shares her journey from a 16-year career at P&G to venturing into the dynamic field of AI. They discuss her decision to found Wonder Consulting and her passion for demystifying AI for non-technical leaders. The conversation delves into practical applications of AI in business, the importance of upskilling, and the transformational potential of AI within organizations. Lauren also outlines her five-step AI transformation framework and shares insights on the evolving landscape of AI native companies and the critical role of effective AI councils. 00:00 Introduction and Guest Welcome 00:47 Lauren's Background and Career Journey 01:20 Diving into AI and Its Impact 02:48 Upskilling and Learning AI 05:08 AI in Consumer Insights and Innovation 12:42 AI Councils and Organizational Transformation 17:33 The Future of Prompting in AI 17:58 Adoption and Tool Recommendations 18:27 Maximizing Approved Tools 20:28 Balancing AI and Human Roles 22:59 Trends in AI for 2025 23:46 AI Native Companies 27:15 Culture and Change Management in AI 30:43 Personal AI Tools and Final Thoughts

www.gtmaiacademy.com www.aibusinessnetwork.ai https://www.linkedin.com/in/kimberlyhacker/ AI in the Sales Journey: Lessons from Testing 22 Note-Taking Tools I recently connected with Kim Hacker, Head of Business Operations at Arrows, who ran a fascinating experiment testing 22 AI note-taking tools simultaneously on sales calls. (read her in depth analysis here) Her insights opened my eyes to how AI is changing our sales processes in practical, meaningful ways. Kim's experiment came from a real need. Working at Arrows, a company building AI-powered digital sales rooms, she wanted to understand which note-taking tools would best support their AI features. "I use ChatGPT, I use Claude, I use AI day to day. But I was feeling like I didn't have the knowledge to back up a marketing campaign for our AI features," Kim explained. What surprised her was how different the results were across all 22 tools. The top performers weren't just capturing information - they were making it immediately useful for sales reps. Fathom took first place, with Granola second and Circle Back third. These winners stood out by producing skimmable notes that captured exactly what matters in sales - key stakeholders, timeline, and buyer interests - without unnecessary fluff.

www.aibusinessnetwork.ai www.gtmaiacademy.com Sami Rejeb is no stranger to transformative technology. With over 20 years of experience in revenue management, he's seen the sector evolve from manual operations to dynamic, AI-driven systems. His journey began as a CRM consultant at KPMG, followed by roles such as Customer Care Director for a mobile operator, Head of Value Selling for Oracle in the EMEA region, and managing RevOps for Salesforce in the Nordics. These experiences, filled with challenges and successes, motivated him to leverage AI to address the key issues revenue leaders face today. From Global Corporations to Entrepreneurial Ventures Sami’s global experience stretches across Oracle and Salesforce, and he has now taken a bold leap into entrepreneurship with ValueOrbit. This transition from large corporations to a startup naturally comes with its own set of differences. Sami recognizes that the agility of a startup offers unique advantages not typically found in larger, more established organizations. While major corporations like Oracle and Salesforce are marked by a high level of sophistication in sales strategies, the startup ecosystem allows for more flexibility and fortunately quick adaptation to new opportunities. At ValueOrbit, Sami aims to harness this flexibility to answer crucial sales-related questions: What deal should I prioritize? Should this be in our forecast? What should my next step be? These questions were central during his tenure at Oracle and Salesforce, and remain so as he pioneers ValueOrbit. The Birth of ValueOrbit The inception of ValueOrbit stemmed from a personal mission: to maximize the potential of CRM systems in driving sales success. While working at major organizations, Sami built layers of methodologies atop existing CRM tools, but it wasn’t until the advent of AI that he truly saw the potential to transform these processes. The use of AI in sales—something that previously seemed like a distant dream—became a reality, offering unprecedented possibilities for process enhancement. Sami’s approach with ValueOrbit focuses on revenue intelligence—spanning deal generation, closing, forecasting, and even conversational intelligence. Unlike traditional competitors, ValueOrbit doesn't simply aim to replicate existing solutions; it strives to redefine them by concentrating on process efficiency and automation. The Future of CRM and AI Integration Throughout our conversation, we explored the transformative potential of AI on CRM platforms. Sami believes that while CRM systems like Salesforce offer substantial value, they are ripe for evolution. He envisions a future where traditional CRM models, driven largely by manual input, are replaced or supplemented by automated systems that enhance user interactions. In the modern sales ecosystem, the integration of AI is not just about speeding up existing processes. It offers a unique opportunity to rethink and redesign the entire sales methodology. The current tools provide enormous data capabilities, but aligning these with practical, day-to-day operations remains a challenge that Sami is eager to tackle. Connect with Sami Rejeb If you’re interested in learning more about ValueOrbit and the innovative work that Sami Rejeb is doing, I encourage you to connect with him directly. You can reach out via LinkedIn or email him at [email protected]. Thank you for joining me in this deep dive into the future of sales and AI with Sami Rejeb. Keep innovating and challenging the status quo—together, let’s build the future of sales.

www.gtmaiacademy.com www.aibusinessnetwork.ai www.loyee.ai Join Coach K, also known as Jonathan Kvarfordt, in an engaging episode of the GTM AI Podcast featuring Dr. Desiree. They discuss Dr. Desiree's impressive journey from Macho Akia to Germany and the US, her entrepreneurial ventures, and her deep expertise in financial economics and AI. Dr. Desiree shares insights into her current work at Loyee.ai, an innovative company revolutionizing sales and marketing through AI and machine learning. Learn how Loyee.ai helps businesses refine their Ideal Customer Profiles (ICPs), enhance lead quality, and optimize go-to-market strategies for maximum efficiency and impact. Tune in for valuable lessons on the intersection of AI, data, and sales strategy. 00:00 Introduction and Guest Welcome 01:44 Guest Background and Journey 03:27 Early Startups and PhD Experience 04:46 Founding the Current Company 05:39 Product and Market Fit 07:18 Competitive Landscape and Differentiation 10:33 Data Sources and Technology 14:11 Quality and Effectiveness of Leads 15:53 Machine Learning Models vs. Practical Solutions 16:31 Simplifying Data for Clients 16:56 Challenges with Machine Learning Models 17:26 Leveraging External Data Sources 17:56 Future of Machine Learning in Business 18:16 Diving into AI and LLMs 19:42 Quality and Cost Trade-offs in AI 20:33 Strategy and Data Refreshing 24:22 Signal Identification vs. Signal Creation 28:06 Business Impact Stories 32:54 Conclusion and Contact Information

www.aibusinessnetwork.aiwww.gtmaiacademy.comwww.sparkhire.comIn the latest episode of the GTM AI Podcast, I got into an amazing discussion with Gary Schwake from Spark Hire, Inc. , a leading provider of hiring solutions for people-powered organizations. Their conversation explores the intersection of AI within the go-to-market (GTM) strategy and the hiring process, examining how AI can serve as a transformative tool rather than a mere technological novelty.The Spark Hire StoryWhen asked about Spark Hire, Gary enthusiastically explains the unique proposition of the company. Spark Hire, initially a one-way video interview solution, has expanded to include an amalgamation of offerings by acquiring Co Meet and Cha, thereby providing holistic hiring solutions. These solutions are specifically tailored for people-powered organizations in sectors such as healthcare, education, and professional services. This approach allows Spark Hire to address the nuanced needs of these industries by leveraging advanced technologies.AI in Go-To-Market and HiringA key part of the discussion revolves around AI’s role in both the GTM strategy and the hiring process. Gary emphasizes the imperative of utilizing AI to enhance human capabilities rather than replace them. He highlights the challenges of relying on probabilistic AI outcomes in hiring, pointing out the need for deterministic results to avoid unintended biases.In contrast, Jonathan reflects on the opportunities AI presents for refining interview processes and enhancing decision-making in hiring, balancing the need for data-driven insights with the irreplaceable value of human judgment.Strategizing with AI in a Changing LandscapeBoth speakers delve into how AI influences strategic decisions in contemporary business environments. Gary discusses how AI facilitates defining ideal customer profiles (ICPs) with unprecedented precision, extracting insights from unstructured data to improve targeting and engagement strategies. Jonathan, on the other hand, likens the application of AI to a strategic advantage, especially for experienced leaders who understand the framework of effective GTM strategies.The Collaborative FutureThe exchange of ideas also touches on the evolving relationship between roles within organizations, such as the CIO and CRO, as AI becomes more embedded in operations and strategy. Gary notes the necessity of a cross-functional approach in AI implementation, often orchestrated by CEOs to ensure seamless integration across departments and improve overall customer experience.Concluding ThoughtsIn concluding the episode, Gary gave insights on what businesses should prioritize and avoid as they approach the upcoming year. He stresses the importance of aligning AI initiatives with core business objectives, advising companies to begin simply and scale thoughtfully. By focusing on fundamental questions and challenges, organizations can effectively employ AI to bolster their operations and drive meaningful outcomes.Stay tuned for more insightful conversations on the GTM AI Podcast, where technology meets strategy in the fast-evolving business landscape. For direct engagement, connect with Gary Schwake through his LinkedIn profile or explore Spark Hire solutions at sparkhire.com.

www.aibusinessnetwork.aiwww.gtmaiacademy.comDaniel Beecham: https://www.linkedin.com/in/daniel-beecham/In a rapidly evolving world where artificial intelligence (AI) is reshaping industries and redefining job roles, understanding the nuances of AI implementation and adoption is crucial. In this enlightening podcast, I got to dig in with Daniel Beecham a fellow Founding Member of the AI Circle. We got into the intricacies of AI strategy, the challenges of adoption, and the exciting prospects for 2025.Meeting Daniel Beecham: AI Pro and AdvocateDaniel's journey from a biomedical engineering student at Georgia Tech to a pioneer in AI strategy is both remarkable and instructive. His experiences range from spending time at a marketing startup, navigating IT consulting at Capgemini, to tackling AI challenges in product management, offering valuable insights into AI integration within businesses.Navigating AI Strategy in OrganizationsOne of the core discussions revolves around the AI strategy in organizations. Daniel explains the importance of understanding the "why" behind AI adoption, emphasizing that AI should genuinely enhance business processes rather than act as a mere technological gimmick. He highlights critical steps in setting up an AI strategy, including assessing data maturity and ensuring good data governance. According to Daniel, businesses must have well-rounded representation within their AI governance teams, underscoring the need for executive leadership to play a role in prioritizing AI initiatives.Challenges in AI Adoption and Trust BuildingThe complexities tied to AI adoption are well-articulated, particularly the gap between initial excitement and sustainable usage. Daniel notes the essential role executive sponsorship plays in fostering widespread adoption within an organization. Furthermore, the conversation touches on trust in AI systems—how do organizations ensure their AI tools are providing accurate, reliable results? Jonathan and Daniel explore techniques such as prompt engineering and citations in AI outputs to bolster trust and reliability in AI solutions.The Power of Proof of Concept and Evaluating SuccessProof of concept (POC) initiatives are invaluable in evaluating AI tools' efficacy. Daniel shares insights from prior projects, illustrating how success metrics must be explicitly defined from the onset to measure POCs effectively. The conversation underlines how reductions in time and cost should align with stakeholder value, advocating for a metric-based approach to identify areas ripe for AI-driven transformation.Future Outlook: Hardware Innovations and Agentic WorkflowsAs the podcast draws to a close, attention shifts to future predictions for AI in 2025. Daniel expresses excitement around AI hardware advancements and agentic workflows, highlighting their potential to revolutionize personal and professional landscapes. The integration of AI into hardware promises to enhance the realism and applicability of AI technologies, paving the way for increased optimization and user experience.ConclusionThe podcast session with Daniel Beecham is an insightful exploration of AI's multifaceted journey through business strategy, workforce impact, and ethical considerations. It's a conversation that paints a comprehensive picture of where AI stands today and where it could potentially lead us tomorrow. As organizations continue to adapt and evolve, the insights shared in this discussion serve as guiding principles for embracing AI as a transformational force in society.

www.aibusinessnetwork.aiwww.gtmaiacademy.comwww.winningbydesign.comDRAMATIC SHIFT AND IMPACT OF AI ON BUSINESS AND GO TO MARKETToday hosted by Jonathan Moss we are thrilled to have Jacco van der Kooij the Founder of Winning by Design on to join us and talk about our favorite topic ;)Jonathan kicks off the conversation by highlighting the recent shifts in the go-to-market landscape. Over the past few years, businesses have transitioned from a "growth at all costs" mentality to emphasizing profitable, efficient growth. This shift coincides with the rise of AI as a transformative platform, presenting both challenges and opportunities for businesses.As Jacco points out, the impact of AI is not just about automation—it's about fundamentally transforming business models. Traditional inbound and outbound models are being replaced by AI-led growth, which emphasizes efficiency and scalability.Jacco introduces three key growth models: Product-Led Growth (PLG), Human-Led Growth (HLG), and AI-Led Growth (AILG). Each has its place in the market, but AI-Led Growth is particularly effective in optimizing costs and processes. According to Jacco, this model allows businesses to scale operations without exponentially increasing personnel costs. This change is crucial, especially in saturated markets where traditional human-led approaches are financially unsustainable.The discussion underscores the importance of viewing businesses like factories, where efficiency, quality, and scalability are the cornerstones of success. AI enhances these factors by providing rapid, accurate data insights, enabling businesses to adapt swiftly to market demands.While AI can substantially augment operations, Jacco and Jonathan agree on one crucial aspect: the human element. Relationships remain a cornerstone of business, especially in high-value transactions. The trust and brand reputation that a company establishes are invaluable. AI, rather than replacing human interaction, should enhance experiences by reducing friction in the buying process and allowing businesses to focus on nurturing relationships.Jacco highlights how AI is revolutionizing customer experience by delivering timely, accurate responses without the inefficiencies of traditional methods. Whether it's answering customer queries precisely or automating repetitive tasks, AI is redefining what businesses can achieve. However, achieving this requires businesses to rethink their processes and leverage AI to foster a seamless buying journey.The episode concludes with insights into where the industry is headed. Jacco envisions a future where AI reshapes pricing models, with dynamic pricing responding to real-time market demands. This shift, much like the introduction of AI itself, represents a renaissance in business—one where constant innovation and adaptation are key.The GTM AI Pod episode with Jacco is a critical exploration of how AI is not just an optional tool but an essential component of modern business strategy. For businesses looking to thrive in this new landscape, embracing AI to enhance both operational efficiency and customer experience is non-negotiable. As we continue to explore these changes, keeping the focus on creating exceptional buying experiences will be the defining element of success.For listeners and businesses alike, the message is clear: AI is here to stay, and integrating it thoughtfully will be the key to unlocking future growth.

www.aibusinessnetwork.aiwww.gtmaiacademy.comhttps://www.luella.ai/https://www.linkedin.com/in/mustafasaeed/Good morning, good evening, or good afternoon—whenever you find yourself diving into this exploration of AI and business technology. I am excited to dive deep into the world of AI-driven communication innovations with Mustafa Saeed, CEO and co-founder of Luella.AI.The Genesis of Luella AIMeeting Mustafa was like meeting a force of nature in the tech world. His story begins with a YouTube channel that funded his university education, transitioning into a tumultuous but rewarding role at a marketing agency impacted by Apple's iOS 14 update. This led to a life-changing pivot that set him on a path of technological exploration and growth.At Clearco, a significant player in e-commerce investment, Mustafa thrived, honing skills in sales and consultancy that eventually culminated in founding Luella AI. Driven by overcoming challenges he experienced firsthand, Mustafa and his team have focused intensely on AI's potential to revolutionize business communication.Why Luella? What's in a Name?Interestingly, Luella didn’t start with a grand story. Mustafa candidly admits the name was suggested by ChatGPT during a low moment of noodling through domain names. It was deemed suitable through its uniqueness and simplicity—fitting for a tech solution aiming to be straightforward and effective.Transforming Email DeliverabilityLuella AI's focus is a response to an immense pain point in today's digital communication landscape—email deliverability. All too often, emails, including key business communications, end up in spam due to AI-driven spam filters' evolutions from giants like Google and Microsoft.Luella positions itself as a protector of sender reputation and deliverability. By employing intricate systems mimicking those of major platforms, it ensures that spam rates can be reduced significantly for its users. This isn't just an enhancement tool; it's a potential game-changer for any business reliant on effective email outreach.Insights into the AI-Empowered FutureMustafa sees a promising horizon where communication agents do not just automate but optimize. Luella isn't just about sending emails; it’s about refining and targeting these messages to maximize engagement and results. The AI isn’t just an executor but a strategist alongside the human element, constantly experimenting and learning.Agents of Change: The Larger VisionWhere does Luella see its future? While staying grounded in cold email outreach for now, the company eyes potential expansions into other channels. The philosophy is intentionality over breadth—specialize deeply in a single facet and excel before branching out. There's an eagerness to innovate without losing focus, ensuring their existing solutions remain unmatched.

www.aibusinessnetwork.aiwww.gtmaiacademy.comFor FrontRace www.frontrace.comIn this episode of the GTM AI Podcast, host Jonathan Kvarfordt, also known as Coach K, is joined by Jack Siney from FrontRace. They dive deep into Jack's unique career journey, his transition from working with the Navy to entrepreneurship, and how he came to build his current company, FrontRace. Jack elaborates on how FrontRace helps companies effectively manage and analyze large datasets using AI, enabling better decision-making and operational efficiency. The conversation also touches upon the changes in sales processes post-COVID, the integration of AI in workflow, and future trends in automation and human interaction. The episode concludes with a discussion on the exciting yet challenging future of AI in various industries.00:00 Introduction and Guest Welcome00:26 Jack Siney's Background and Career Journey02:08 Introduction to FrontRace04:04 Challenges in Data Management and AI Solutions06:13 The Future of AI in Sales and Customer Interaction09:13 Human Element in AI and Automation15:48 Current AI Innovations at FrontRace16:08 The Data Dilemma: Too Much Information, Not Enough Insight16:54 Connecting the Dots: Integrating Data for Better Insights17:20 AI to the Rescue: Leveraging Artificial Intelligence for Data Analysis19:06 Real-World Applications: Success Stories and Challenges26:40 The Future of Sales and AI: Predictions and Expectations30:15 Conclusion: Embracing Change and Innovation