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FutureCraft GTM

FutureCraft GTM

Written by: Erin Mills & Ken Roden
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 FutureCraft GTM, the essential podcast for B2B marketers, sales and CS seeking to harness the power of AI. Hosted by industry experts Erin Mills and Ken Roden, each episode explores the dynamic intersection of artificial intelligence, go-to-market, strategy, and emerging trends in the B2B space.Copyright 2025 All rights reserved. Economics Marketing Marketing & Sales
Episodes
  • Special Episode: Why Customer Success Can’t Be Automated (And What AI Can Actually Do)

    Special Episode: Why Customer Success Can’t Be Automated (And What AI Can Actually Do)
    Dec 18 2025
    Why Customer Success Can't Be Automated (And What AI Can Actually Do) In this special year-end episode of the FutureCraft GTM Podcast, hosts Ken Roden and Erin Mills sit down with Amanda Berger, Chief Customer Officer at Employ, to tackle the biggest question facing CS leaders in December 2026: What can AI actually do in customer success, and where do humans remain irreplaceable? Amanda brings 20+ years at the intersection of data and human decision-making—from AI-powered e-commerce personalization at Rich Relevance, to human-led security at HackerOne, to now implementing AI companions for recruiters. Her journey is a masterclass in understanding where the machine ends and the human begins. This conversation delivers hard truths about metrics, change management, and the future of CS roles—plus Amanda's controversial take that "if you don't use AI, AI will take your job." Unpacking the Human vs. Machine Balance in Customer Success Amanda returns with a reality check: AI doesn't understand business outcomes or motivation—humans do. She reveals how her career evolved from philosophy major studying "man versus machine" to implementing AI across radically different contexts (e-commerce, security, recruiting), giving her unique pattern recognition about what AI can genuinely do versus where it consistently fails. The Lagging Indicator Problem: Why NRR, churn, and NPS tell you what already happened (6 months ago) instead of what you can influence. Amanda makes the case for verified outcomes, leading indicators, and real-time CSAT at decision points. The 70% Rule for CS in Sales: Why most churn starts during implementation, not at renewal—and exactly when to bring CS into the deal to prevent it (technical win stage/vendor of choice). Segmentation ≠ Personalization: The jumpsuit story that proves AI is still just sophisticated bucketing, even with all the advances in 2026. True personalization requires understanding context, motivation, and individual goals. The Delegation Framework: Don't ask "what can AI do?" Ask "what parts of my job do I hate?" Delegate the tedious (formatting reports, repetitive emails, data analysis) so humans can focus on what makes them irreplaceable. Timestamps 00:00 - Introduction and AI Updates from Ken & Erin 01:28 - Welcoming Amanda Berger: From Philosophy to Customer Success 03:58 - The Man vs. Machine Question: Where AI Ends and Humans Begin 06:30 - The Jumpsuit Story: Why AI Personalization Is Still Segmentation 09:06 - Why NRR Is a Lagging Indicator (And What to Measure Instead) 12:20 - CSAT as the Most Underrated CS Metric 17:34 - The $4M Vulnerability: House Security Analogy for Attribution 21:15 - Bringing CS Into Sales at 70% Probability (The Non-Negotiable) 25:31 - Getting Customers to Actually Tell You Their Goals 28:21 - AI Companions at Employ: The Recruiting Reality Check 32:50 - The Delegation Mindset: What Parts of Your Job Do You Hate? 36:40 - Making the Case for Humans in an AI-First World 40:15 - The Framework: When to Use Digital vs. Human Touch 43:10 - The 8-Hour Workflow Reduced to 30 Minutes (Real ROI Examples) 45:30 - By 2027: The Hardest CX Role to Hire 47:49 - Lightning Round: Summarization, Implementation, Data Themes 51:09 - Wrap-Up and Key Takeaways Edited Transcript Introduction: Where Does the Machine End and Where Does the Human Begin? Erin Mills: Your career reads like a roadmap of enterprise AI evolution—from AI-powered e-commerce personalization at Rich Relevance, to human-powered collective intelligence at HackerOne, and now augmented recruiting at Employ. This doesn't feel random—it feels intentional. How has this journey shaped your philosophy on where AI belongs in customer experience? Amanda Berger: It goes back even further than that. I started my career in the late '90s in what was first called decision support, then business intelligence. All of this is really just data and how data helps humans make decisions. What's evolved through my career is how quickly we can access data and how spoon-fed those decisions are. Back then, you had to drill around looking for a needle in a haystack. Now, does that needle just pop out at you so you can make decisions based on it? I got bit by the data bug early on, realizing that information is abundant—and it becomes more abundant as the years go on. The way we access that information is the difference between making good business decisions and poor business decisions. In customer success, you realize it's really just about humans helping humans be successful. That convergence of "where's the data, where's the human" has been central to my career. The Jumpsuit Story: Why AI Personalization Is Still Just Segmentation Ken Roden: Back in 2019, you talked about being excited for AI to become truly personal—not segment-based. Flash forward to December 2026. How close are we to actual personalization? Amanda Berger: I don't think we're that close. I'll give you an example. A friend suggested I...
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    43 mins
  • Why AI Rollouts Failed in 2025, And What's Actually Working in Go-to-Market

    Why AI Rollouts Failed in 2025, And What's Actually Working in Go-to-Market
    Nov 13 2025

    Join hosts Ken Roden and Erin Mills as they reflect on an incredible Season 2 of the FutureCraft GTM podcast. From pilot purgatory to agent swarms, they unpack how AI in go-to-market evolved throughout the year, share their biggest lessons learned, and make bold predictions for 2026.

    Key Topics Covered

    Season 2 Reflections [00:01:00]

    • The slow start vs. strong finish of AI adoption
    • Pilot purgatory and why 95% of AI rollouts struggled
    • The accordion effect of AI tools throughout the year

    Guest Predictions Review - "They Called It" [00:04:00]

    • Rachel Tru Air on AI SDRs: Still a work in progress
    • Chase Hannigan on no-code agentic systems: Ahead of the curve
    • Liza Adams on EQ being the edge: Called it perfectly

    Major Themes That Emerged [00:08:00]

    • Adoption over tools as the key to success
    • AI as teammate vs. AI as output generator
    • The "sandwich model" - humans at both ends, AI in the middle
    • Curiosity and EQ as critical differentiators

    What Failed This Year [00:10:00]

    • AI vendor spray-and-pray marketing
    • Custom GPT overload (600 GPTs at one company!)
    • Rolling out LLMs without proper change management

    Business Impact Wins [00:17:00]

    • Speed to market improvements
    • Analytics accessibility for non-technical users
    • 600% more time on site from AI-driven traffic
    • Time auditing as a measurement strategy

    Personal Lightning Round [00:32:00]

    • Most overhyped buzzword: AIEO
    • Underrated tool: N8N
    • Biggest personal unlock: Self-regulation with AI use
    • Best use case: Digital twins and content workflows

    2026 Predictions [00:24:00]

    • Agent swarms and workforces (Erin's pick)
    • Digital twins as the hero (Ken's pick)
    • Closed company-specific LLMs
    • Fractional AI experts with their own agent teams
    • New organizational structures emerging
    Notable Quotes

    "AI is like an intern with a PhD who doesn't have any business experience" - Ken

    "Digital twins are great, but I think it's gonna be swarms" - Erin

    "It's 90% focus on the people and 10% on the execution now, not the other way around" - Erin

    "Get your hands dirty. Because this is new to everybody, there's a real need to understand what your team is going through" - Erin

    Guests Mentioned This Episode
    • Liza Adams
    • Rachel Truair (Simpro)
    • Chase Hannegan
    • Sheena Miles
    • Rebecca Shaddix
    • Chris Penn
    Key Takeaways
    1. Change management is critical - 80% focus on people, 20% on execution
    2. Start with boring problems - Don't chase the sexiest AI use cases
    3. Define acceptable mistakes - Know when to call a pilot a failure
    4. Agent swarms are the future - Moving beyond single-purpose tools
    5. Communities matter - AI has opened unprecedented knowledge sharing
    6. Speed to market - Months-long processes now taking days or hours
    Resources Mentioned
    • N8N workflow automation platform
    • Relevance AI
    • Lindy
    • ElevenLabs (voice)
    • Planet Money AI recruiting segment
    • Chris Penn's analytics community
    Coming in Season 3 (March 2026)
    • Human agentic workflows with verification stopgaps
    • Agent swarm implementations
    • New modalities: voice and video applications
    • More on the Iron Man suit approach to fractional AI work

    Share what you want to see in Season 3 & Connect with the Hosts:

    • Ken Roden
    • Erin Mills

    About FutureCraft

    Stay tuned for more insightful episodes from the FutureCraft podcast, where we continue to explore the evolving intersection of AI and GTM. Take advantage of the full episode for in-depth discussions and much more.

    To listen to the full episode and stay updated on future episodes, visit our website, https://www.futurecraftai.media/

    Disclaimer: This podcast is for informational and entertainment purposes only and should not be considered advice. The views and opinions expressed in this podcast are our own and do not represent those of any company or business we currently work for/with or have worked for/with in the past.

    Music: Far Away - MK2
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    38 mins
  • Boring Problems, Big Wins, Community‑Driven AI Adoption

    Boring Problems, Big Wins, Community‑Driven AI Adoption
    Nov 6 2025
    Boring Problems, Big Wins, Community‑Driven AI Adoption

    AI is not overhyped, it is under-implemented. Ken Roden and Erin Mills chat with Sheena Miles on how to move from tool obsession to behavior change, her three stage framework, and the practical KPIs that prove progress before revenue shows up. We also talk AI policy that unlocks safe experimentation, community as an accelerator, and Sheena demos how she spins up n8n workflows from a prompt.

    Chapter markers

    00:00, Cold open and disclaimer 01:00, Is AI overhyped, what is really failing 03:20, Early indicators versus lagging revenue, set better goals 04:20, Exec view, target 3 percent faster time to market 06:00, Avoid AI slop, find repetitive, boring work 07:00, Guest intro 09:00, Real state of adoption, dual speed orgs and siloed champions 10:45, Teach concepts, not tools 12:00, Policy, security review, AI council 14:00, Behavior beats features 15:30, Community for accountability and shared assets 17:30, Live n8n demo, import a skeleton workflow and adapt 35:00, AI first versus AI native, embed into workflows 36:30, Influence without authority, solve a champion’s boring problem 38:00, Inclusion and usage gaps, why it matters to the business 40:00, Skills that matter now, prompting, rapid testing, communicating thought process 43:00, Why to be optimistic 45:00, Lightning round 48:00, Host debrief and takeaways

    Key takeaways
    • Hype versus reality, most failures are vague goals and tool-first rollouts, not AI itself. • Measure what you can now, speed to market, cycle time, sprint throughput, ticket deflection, before revenue. • Framework, Activate, Amplify, Accelerate, start small, spread what works, then institutionalize. • Policy unlocks velocity, simple rules for data and tool vetting plus a cross functional council. • Behavior over features, learn inputs and outputs so skills transfer across tools. • Community compounds, accountability and shared templates speed learning. • Start with boring problems, compliance questionnaires, asset generation, ticket clustering, call insights. • AI first versus AI native, move from sidecar to embedded with human review gates. • Inclusion is a business lever, close usage gaps or accept a productivity gap.
    Sheena’s three stage framework

    Activate, prove value safely • Define the problem, validate AI fit, run a small pilot. • Track accuracy thresholds and time saved. • Example, auto draft responses to repetitive compliance questionnaires from a vetted knowledge base.

    Amplify, spread what works • Connect adjacent teams, add light governance, share patterns. • Run cross team pilots and publish playbooks. • Example, connect support tickets, payments, compliance, partner success to detect issues proactively.

    Accelerate, institutionalize • Assign ownership, embed training, integrate tools, set ROI guardrails. • Roll out across channels and systems with quality gates. • Example, ad copy system owned by demand gen, content as QA, used across paid, email, social.

    Hot Takes from Sheena

    “Policy enables speed if you write it to unblock safe experiments.” “Stop memorizing tool steps, learn the concepts so they transfer.” “Solve the boring problem first, that is where AI pays for itself.” “If NRR belongs to someone, it belongs to everyone.”

    Resources & Links

    • Sheena Miles on LinkedIn
    • Women Defining AI, podcast and community
    • n8n

    About FutureCraft

    Stay tuned for more insightful episodes from the FutureCraft podcast, where we continue to explore the evolving intersection of AI and GTM. Take advantage of the full episode for in-depth discussions and much more.

    To listen to the full episode and stay updated on future episodes, visit our website, https://www.futurecraftai.media/

    Disclaimer: This podcast is for informational and entertainment purposes only and should not be considered advice. The views and opinions expressed in this podcast are our own and do not represent those of any company or business we currently work for/with or have worked for/with in the past.

    Music: Far Away - MK2
    Show More Show Less
    51 mins
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