AI‑Native GTM: Billy Collins on Authenticity, Agentic Systems, and Top‑of‑Funnel Growth

Summary

With AI flooding every inbox, how do go-to-market leaders cut through without losing the human touch? Billy Collins, Partner at Eidra, a consultancy collective blending creativity, engineering, and data—shares how he’s building Eidra's U.S. presence while navigating AI’s promise and pitfalls. A former product and innovation leader turned commercial operator, Billy explains why his fully agentic cold-outreach experiments fell short, why authenticity now outperforms automation, and how he uses AI for industry-level research and brand building rather than one-to-one selling. He breaks down an AI-native top-of-funnel model—always-on content, social listening, and human-in-the-loop quality control—and flags first-mover opportunities like third‑party apps inside ChatGPT as new distribution channels. Billy also weighs the limits of digital twins, offers a practical framework for finding “arbitrage” in new platforms, and shares how to stay experimental without shipping AI-generated slop.

Timestamps

[00:00] – Why GTM leaders need an experimenter’s mindset to spot AI-driven arbitrage

[01:21] – Billy’s path from product/innovation to commercial leader and Eidra's U.S. growth mandate

[03:21] – Agentic outreach experiments: end‑to‑end automation vs. authentic 1:1 messages

[06:54] – Targeting smarter: deep industry research with AI (Gemini), human-in-the-loop, and the “chemistry” filter

[10:13] – Keeping outreach creative and real: focus on shared pain points and voice

[11:12] – The toughest GTM challenge: top‑of‑funnel, trust, and brand recognition in a new market

[14:03] – How far to automate: digital twins, video tools, and why the team stays human-first

[17:13] – SEO to AEO: authoritative content, agentic engines, and first-mover gains via ChatGPT apps

[21:21] – Where to follow Billy: LinkedIn thought leadership and occasional video

[22:08] – Parting advice: stay curious, run tight experiments, and revisit tools as models mature

Takeaways

- Run tight experiments: document, measure, scale what works, and kill what doesn’t—fast.

- Use AI for leverage, not replacement: apply it to industry research, content ops, and social listening; keep humans on tone and quality.

- Lead with authenticity in outreach: write in your voice; resist fully automated, end‑to‑end agentic campaigns.

- Build an AI‑native top of funnel: always‑on content, platform listening, and brand consistency to earn trust quickly.

- Pursue new distribution arbitrage: experiment with third‑party apps inside ChatGPT and other emerging channels.

- Be realistic about AEO: authority still wins—invest in credible thought leadership and performant web experiences before chasing shortcuts.

AI-First GTM in Heavy Industry: Digital Twin Spokesperson, YouTube SEO, and Master Prompts

Summary

If your buyers aren’t on social, rarely check email, and have zero tolerance for fluff, how do you earn attention and trust? Sarah Calkin-Ward, Director of Marketing at Fero Labs, explains how she scales a one-person marketing team with AI to reach process engineers and metallurgists in safety-critical environments. She shares why Fero Labs built an AI “digital twin” spokesperson—Pete Persona—to deliver thought leadership at scale, and why YouTube beat other channels for discoverability in an AI-driven search world. Sarah breaks down a rigorous win–loss analysis cadence to surface limiting beliefs that stall deals, then shows how “snackable” breadcrumb content and pillar events move conservative buyers forward. She also details how master prompts keep brand, persona, and regional nuance consistent across content, and how to train LLMs (and correct them) so they become reliable teammates. Expect concrete tactics any B2B team can borrow—from platform choices and persona design to prompt engineering that multiplies output without diluting quality.

Timestamps

[00:45] – Meet Sarah Calkin-Ward and Fero Labs’ mission: profitable sustainability for industrial processes

[02:26] – From B‑roll to Pete Persona: creating a digital twin spokesperson and choosing YouTube

[04:35] – Beating AI search bias: why authority sites win and how to ride YouTube, Wikipedia, Reddit signals

[06:08] – Unblocking deals: identifying and addressing buyer limiting beliefs before campaigns

[07:45] – Data in a niche market: win–loss analysis, sales probing, and internal reviews over volume

[09:51] – Channel strategy for busy, offline buyers: industry events and visitor-first YouTube content

[12:53] – Building an AI-powered stack: prompt engineering and master prompts for brand consistency

[16:13] – Training LLMs as teammates: persona/regional chats, catching errors, and tone replication

[18:19] – GTM focus: visibility, timing, and “snackable” breadcrumbing to invite deeper engagement

[20:03] – Parting advice: get behind AI or get left behind

Takeaways

- Build an AI spokesperson to scale thought leadership when executive time is scarce.

- Prioritize platforms favored in AI-driven search; use YouTube for speed, authority, and face recognition.

- Surface and neutralize buyer limiting beliefs with disciplined win–loss and sales-driven discovery.

- Create “snackable” breadcrumb content that delivers value fast and invites deeper conversations.

- Operationalize master prompts (company, brand, persona, region, product) to keep every asset on-voice.

- Treat LLMs as trainable teammates: correct inaccuracies, store prompts centrally, and iterate for consistency.

From SEO to GEO: Winning AI Search with Data‑Backed Thought Leadership

Summary

Is traditional SEO still worth it in the era of AI search? Founder and CEO of Artios, Andreas Voniatis, argues it’s “on life support” and lays out a practical roadmap to pivot from keyword-driven SEO to GEO—Generative Engine Optimization. A qualified accountant turned data scientist, Andreas retrained in machine learning, built his own LLM, and now helps companies become visible where buyers actually discover brands: inside AI systems. He explains why LLMs don’t crawl like search engines, why information gain (teaching AI something new) is the new ranking advantage, and why consolidating content into one authoritative URL beats publishing dozens of thin posts. You’ll hear how to renegotiate SEO contracts, ditch keyword tools, mine real buyer data from LinkedIn/Reddit/X or surveys, and craft people‑centric, evidence‑based thought leadership that passes AI fact‑checking. Andreas also previews what’s next—multimodal models that can ingest far richer content—and how to future‑proof your strategy now.

Timestamps

[00:45] – Meet Andreas Voniatis: accountant → SEO → data scientist; building an LLM and the wake‑up call for SEO

[02:58] – SEO vs. AI search: ETL, models, and why LLMs are people‑driven (not keyword‑driven)

[04:46] – The new ranking edge: information gain and teaching LLMs something they don’t know

[06:06] – Content architecture shift: one robust URL > dozens of posts; energy cost and model constraints

[07:04] – What to stop and start: renegotiate SEO scope, ditch keyword tools, invest in data research

[08:41] – Finding real buyer questions: data mining LinkedIn/Reddit/X and running surveys

[10:33] – Building E‑E‑A‑T: founder/SME commentary, contrasting perspectives, and passing AI fact‑checks

[12:22] – What’s next: saturation, multimodal LLMs, richer content experiences, and interactive formats

[21:17] – SEO and social converge: buyer‑centric GEO content that works on site and in feed

[24:56] – Where to find Andreas + parting advice for preparing now

Takeaways

- Prioritize information gain: publish data‑backed, buyer‑centric thought leadership that teaches LLMs something new.

- Consolidate related topics into a single, authoritative URL to align with how models ingest content.

- Redefine SEO vendor scope to technical discoverability/indexation; retire keyword‑led content planning tools.

- Mine your market: scrape LinkedIn/Reddit/X or run surveys to uncover real prompts, language, and topics buyers care about.

- Boost E‑E‑A‑T: include founder/SME commentary and contrasting viewpoints; cite data and methods to pass AI fact‑checking.

- Future‑proof content: design richer, multimodal experiences (visuals, interactive elements) as models ingest more than text.

Cutting Through the Noise: AI, Specificity, and Enterprise GTM with Aware’s CRO Brian Krause

Summary

In a market flooded with messages and smarter buyers, how do you win complex enterprise deals without adding to the noise? Brian Krause, Chief Revenue Officer at Aware, angel investor, and strategic advisor, shares a playbook for precision go-to-market. Aware builds biometric software that helps organizations verify identities and combat deepfakes, synthetic fraud, and account takeovers—giving Brian a front-row view of both GTM transformation and AI-driven threats. He explains why the best sellers are “information brokers,” how AI should speed access to relevant insights (not replace relationships), and why Customer Success is the most overlooked frontier for AI-driven revenue. Brian also breaks down how to turn research-grade innovation into clear differentiation, why use-case specificity beats generic claims, and where chatbots help—and fail—in technical enterprise sales. He closes with practical security advice for leaders and consumers: be vigilant, and choose providers with biometrics and step-up authentication. 

Timestamps

- [00:01] – Guest intro and career path: from Wall Street to CRO at Aware

- [01:44] – Pace and specificity: why generalist selling no longer works

- [02:46] – AI’s real role in enterprise sales—and the overlooked Customer Success opportunity

- [05:54] – Practical tools: internal automation and arming reps with timely intel

- [08:56] – Fighting deepfakes: translating R&D into differentiated GTM

- [10:55] – Cutting through the noise: use-case messaging and consultant-level selling

- [14:59] – Bots vs. humans in complex sales: where chatbots help and where they don’t

- [17:07] – Protecting against AI-driven fraud: vigilance and biometrics-first security

Takeaways

- Anchor your GTM to precise use cases and the customer’s decision criteria—not broad product claims.

- Use AI to arm sellers with timely, relevant insights; accelerate research without replacing human relationships.

- Elevate Customer Success with AI that surfaces multi-threaded account signals to drive retention and expansion.

- Curate data inputs: tight ICPs, personas, and governed feeds beat “boil the ocean” approaches.

- Translate deep technical work into clear differentiation backed by proof points and demos.

- Strengthen security by choosing providers with biometrics and step-up authentication; continually train teams to spot phishing and deepfakes.

GTM in the GenAI Era: ActiveFence’s CRO on Safety, Research-Led Outreach, and Precision Prospecting

Summary

GenAI is surging—and so is the noise. How do you build pipeline, stay credible, and keep customers safe in the process? John O’Donnell, Chief Revenue Officer at ActiveFence, shares how his team protects 3B+ users while helping enterprises deploy AI responsibly. ActiveFence partners with the world’s largest social platforms and foundation model companies, powered by a world-class research team and a “database of evil” that tracks bad actors and emerging threats. John breaks down a research-led outreach motion that leads with value, not hype; how tools like Clay and Gong sharpen targeting and speed execution; and why “go-to-market” is becoming “go-to-network.” He also covers the biggest GTM challenge right now—filtering FOMO-fueled noise—and how to qualify by GenAI maturity stage. Expect practical tactics to mobilize subject-matter experts without pulling them off their day jobs, build credibility even when mentioning competitors, and scale globally as AI agents move into production.

Timestamps

- [00:45] – Guest intro: ActiveFence’s mission and protecting 3B+ users online

- [01:04] – John’s path from Rapid7 to CRO and why AI safety is a GTM advantage

- [03:17] – Precision prospecting with GenAI and Clay: from “wide nets” to right-time outreach

- [05:57] – Research-led messaging: dark web intel, value-first content, credibility at first touch

- [07:29] – Today’s GTM challenge: filtering FOMO noise and qualifying by GenAI maturity

- [09:15] – Operational leverage with Gong: CRM automation, email summaries, and faster follow-up

- [11:59] – Mobilizing SMEs: using AI to turn expert insight into scalable content (without the drag)

- [14:17] – Go-to-network: everyone sells; overcoming “salesy” fears and earning peer trust

- [18:16] – What’s next for ActiveFence: securing GenAI agents and global expansion

- [20:59] – Parting advice: continuous learning as a competitive edge

Takeaways

- Lead with intelligence: share research and threat insights upfront to earn trust before the first call.

- Use Clay to segment by industry, role, and GenAI stage; personalize messaging to policy and risk.

- Automate the admin: deploy Gong to capture notes, summarize emails, and accelerate next steps.

- Turn SMEs into multipliers: use AI to draft white papers and briefs from expert input in hours.

- Build a go-to-network culture: equip non-sales teams to answer peer questions credibly—even when mentioning competitors.

- Qualify for signal: map prospects by GenAI deployment maturity to focus timing, message, and resources.

Beyond Leads: Jeanne Hopkins on VoC, Tech Stacks, and Community-Led Growth

Summary

If your marketing still revolves around net-new leads, you’re leaving growth on the table. Jeanne Hopkins—former VP of Marketing at HubSpot (employee #100) and veteran B2B/B2C leader with roles at LEGO and Symmetricom—explains why the best marketers own the voice of the customer and build systems that align product, sales, and support. Jeanne shares how she launched an internal blog to unite global teams before “content ops” was a term, why monthly cross-functional VoC forums beat ad-hoc requests, and how to use AI and competitive intel for sharper battlecards without losing focus on product-market fit. She breaks down a practical tech stack audit in a CFO‑driven era, the community and partner strategies that scaled HubSpot (including webinars drawing 25,000 registrants and a partner channel now driving ~50% of revenue), and the change-management pitfalls when product UX shifts too far from what users know. Expect actionable guidance on customer marketing, channel mix, and budget discipline that travels from startup to enterprise.

Timestamps

- [00:45] – Jeanne’s career arc: journalism roots, accounting degree, LEGO to Symmetricom, and a lifelong learning mindset

- [03:26] – Building “Symblog”: internal comms as a growth lever and the case for marketing-led alignment

- [05:26] – From stitched tools to integrated stacks: HubSpot’s role and why marketing is communication (inside and out)

- [07:27] – Owning VoC: the monthly “three things customers want” meeting to align GTM and product roadmaps

- [11:16] – Practical AI and comp intel (Crayon): battlecards, differentiation vs. commodity, and PMF realities

- [14:14] – CFO-era decisions: how to rationalize your tech stack, avoid redundancy, and justify spend

- [16:19] – Content as a magnet: HubSpot’s inbound play, 25k-registrant Facebook series, and community that scales

- [19:13] – Channel strategy beyond direct: partners, e-commerce, and the exponential effect of shared content

- [26:19] – Personalization starts offline: listening to sales calls, calling customers, and the 80/20 retention gap

- [28:13] – Change management lessons: when a UX overhaul backfires and how to protect user continuity

- [30:36] – Parting advice: partner with your CFO, love your budget, and remember—the logo color doesn’t matter

Takeaways

- Own the voice of the customer by running a monthly cross-functional forum that prioritizes the top three customer needs across sales, support, marketing, and product.

- Audit and rationalize your tech stack: identify owners, budgets, renewal dates, overlap, and auto-renew traps; cut redundancy before the CFO does it for you.

- Use AI and competitive intel to accelerate research and battlecards, then anchor messaging in real differentiation and product-market fit—not “arts and crafts.”

- Build community-led content (series, how-tos, webinars) that teaches; package and repurpose to compound reach over time.

- Scale with partners and channels, not just direct: enable resellers and agencies to share your content and extend your brand.

- Prioritize customer marketing: listen to sales calls, proactively interview the “other 80%,” and turn retention and expansion into core growth engines.

- Manage change deliberately: protect user workflows, test with real customers, and avoid disruptive redesigns that break adoption.

Winning Pipeline in an AI Era: Scott Leese on Go-to-Network, Creative Prospecting, and Sales Fundamentals

Summary

Pipeline is harder to build, inboxes are noisy, and AI is changing how buyers buy—so what actually works now? Bestselling author and go-to-market advisor Scott Leese joins Growth Wizards to share a pragmatic playbook for winning deals in 2025. Scott advises seed to Series C companies on GTM, sales ops, and RevOps, runs a micro-VC, coaches 65+ CROs/VPs, and even operates an Austin landscaping business—giving him a rare vantage point across tech and traditional services. He breaks down where AI is useful today (coaching and mid-funnel automation), why agent-to-agent selling is closer than most think, and how to apply AI advantage in “slow adopter” industries. Then he dives into the creative, unscalable tactics that are working now—shifting from go-to-market to go-to-network, hosting micro-events, and standout direct mail—to open doors when cold calls and email underperform. Finally, Scott brings it back to basics: diagnosing real pain, creating urgency, quantifying impact, and closing with discipline. He also previews his 24-hour Midnight to Millions virtual sales event and closes with a challenge: track network growth as a core sales KPI.

Timestamps

- [00:45] – Who is Scott Leese: advisor, coach, founder, and multi-business operator

- [02:06] – Time management without AI assistants: partners, fast decisions, publish and ship

- [04:28] – Practical AI in GTM: coaching platforms, AI demo agents, and applying AI beyond tech

- [07:31] – Will AI own the funnel? Agent-to-agent sales timelines and what’s realistic

- [11:25] – Creativity that cuts through: go-to-network, micro-events, direct mail, and unscalable moves

- [16:21] – Back to basics: find pain, create urgency, differentiate clearly, quantify ROI, follow up

- [18:25] – Today’s GTM gap: pipeline first, then urgency, then fundamentals

- [19:34] – Midnight to Millions preview and why breadth of topics matters

- [22:05] – Parting advice: grow your network and measure it like a KPI

Takeaways

- Build a go-to-network engine: expand referrals and affiliate intros to open higher-converting opportunities.

- Do the unscalable to stand out: host invite-only dinners, micro-events, morning runs, or airport rides.

- Use creative direct mail to earn attention: thoughtful, on-brand gifts beat crowded inboxes.

- Apply AI where it’s ready now: coaching, discovery, and mid-funnel tasks—then expand beyond tech.

- Master the fundamentals: diagnose real pain, make it urgent, quantify impact, and close decisively.

- Track network growth as a core KPI and reward introductions with meaningful referral commissions.

From QVC to AI-Driven Enrollment: Mickey Baines on Data Hygiene, Frictionless Journeys, and 1:1 Outreach

Summary

What can a live TV toy demo teach leaders about building high-performing, AI-enabled teams? Mickey Baines, President and Chief Revenue Officer at Kennedy & Company Education Strategies, shares how seven-minute QVC segments shaped his approach to feedback, messaging, and execution in higher education. Mickey breaks down how to translate features into benefits, set up disciplined AI experimentation, and move from broad segments to truly one-to-one outreach. He explains why you must start with foundational prompting skills, align “AI toys” to strategy, and invest in clean, connected data to unlock predictive intent, next-best-action communications, and natural-language access to enterprise metrics. You’ll hear practical examples—from cutting call volume in half by solving password resets upfront to mining unstructured data to spot friction in real time—plus a maturity model for advancing toward personalized engagement at scale. He closes with how to keep your flywheel spinning: keep learning, assessing, and applying.

Key Timestamps

- [00:45] – Mickey’s path: higher ed practitioner to consultant—and six years selling toys on QVC

- [02:24] – Live TV lessons: revenue-per-minute, ultra-specific feedback, and performing under pressure

- [07:13] – Turning features into benefits: messaging that resonates with buyers and students

- [08:40] – The AI “toys”: start with prompting, then run directed experiments aligned to strategy

- [11:57] – Predictive intent and 1:1 automation: voice agents, video, and next-best communication

- [13:50] – Natural-language analytics: querying connected data so leaders self-serve insights

- [15:49] – Removing friction: password resets, proactive comms, and using unstructured data to spot issues fast

- [19:43] – The hard truth: data hygiene, integration, and feature engineering to reach true personalization

- [24:57] – Where to find Mickey: Spark and Scale podcast and LinkedIn

- [26:18] – Parting advice: keep learning—feed the flywheel

Takeaways

- Start with prompting: build foundational skills and run directed, strategy-aligned AI experiments.

- Translate features into benefits to drive action; make the value obvious for your audience.

- Invest in data hygiene and integration; clean, connected data is prerequisite for predictive and 1:1 outreach.

- Use AI to surface friction from unstructured data and fix issues proactively (e.g., password reset bottlenecks).

- Prioritize by intent and prescribe next steps; move from broad segments to automated, one-to-one engagement.

- Enable natural-language access to metrics so executives and teams can self-serve insights in seconds.

Early-stage founders don’t need a $200K marketing hire to build pipeline—they need a system that scales. Justin Ashby, a Utah-based fractional VP of Marketing and former product marketing leader turned founder advisor, breaks down “go-to-market engineering”: stitching affordable tools and workflows to turn website intent into warm conversations.

With experience across 12 startups in the past eight months, BYU MBA venture training, and a service he calls “executive orchestration,” Justin shows how to activate founders on LinkedIn, personalize outreach for modern buying committees, and run rapid experiments that reveal winners fast. He shares the exact building blocks (think website tracking, enrichment, and automated—but human-sounding—multichannel follow-up), why AI should multiply—not replace—your efforts, and when a fractional leader outperforms a first full-time marketing hire.

Expect practical tactics like role-specific messaging to CFOs/RevOps/Marketing, gift-card and ABM plays (yes, even Lego kits), and scrappy in-person events that compress sales cycles.

Timestamps

- [00:45] – Justin’s path: product marketing, VC exposure, zero-to-one startups, and going fractional

- [04:49] – The first marketing hire dilemma: why fractional leadership de-risks early GTM

- [07:05] – Building a lean GTM engine: channels, partnerships, LinkedIn, and fast testing

- [08:45] – AI + GTM engineering: connecting tools and workflows without heavy “agents”

- [10:57] – The stack blueprint: website tracking → enrichment (e.g., Clay) → email (e.g., Instantly) → LinkedIn

- [11:39] – Executive orchestration: turning founders into consistent LinkedIn thought leaders

- [13:50] – Standing out: personalized, multi-threaded outreach for larger buying committees

- [17:20] – Experiment or fall behind: rapid iteration, ABM plays, and in-person events that accelerate deals

- [19:31] – How to connect with Justin and where he’s speaking next

Takeaways

- Engineer your GTM: connect website intent to enrichment, email, and LinkedIn outreach so follow-up happens automatically and fast.

- Activate executives as creators: use founder-led LinkedIn to drive awareness, intros, and trust at the top of the funnel.

- Personalize across the buying committee: craft role-specific messages for CFOs, RevOps, and functional leaders to multi-thread deals.

- Use AI as a multiplier: automate the grunt work but keep copy human, specific, and signal-rich.

- Run rapid experiments: test multiple motions monthly (email offers, ABM kits, partnerships), kill losers, and scale winners.

- Host scrappy in-person events: small meetups compress sales cycles and create high-quality conversations at low cost.

- Start fractional, then scale: bring in a senior operator to build the system and channels before hiring full-time.

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What does it take to scale a global B2B startup into a unicorn? In this episode of Growth Wizards, host Tanner Green sits down with David Gales, Head of Marketing at Oyster, a global employment platform revolutionizing how companies hire and support talent across borders.

David shares how his early focus on customer experience and retention laid the foundation for Oyster’s scalable growth engine. From launching onboarding campaigns with authentic personal touches to building cross-functional frameworks with sales and operations, David breaks down the core systems that enabled Oyster’s global expansion.

He also dives into how the team uses tools like Clay for signal-based prospecting and AI-powered automation, how they run internal journey mapping workshops to close CX gaps, and why building the right infrastructure before scaling is essential.

Whether you're a startup marketer or a founder building toward scale, this conversation is full of actionable strategies you can apply today.

Timestamps

• [00:14] – David Gales introduces himself and Oyster’s global mission

• [01:32] – Early scaling challenges: Data scarcity and intuitive decision-making

• [03:15] – Why customer interviews and authentic outreach matter

• [05:59] – Building lifecycle frameworks and defining friction points

• [08:07] – Role of operations in aligning sales, CX, and marketing

• [10:33] – Tech stack essentials: How Oyster uses Clay for AI-led prospecting

• [13:29] – David’s advice for marketers building toward unicorn status

  
  

Takeaways

• Start with customer insight – Prioritize user interviews and real conversations before relying on data.

• Build before you scale – Invest early in operations, lifecycle mapping, and internal alignment.

• Use AI tools intentionally – Combine tools like Clay with automation for signal-driven prospecting.

• Design with delight in mind – Cross-functional CX workshops can uncover hidden gaps and drive better experiences.

• Test fast, learn faster – Rapid experimentation, followed by iteration, builds smarter marketing systems.