Gabe Larsen, CRO of Atonom, canceled a $40KSalesforce contract with no replacement plan and built a working CRM in 3 hours using Lovable. This is the full story plus his playbook on AI SDRs and the autonomous organization.

In Episode 13 of GTM Hackers, host Charles Brun sits down with Gabe Larsen to unpack two of the most talked about shifts in go to market today. First, the rise of the autonomous organization where AI cloud employees work side by side with humans. Second, the bold decision to rip out Salesforce and vibe code a custom CRM using Lovable.

Gabe brings 20 plus years of GTM experience from Goldman Sachs, Accenture, Inside Sales.com, and Customer (acquired by Meta). He now leads revenue at Atonom, a startup building the cloud employee category across marketing, sales, customer success, support, and HR.

What you will learn in this episode:

1. Why the traditional model of scaling with headcount and tools is dead, and what is replacing it.

2. How to think about AI SDRs as employees rather than tools or cost per conversation.

3. The full 4 step onboarding process Atonom uses for every new AI cloud employee, covering identity, memory, tools, and role play.

4. Why multi agent architectures beat deterministic workflow tools like Make and N8N for complex GTM jobs.

5. The real world performance of AI SDRs on inbound lead qualification, including a case study with a 1000 percent improvement in lead response time.

6. Why cold outbound AI SDRs are failing and what signal based selling with cloud employees looks like instead.

7. The hot, warm, and cold framework for AI in GTM motion.

8. The exact moment Gabe decided to cancel Salesforce and why his whole team was relieved.

9. How his CFO and head of finance built the first version of the new CRM in 3 hours over root beers in Salt Lake City.

10. Why the maintenance argument against vibe coded CRMs is overblown.

11. The benefits of a conversational CRM over traditional reporting.

12. Why Gabe never signs SaaS contracts longer than 12 months.

Discussion topics covered:

Autonomous organization and frontier firms

Cloud employees and AI SDR architecture

Multi agent systems and supervisor agents

AI employee onboarding and coaching loops

Inbound vs outbound AI SDR performance

Signal stacking and de anonymized website visitor handoffs

Hot, cold, and warm lead handling with AI

The 3 day inbound conversion rule

Customer service AI and NPS performance data

Ripping out Salesforce at a startup

Vibe coding with Lovable

Conversational CRM as the new interface

Build vs buy decisions for modern GTM stacks

AI adoption mistakes most GTM teams are making

Guest:

Gabe Larsen is the CRO of Atonom, host of the Talk AI podcast, and a veteran GTM operator with leadership experience at Customer (Meta), Inside Sales.com, Accenture, and Goldman Sachs.

Host:

Charles Brun is the host of GTM Hackers, a B2B video podcast focused on AI powered go to market strategies. He is also the founder and CEO of Everest.

If you are a founder, CRO, VP of Sales, GTM engineer, RevOps leader, or operator thinking about AI adoption, this conversation delivers both the big picture vision and the tactical details you need.

Follow GTM Hackers, rate the show, and share this episode with a GTM operator who needs to hear it. New episodes drop weekly.

Related topics: AI in sales, AI SDR, vibe coding, replacing Salesforce, autonomous organization, GTM engineer, agentic AI, cloud employees, RevOps, conversational CRM, build vs buy, AI adoption, signal based selling, Lovable, no code CRM.

A Google AI engineer built a fully functional Slack clone in 14 days using Claude Code — without manually writing or editing a single line of code. In this episode, Nathan shares the full story.

Nathan is an AI Engineer at Google who works with the company's largest enterprise customers to build generative AI solutions. He issued himself a public challenge: clone Slack in two weeks using only vibe coding and AI agents. He did it. The project — called Slawk — is open source, already has 250 GitHub stars, and has sparked a wide debate about the future of software engineering.

In this conversation with GTM Hackers host Charles Brun, Nathan and Charles break down exactly how it was built, what went wrong, what surprised him, and what it all means for founders and GTM leaders thinking about AI-powered product development.

What we cover in this episode:

1. Why Nathan decided to clone Slack as his side project challenge

2. The tech stack he chose and how he planned the architecture with Claude

3. How he used a browser-connected MCP agent to visually compare and clone Slack's UI

4. The 3-agent system he built: QA agent, Dev agent, and CTO orchestrator

5. How the QA agent filed GitHub issues with GIF screenshots — automatically — while Nathan slept

6. Test-driven development in a vibe coding workflow

7. The real cost of the project (under $200 total)

8. Why cloud infrastructure solves most scalability concerns critics raised

9. Why MCP servers make traditional app integrations obsolete

10. Nathan's vision for an AI-native Slack and why incumbents can't build it

11. The identity crisis behind anti-AI pushback in the software engineering community

12. Nathan's next project: QA as a Service

Nathan's key argument: only 1% of people can currently build software because they need to know how to code. Vibe coding is about to change that ratio dramatically. And the companies that figure this out first will have a significant competitive advantage.

If you are a founder, a GTM leader, or a builder exploring AI tools, this episode is one of the most practical and honest accounts of what vibe coding can actually do in 2025.

Find Nathan on LinkedIn — he replies to everyone in DMs. The Loc GitHub repository is linked in the show notes.

GTM Hackers is hosted by Charles Brun, a B2B SaaS go-to-market advisor and founder with 15 years of experience scaling revenue with AI. Follow GTM Hackers on Spotify to get notified of new episodes every week.

Related topics: Claude Code, vibe coding, agentic AI, multi-agent workflows, AI software engineering, Slack alternatives, open source tools, SaaS cost reduction, AI for startups, go-to-market AI strategy, MCP server, model context protocol, AI QA testing, building in public, AI product development.

In many startups, go-to-market breaks when the team scales: more tools, more handoffs, more chaos.

In this episode of GTM Hackers, Charles Brun sits down with Christian Lim, co-founder of Youno, to explain a more durable approach: start by building GTM infrastructure that is easy to maintain, then layer automation and AI agents on top.

You will learn:

1. Why tool sprawl creates a maintenance tax that slows teams down
2. How API-first choices make your GTM stack more resilient over time
3. The two common GTM failure points: misalignment and messy CRM data
4. How CRM deduplication and enrichment improve outbound execution and forecasting
5. How simple AI classification prompts can keep data structured (for example, company size)
6. How a Slack-native assistant can help reps find prospect details faster
7. A practical workflow to automate weekly client updates using Dust and ClickUp8) How to drive AI adoption with one internal champion and one high-impact workflow

Guest: Christian Lim (Youno)

Host: Charles Brun

Vibe coding is changing go to market faster than most SaaS teams realize. In this GTM Hackers episode, Charles Brun sits down with Noy Peleg and Sivan Butnaro  from Via to unpack how two non-developers built an internal app called Vira that replaced messy spreadsheets, synced with Jira, and is now saving teams hundreds of hours per week.

If you’re a founder, GTM leader, RevOps operator, program manager, or anyone trying to understand what AI means for internal tooling and GTM, this episode is a masterclass in starting from pain, shipping fast, and building adoption inside a real company.

AI in go-to-market isn’t a magic shortcut. It’s a precision engine, but only if your fundamentals are right. In this episode of GTM Hackers, Charles Brun sits down with Stephen Bates, Founder of Cabot Insights, to unpack what actually works when startups try to implement AI, automation, and GTM engineering.

They break down why most viral automation workflows fail in the real world. Teams move too fast, skip ICP definition, ignore data quality, and expect tools to fix broken foundations. Stephen shares how his team uses Clay and LLMs to enrich accounts, capture intent signals, and score ICP fit at scale, while keeping human judgment and feedback loops in the system so reps actually use the output.

Key discussion points:

- Why rushing AI adoption creates long term GTM problems

- Crawl before you run: data hygiene, CRM quality, and ICP clarity first

- How Clay enables micro segmentation, enrichment, and ICP scoring at scale

- Prompting strategy: specificity, strict outputs, and auditability for trust

- How to detect intent signals using real account signals

- Choosing models by ROI: lower cost scoring vs higher quality email generation

- Adoption and reinforcement: weekly AE feedback loops and enablement

Guest:Stephen Bates is the Founder of Cabot Insights, a GTM engineering agency helping high growth startups implement AI automation to improve outbound efficiency and lead quality. Stephen Bates brings experience from enterprise sales and the startup ecosystem, with a strong focus on ICP rigor and measurable ROI.

Follow GTM Hackers, share this episode with a GTM leader, and leave a rating if you want more deep dives on AI for go-to-market.

He uses this 90-day sprint framework to accelerate revenue🚀 What happens when a proven go-to-market strategy meets AI-powered automation? Spencer Tahil, founder of Growth Alliance, breaks down the exact 90-day sprint framework he uses to take early-stage startups from zero infrastructure to a fully operational, revenue-generating machine — with just two people.In this episode of GTM Hackers, Spencer pulls the curtain back on how he's helped Series A and Series B startups accelerate their sales pipeline, eliminate CRM chaos, and build scalable AI workflows — all while charging a premium and working his way out of a job in under six months.This isn't theory. This is a data-driven, battle-tested playbook from someone who's been inside the trenches of startup scaling for years.📌 WHAT YOU'LL DISCOVER IN THIS EPISODE🔹 The 3-sprint system Spencer uses to turn startup chaos into predictable revenue in 90 days🔹 Why most founders are buying AI tools for the wrong reasons — and how to stop wasting budget🔹 The #1 mistake killing startups before they even find product market fit🔹 How internal misalignment quietly destroys go-to-market momentum (and how to fix it)🔹 The real difference between "unorganized chaos" and "organized chaos" in startup life🔹 How Spencer runs 4 clients simultaneously with a team of just 2 — and delivers real results🔹 Why the smartest revenue operations leaders are designed to get fired🔹 The essential role of the go-to-market engineer and why it's the hottest position in SaaS right now⏱️ TIMESTAMPS0:00 — Intro & Welcome1:00 — Who Is Spencer Tahil & What Is Growth Alliance2:30 — How to Prioritize GTM Initiatives by Startup Stage5:00 — Testing Strategies Without Losing Revenue7:00 — Risk Tolerance, Investor Pressure & Realistic Goals9:00 — The 90-Day Sprint Framework Breakdown12:00 — Sprint 1: CRM Audit & Building Infrastructure14:00 — Sprint 2: Stress Testing & Gathering Data16:00 — The PMF Reality Check — When to Pivot vs. Scale18:00 — Why Internal Alignment Is Everything21:00 — Unorganized Chaos vs. Organized Chaos in GTM23:00 — Clay.com, GTM Engineering & The Future of Outbound25:00 — Passing the Baton: Who Takes Over After You Leave?28:00 — The Go-To-Market Engineer Role Explained30:00 — Real Failures: Buying Tools Instead of Strategy34:00 — How to Define Objectives, Activities & Desired Outcomes39:00 — Inside a Real Client Engagement Roadmap46:00 — How a 2-Person Team Runs 4 Startups at Once49:00 — Pricing, ROI & How to Pitch to Founders52:00 — The #1 Mistake Consistently Killing Startups55:00 — Final Thoughts & How to Connect with Spencer👤 ABOUT THE GUESTSpencer Tahil is the founder of Growth Alliance, a revenue activation consultancy specializing in AI-powered go-to-market engineering for high-growth startups. With years of experience in HubSpot, Salesforce, and marketing operations, Spencer helps Series A and B companies build scalable outbound sales systems, automate CRM workflows, and turn messy tech stacks into revenue machines. Find him on LinkedIn and YouTube.👤 ABOUT THE HOSTCharles Brun is a SaaS founder with 12+ years of experience scaling go-to-market teams. GTM Hackers is his show dedicated to interviewing revenue architects and uncovering the systems, tools, and strategies behind winning outcomes.💬 GOT THOUGHTS? Drop a comment below — we'd love to hear:👉 Are you using a sprint framework in your startup? What's working?👉 What's the biggest GTM challenge you're facing right now?🔔 Subscribe to GTM Hackers so you never miss an episode. Hit that notification bell!🔗 CONNECT & RESOURCESSpencer Tahil → LinkedIn: linkedin.com/in/spncertahilGrowth Alliance → YouTube:    / @growthalliance  Charles Brun → LinkedIn: linkedin.com/in/charlesbrunGTM Hackers → YouTube:    / @gtmhackers  #GoToMarketStrategy #StartupGrowth #AIAutomation #RevenueOperations #GTMHackers

AI-Powered GTM Engineering: How to Scale Revenue Without Overcomplicating Your StackAI-powered GTM engineering is changing how modern sales teams scale revenue — but most founders are doing it wrong. In this episode of Go To Market Hackers, we break down how to build high-ROI go-to-market systems using AI, automation, and outbound strategy without falling into the trap of over-engineered workflows.🎙️ Host Charles Brun sits down with Jorge Macias, founder of The GTM Engineering Company and former enterprise AE, to reveal what actually works in AI-driven go-to-market strategy, cold outreach, CRM automation, and revenue operations.🚀 What You’ll Learn in This EpisodeThis conversation goes beyond theory and dives into proven, real-world GTM execution, including:

• How AI is reshaping B2B sales automation and outbound prospecting

• Why complex GTM workflows often reduce ROI instead of increasing it

• The right way to inject AI into your go-to-market motion

• How to scale cold outreach without destroying deliverability

• Why “GTM porn” on LinkedIn is misleading founders

• How top GTM engineers prioritize speed, simplicity, and leverage

• The difference between workflows that look impressive vs. ones that drive revenue

• How to avoid single points of failure in RevOps and GTM systems

• If you’re a founder, RevOps leader, GTM engineer, or sales operator, this episode will help you discover a simpler, smarter way to scale revenue with AI.

⏱️ Timestamps / Chapters00:00 – What GTM Engineering Really Means02:45 – From Sales Rep to GTM Engineer05:20 – Why Most AI GTM Strategies Fail08:10 – Cold Outreach, Domain Warming & Deliverability11:30 – Simple vs Complex Workflows (ROI Breakdown)15:40 – Managing Founder Expectations in GTM18:30 – The Truth About “GTM Porn” on LinkedIn21:00 – Bundling Steps & Reducing Workflow Fragility25:10 – AI, Vibe Coding & the Future of GTM Engineering28:00 – Documentation, Training & Avoiding Single Points of Failure💡 Key Highlights & Takeaways✅ AI in go-to-market is no longer optional — but strategy matters more than tools✅ Simple workflows often outperform complex automations✅ Cold outbound still works when done systematically and ethically✅ GTM engineering is about leverage, not complexity✅ Founders should optimize for ROI, not visual impressiveness✅ Training and documentation are essential for scalable RevOps👤 Guest & HostJorge MaciasFounder, The GTM Engineering Company (https://www.gtm-engineering.io)Former SDR → AE → Enterprise AE with 10+ years in B2B sales, automation, and go-to-market engineering. Jorge specializes in AI-powered outbound systems, CRM enrichment, and scalable GTM workflows.Charles BrunFounder, Wizardly & Host of GTM Hackers podcast (https://trywizardly.com)Startup founder with 10+ years of experience scaling GTM teams at VC-backed companies, focused on revenue systems, RevOps, and AI-driven growth.📌 Who This Episode Is ForB2B founders & startup operatorsRevenue Operations & Sales Ops leadersGTM engineers & automation buildersAI-curious sales teamsAnyone scaling outbound, inbound, or RevOps systems🔔 Call to Action👉 Subscribe for weekly deep dives into GTM engineering, AI, RevOps, and revenue systems👍 Like if you want more practical, no-BS GTM content💬 Comment with your biggest GTM challenge or AI workflow question🔗 Resources & Links🎧 Listen to more episodes of Go To Market Hackers📈 Follow for GTM, RevOps & AI growth insights🤝 Interested in GTM engineering? Reach out to connect🧠 Keywords & Topics CoveredAI GTM engineering, go-to-market strategy, GTM automation, B2B sales automation, revenue operations, RevOps workflows, cold outreach strategy, AI sales tools, CRM automation, outbound sales, GTM engineer, AI in sales, scalable GTM systems, sales process optimization, startup growth strategy

📈 The Ultimate Guide to GTM Engineering, RevOps Systems & AI Workflows (with Oriol Serra)GTM engineering is transforming how modern revenue teams operate — and in this episode of GTM Hackers, we break down exactly how top companies are using systems thinking, automation, and AI to streamline their go-to-market motion. Whether you’re a founder, RevOps leader, or early-stage builder, this deep-dive will help you understand how GTM systems actually work, how to inject AI into your sales and marketing engine, and how to eliminate the operational bottlenecks slowing your team down. 🚀In this conversation, Oriol Serra (Founder of The Conversion Architects) reveals a practical, real-world view of GTM engineering, including: modern RevOps design, Clay workflows, data automation, deduplication systems, ICP mapping, outbound list building, AI validation workflows, CRM best practices, and how to think like a systems engineer — even if you’re not technical.⸻⏱️ Chapters & Timestamps00:00 — Intro: Who is Oriol Serra?01:00 — From customer service → sales → RevOps → GTM engineering02:30 — What is a GTM engineer? The real definition04:00 — Why revenue teams (marketing, sales, CS) are disconnected05:30 — Systems thinking vs. tool-thinking08:00 — How AI changes GTM orgs09:00 — Oriol’s process for mapping GTM systems12:00 — Defining terminology, handoffs & team workflows15:00 — Systems design before touching tools16:00 — Thinking like a programmer → GTM engineering framework18:00 — When AI shouldn’t replace humans in outbound20:00 — Building system SOPs & documentation24:00 — Why organization matters more than automation26:00 — Live Clay demo: ICP filtering, data enrichment, routing32:00 — How to score leads with AI models36:00 — CRM choices: HubSpot vs. Salesforce vs. Attio40:00 — Clay vs. N8N vs. Zapier vs. Make44:00 — Advanced Clay deduplication workflow49:00 — Why “boring automation” makes the most revenue50:00 — Who The Conversion Architects works with⸻⭐ Key Highlights — What You’ll Learn• What GTM engineering actually is (beyond buzzwords)• How to map your entire GTM system from marketing → sales → CS• Why system design must come before tools or AI automations• How to eliminate misalignment between teams using data flows• The step-by-step process Oriol uses to audit and rebuild GTM systems• How to automate outbound list building using Clay + AI• Why startups should avoid over-automating outbound messaging• How to build reliable ICP validation workflows with AI models• The exact approach to deduping CRM data at scale (HubSpot example)• How documentation & SOPs make GTM systems sustainable• Which tools matter most for early-stage teams (Clay, HubSpot, N8N)• How AI will reshape GTM operators into true systems engineers⸻👤 About the Guest — Oriol SerraOriol Serra is the founder of The Conversion Architects, a GTM engineering & RevOps consultancy helping tech companies automate systems, clean their data, and scale revenue operations with AI. He specializes in Clay automations, CRM architecture, and designing end-to-end GTM systems for SaaS companies.👉 LinkedIn: Oriol Serra -   / oriol-serra-tca  👉 Website: theconversionarchitects.com🎙️ About the Host — Charles BrunCharles is the creator of GTM Hackers, a podcast for founders, GTM leaders, RevOps operators, and anyone obsessed with scaling revenue through better systems and smarter workflows. He interviews the people building the future of GTM.👉 LinkedIn: Charles Brun -   / charlesbrun  👉 LinkedIn: GTMHackers -   / gtm-hackers  👉 Our Sponsor Wizardly: https://trywizardly.com/⸻🔔 Enjoyed the episode? Do this next:👍 Like the podcast💬 Comment your favorite insight📩 Share it with your RevOps or GTM team▶️ Subscribe for weekly deep dives on GTM, AI, and revenue automation#GTMEngineering #RevOps #GoToMarket

RevOps and AI: The New Operating System for High-Performing GTM TeamsRevOps and AI are transforming how modern GTM teams operate — and in this episode, we uncover what that actually looks like behind the scenes. I sat down with Yuval Bresler, Director of GTM Ops & Analytics at Yotpo, to break down how elite operators build scalable systems, blend AI into their workflows, and drive predictable revenue without chaos. If you’re trying to understand how AI is reshaping RevOps, outbound, and GTM execution, this is the episode you’ve been waiting for.In this conversation, Yuval shares the real work behind systems design: how to structure data pipelines, why bad processes sabotage automation, how to operationalize ICP, and what “good RevOps” actually looks like inside a fast-scaling SaaS company. We explore the intersection of AI, RevOps, GTM strategy, sales operations, automation frameworks, and pipeline generation — packed with insights founders and operators can apply immediately.⸻🔥 What You’ll Learn• How top operators integrate AI into RevOps workflows• Why most GTM problems have nothing to do with messaging — and everything to do with broken systems• How elite teams design scalable GTM architectures that support predictable revenue• The difference between bad automation and aligned, intentional automation• How Yotpo structures RevOps, analytics, and GTM operations• The role of RevOps as a strategic partner vs a support function• How to build data integrity, clean routing, and friction-free workflows• Practical frameworks for AI-assisted outbound, lead scoring, and enrichment• Why founders misunderstand RevOps — and how to avoid the most common traps⸻🧩 Timestamps00:00 – Intro01:12 – Why RevOps is broken at most startups04:45 – Systems design vs “fixing tools”08:10 – How AI is transforming RevOps workflows12:39 – The biggest mistake teams make when adding automation16:02 – GTM architecture: mapping handoffs & data pipelines19:55 – Operationalizing ICP: from theory to execution25:40 – AI in outbound: enrichment, scoring, and validation30:15 – Building trustworthy forecasts and data structures35:22 – What founders get wrong about RevOps41:56 – Yuval’s frameworks for scalable GTM systems47:18 – Final takeaways⸻🎙️ About Our Guest — Yuval BreslerYuval is the Director of GTM Ops & Analytics at Yotpo, where he leads RevOps strategy, systems architecture, analytics, and cross-functional alignment across sales, marketing, and CS. With deep experience in data modeling, automation, and GTM design, he’s one of the most thoughtful operators in the RevOps space — and a leading voice on how AI and RevOps intersect inside high-growth SaaS companies.⸻🚀 Key Topics Covered• RevOps and AI• GTM operations• Sales operations & sales architecture• AI-powered automation• Workflows, routing & enrichment• Data integrity & pipeline modeling• Outbound systems & ICP frameworks• Predictable revenue engines• SaaS GTM strategy• Founder mental models for scaling⸻🙌 If you enjoyed this episodePlease like, comment, and subscribe — it helps us bring more operators, GTM leaders, and RevOps experts to the show.Tell us in the comments: Which GTM or RevOps challenge should we cover next?⸻🔗 Connect With UsCharles Brun👉 LinkedIn: Charles Brun -   / charlesbrun  👉 LinkedIn: GTMHackers -   / gtm-hackers  👉 Our Sponsor Wizardly: https://trywizardly.com/Yuval Bresler👉 LinkedIn:   / yuvalbresler  👉 Yotpo: https://www.yotpo.com/

In this RevOps strategy podcast episode, we dive deep into how large, global SaaS companies operationalize AI, structure revenue operations, and build scalable GTM systems. If you want to understand how world-class RevOps teams think, this conversation with Shir Guterman (AppsFlyer) is packed with frameworks, playbooks, and real-world examples.Shir leads Revenue Operations across EMEA & LATAM at AppsFlyer — one of the biggest, most data-driven SaaS companies in mobile marketing analytics. In this episode, she breaks down how to design global go-to-market alignment, unify qualification frameworks (like MEDDPICC), implement AI responsibly, and build a well-oiled GTM engine inside a 1,500-person company.⸻🔍 What You’ll Learn in This EpisodeThis episode is a masterclass in modern RevOps, GTM engineering, and AI-driven go-to-market strategy, including:• How enterprise GTM teams structure RevOps organizations across global regions• The biggest mistakes companies make when adopting AI in sales, SDR workflows, and pipeline management• Why strategy, process, and data foundations matter more than tools• How AppsFlyer uses account planning, unified qualification (MEDDPICC), forecasting, and Gong analytics• What an effective AI task force looks like inside a global revenue org• The evolving concept of “source of truth” (Salesforce vs. Gong vs. BI tools vs. LLM interfaces)• How to operationalize personalization at scale for enterprise outbound• Why RevOps needs both business architects and technical operators• How global teams cascade strategy top-down and bottom-upThis is the episode for anyone searching for:revops strategy podcast, GTM strategy, AI in RevOps, revenue operations frameworks, GTM engineering, B2B SaaS operations, MEDDPICC training, SDR AI workflows, account planning with AI, pipeline accuracy, forecasting AI tools, AppsFlyer GTM.⭐ Key Highlights• The RevOps role is evolving into a hybrid of systems architect, strategist, and data operator.• AI should enhance a strong GTM strategy — not define it.• Global SaaS companies need a mix of top-down direction and bottom-up GTM innovation.• Tools matter less than process clarity, alignment, and data integrity.• SDRs are moving toward hyper-personalization powered by AI, not volume.• AppsFlyer’s RevOps team uses custom GPTs to unify data from Salesforce, Gong, platform data, and web sources.👤 Guest: Shir Guterman (AppsFlyer)Revenue Operations leader covering EMEA & LATAM at AppsFlyer. Formerly led GTM & operations at DataGen, with deep expertise in RevOps architecture, GTM systems, AI enablement, and enterprise sales operations.🎙️ Host: Charles BrunSaaS founder, GTM strategist, and longtime leader of revenue teams across venture-backed startups. Creator of GTM Hackers, the podcast exploring how the best GTM engineers build systems that scale.⸻🔗 Connect & ResourcesLinkedIn — Shir Guterman:   / shir-guterman-ramot-4467a058  LinkedIn — Charles Brun:   / charlesbrun  Show sponsored by Wizardly: https://trywizardly.com/⸻🔥 Hashtags#RevOps #GTMStrategy #B2BSaaS