How I spent $18K on AI sales tools and found the best 16

I wasted $150k testing 100+ AI sales tools so you don't have to. Here's the exact 25-tool stack that took us to $6M ARR: AI Agents → Relevance AI (Agent Builder) → Claygent (Research Agent) → Instantly.ai (Reply Agent) → Artisan (AI SDR) Sales Engagement → lemlist (Multi-channel) → Instantly.ai (Cold Email) → Valley (LinkedIn AI SDR) → Expandi.io(LinkedIn Outreach) Data Enrichment → Clay → Wiza → FullEnrich → Prospeo.io → LeadMagic Data Sourcing → Exa → Apollo → Ocean.io → Openmart → LinkedIn Sales Navigator Data Scraping → Apify → Firecrawl → Instant Data Scraper Intent Signals → Clay → Common Room Visitor Identification → RB2B → Vector 👻 → Midbound Workflows → Clay (GTM Workflows) → AirOps (AI SEO Workflows) → n8n (General Automations) → Default (Inbound Workflows) MCPs → Claude Sales Assistants → Attention → Momentum.io Messaging → Twain → Octave CRM → Attio → HubSpot → Breakcold Always keen to try out new tools, what tools would you recommend?

Alex, but what if you could replace all of this with minimal tech? Instead of a $150k labyrinth of overlapping tools, imagine running lean with surgical precision Humantic AI / Miaa → account-level research + DISC profiling of decision-makers BitScale → clean contact enrichment without the bloat Closed Circuit Selling™ (CCS) → the operating system that validates markets, interprets first-party intent signals, and closes the loop so nothing leaks (And another coming soon with something you have never seen before) That stack doesn’t just cut cost…It collapses complexity. You’re left with market validation, true signal discipline, and a repeatable revenue circuit. I spent the years and the scars so founders don’t waste cycles stacking 25 tools when 3 will do the job better. Sometimes less tools + more architecture is what actually gets you to scale. Cut the commercial leakage. #B2B

Doubled sales outreach with a single AI workflow. Imagine what it could do for your pipeline. The uncomfortable truth: most companies waste time on manual research and messy CRM tasks. I see it every day. I architected an AI-powered workflow that changed everything for my GTM motion. Here’s what happened: – Automated research on every target account – Personalized outreach at scale (without losing quality) – Unified sales and technical knowledge in one system The result? More qualified conversations. Faster pipeline growth. Less busywork for the team. Most GTM teams still treat AI as a buzzword. The best ones use it to experiment, iterate, and measure impact, fast. Here’s the difference: → Old way: Add more SDRs, hope for results → New way: Run experiments with AI, track outcomes, scale what works Technical excellence isn’t just a nice-to-have. It wins deals. When you build GTM systems that deliver real results, you change how revenue teams operate. I’m proud of what we achieved with this AI workflow. It proved that smart engineering, plus bold experimentation, moves the needle. Curious how you’re using AI to redefine your outreach? Let’s talk about what works (and what doesn’t) in your GTM playbook.

Your outbound playbook isn’t broken. It’s trapped in messy CRMs. AI agents can unlock it. Most teams have the right strategy—but their best data is locked away. The uncomfortable truth: Even world-class GTM plans fall flat if outreach is generic and disconnected. Here’s how I solved this: I built the AI Agent Playbook—a framework for designing, testing, and scaling multi-functional agents inside Clay workflows. These agents do more than automate: → Research fresh leads, surfacing unique data points competitors miss → Personalise outreach at scale, using context from job changes, funding, and psychographics → Activate pipeline with ultra-targeted messaging, not just “first name” mail merges The result? Teams move from “spray and pray” to systematic, context-rich outbound. (Seen it firsthand. Verkada, Rippling, and others are already running this way.) What makes the Playbook different: – It’s not just automation. – It’s a repeatable system for building semi-autonomous revenue engines. – It unlocks both scale and effectiveness—without drowning in CRM chaos. Here’s the difference: ✅ Predictable growth ✅ Outreach that actually lands ✅ Revenue teams focused on value, not manual busywork Want to see the Playbook in action? Curious how AI agents can transform your GTM pipeline? Drop your thoughts below or DM me for a deeper dive into the full framework. How are you unlocking outbound potential with AI agents? 🚀 #GTM #AI #Clay #SalesEngineering #Outbound #RevenueEngineering

AI was everywhere at HubSpot’s Fall Spotlight. Breeze Agents. Customer Agents. Prospecting Agents. Data Hub. But here’s the thing: most HubSpot users don’t need more AI right now. They’re still struggling with the basics: – Defining their Ideal Customer Profile (ICP) – Crafting a clear value proposition – Getting their positioning and messaging right – Building a structured sales process – Designing a content strategy that actually attracts leads In other words: you can’t scale chaos. If your foundations are shaky, AI will just help you scale bad data, bad messaging, and bad processes faster. Before you plug AI into your CRM, make sure you’ve nailed the fundamentals: ✔ Customer research ✔ Market segmentation ✔ ICP + tiering ✔ Buyer’s journey ✔ Content plan ✔ Lead definitions ✔ Website sitemap ✔ Sales process ✔ Customer success strategy Do these first, and you’ll have clean data, strong messaging, and clear processes so AI can actually accelerate growth instead of multiplying noise. 👉 My takeaway from HubSpot’s AI news: AI is not a replacement for strategy. Get the foundation right, and then AI becomes transformational.

We wasted thousands of $ testing dozens (!) of AI sales tools in the last 12 months. Most were shiny objects. A few were game-changers. And here’s the truth: 👉 Even the best tools are useless if you don’t stack them correctly. Here’s an example tech stack that we use to automate lead research and cold outbound: 1/ Data that wins deals Bad data = dead campaigns. Period. Databases: Apollo, LinkedIn Sales Navigator, Ocean.io Niche: Openmart for local focus Scraping: Apify, Instant Data Scraper Intent: Clay, Common Room AI Agents: Exa, Relevance AI, Claygent, Linkup 2/ Verified enrichment Fake emails = wasted time + wrecked domains. Point solutions: Prospeo.io, LeadMagic, Wiza Waterfall: FullEnrich, Clay 3/ Scalable engagement Multi-channel outreach that compounds pipeline. Email: Instantly.ai LinkedIn: Expandi, Valley Hybrid: lemlist 4/ Closing system Because pipeline means nothing if you can’t close. CRM: Attio, Breakcold Intelligence: Attention, Momentum.io 🚨 Out of 1,200+ AI sales tools in 2025… These are a few that ACTUALLY matter — but only when combined in the right way. The unfair advantage isn’t in buying tools. It’s in orchestrating the stack. What’s the last tool you added to your stack? #gtm #gtmengineering

AI will break weak funnels faster. ⚠️ Those funnels that merely narrow prospects down. 🔻 It’s a leaky pipe, not a funnel. … and AI will only exacerbate the leak. Funnels should guide and sort leads, not merely filter them out. Vlad Gozman and his team at involve.me are custom-building that kind of funnel. Adaptive and interactive systems that usher each prospect to the right destination. That funnel is built on – Interactive forms that feel like conversations – Conditional logic that adapts based on answers – Clear routing rules that decide “who goes where” – Integrations with CRMs, HR systems, and other tools As a result, – Prospects feel like they’re being helped, not herded. – Teams get context-rich data, not just email addresses. – Leads are routed instantly to the right owner. Only when this foundation is in place should AI step in. Only then does AI make sense because it scales efficiency, not leaks. Thanks, Vlad, for sharing your insights! We also talked about how he bootstrapped his company to 7-figure ARR in just a few years and earned the trust of 4,500+ companies worldwide– including BCG, Salesforce, and Universal Studios. Interested in getting free access to playbooks, people, and in-person dinners like these? 👉 If you're a B2B Scaleup founder or in VC/PE/M&A, we'd love to invite you to join our community here: https://lnkd.in/eC_7bUh5 Will be sure to share the full conversation with Vlad to the private (but free) community: https://lnkd.in/eC_7bUh5

INBOUND 2025 wrapped with one clear message: AI is no longer a concept. It’s here, practical, and ready to use inside HubSpot. What stood out most for me: • Breeze Agents – AI teammates handling research, SEO clean-up, and support tasks. • Data Hub – unify and trust your customer data in one place. • The Loop – that smart cycle: Express → Tailor → Amplify → Evolve. • AI CPQ – quotes that nearly build themselves. • Workspaces – your AI-powered home within HubSpot. Last year, AI felt overwhelming. This year, it’s intuitive. These updates don’t replace people, they empower them. I’ll be breaking each one down next week, one email, one feature, one real-world idea. Stay tuned.

🔍 Why companies using AI bots are pulling ahead — and how you can do the same (without overcomplicating it). As someone who implements AI bots end-to-end, here’s a breakdown of how they directly drive profit: 💬 1. 𝐍𝐨 𝐥𝐨𝐬𝐭 𝐥𝐞𝐚𝐝𝐬 AI bots reply instantly — even at night or on weekends. 📈 One client saw a +40% increase in inquiries just by speeding up first response time. 🤖 2. 𝐒𝐚𝐥𝐞𝐬 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 AI bots can: -Qualify and segment leads -Recommend the right offer -Send payment/booking links -Follow up automatically ⚡ Result: 𝒍𝒆𝒔𝒔 𝒑𝒓𝒆𝒔𝒔𝒖𝒓𝒆 𝒐𝒏 𝒔𝒂𝒍𝒆𝒔 𝒕𝒆𝒂𝒎𝒔, 𝒎𝒐𝒓𝒆 𝒅𝒆𝒂𝒍𝒔 𝒄𝒍𝒐𝒔𝒆𝒅. 💰 3. 𝐋𝐨𝐰𝐞𝐫 𝐬𝐭𝐚𝐟𝐟𝐢𝐧𝐠 𝐜𝐨𝐬𝐭𝐬 One well-set-up bot can: -Handle hundreds of chats at once -Work 24/7 without breaks -Stay error-free 🌟 4. 𝐁𝐞𝐭𝐭𝐞𝐫 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 AI bots are always: -Polite -Fast -Consistent 🎯 Happier customers → more repeat sales → 𝒉𝒊𝒈𝒉𝒆𝒓 𝑳𝑻𝑽. 📊 5. 𝐃𝐚𝐭𝐚 & 𝐢𝐧𝐬𝐢𝐠𝐡𝐭𝐬 We set up analytics so the bot tracks: -Common questions -Objections -Drop-off points 💡 This helps improve your product, scripts, and funnel. 🔧 𝐇𝐨𝐰 𝐰𝐞 𝐰𝐨𝐫𝐤: ✅ Deep dive into your business and goals ✅ Build the conversation logic and train the bot on your data ✅ Integrate with your site, socials, CRM, messengers ✅ Set up analytics and train your team ✅ Support you post-launch 📩 Curious how much revenue you're leaving on the table 𝒘𝒊𝒕𝒉𝒐𝒖𝒕 𝒂𝒏 𝑨𝑰 𝒃𝒐𝒕? 𝑫𝑴 𝒎𝒆 — 𝑰’𝒍𝒍 𝒘𝒂𝒍𝒌 𝒚𝒐𝒖 𝒕𝒉𝒓𝒐𝒖𝒈𝒉 𝒓𝒆𝒂𝒍 𝒆𝒙𝒂𝒎𝒑𝒍𝒆𝒔 𝒇𝒓𝒐𝒎 𝒔𝒊𝒎𝒊𝒍𝒂𝒓 𝒃𝒖𝒔𝒊𝒏𝒆𝒔𝒔𝒆𝒔.

I just finished creating a GTM workflow guide that shows exactly how teams are saving $500K+ annually with Zapier AI Agents. Want access? Here's what's inside: • Teams saving 500+ hours/year • 15-30% conversion improvements • 28% ticket deflection rates • Real company data (not projections) But the game-changer? Step-by-step tutorials. Like this 8-step process to build your first AI agent: 1. Create agent in Zapier 2. Define its purpose 3. Give it tools 4. Test the workflow 5. Connect to your apps 6. Set triggers 7. Monitor performance 8. Scale what works Real workflows I documented: RevOps Automation: Lead hits website  → AI enriches data  → Scores intent  → Routes to right rep  → Books meeting  → Updates forecast Result: Company processes 20% more deals with same team SDR Force Multiplier: New lead  → AI researches company  → Finds decision makers  → Crafts personalized outreach  → Tracks engagement  → Alerts for hot leads Result: 40% time savings on qualification Customer Success at Scale: Support ticket  → AI categorizes  → Checks knowledge base  → Drafts response  → Human approves  → Customer happy Result: Vendasta saves $1M+ annually The guide includes: ✓ Workflow diagrams you can copy ✓ ROI calculators for each department ✓ 8-week implementation roadmap ✓ Integration blueprints ✓ Success metrics dashboard Comment "ZAPIER" to get the complete GTM Workflows Guide. Or you can get it here: https://lnkd.in/ggKth-6t Lets stop focusing on if AI will replace your team and focus more on multiplying their impact. Your competitors are still doing this manually. That's your opportunity. #GTM #AI #Revenue #zapier