I just spent two weeks tracking what's actually working in B2B GTM vs. what we wish was working. The gap is wider than ever, wider than Grand Canyon and that stuff is BIG. Here's the uncomfortable reality no one's talking about: → AI SDRs sound great in demos, fail spectacularly in production → Most GTM systems are built around the wrong buying signals → Your "perfect" RevOps stack might be accelerating your decline → Every GTM playbook has an expiration date (and yours just expired) But some teams are quietly crushing it. They're not chasing #AI #hype. They're engineering systems around actual buyer behavior. I analyzed 18 posts from operators shipping real results: Stan Rymkiewicz's AI copywriting workflow that scores 0% on AI detectors Janis Zech's findings after talking to 450+ RevOps leaders about GTM AI Lillian Pierson, P.E.'s wake-up call: "GTM Engineer" isn't BS—it's real Jamie Walsh's brutal truth: systems don't fix unclear signals Dimitar Stanimiroff on why every playbook breaks (and always will) The pattern? Winners aren't building bigger stacks. They're finding clearer signals. They're not replacing humans with AI. They're making humans 10x more effective. They're not following last year's playbook. They're rebuilding for the environment that exists today. This week's newsletter breaks down: ✅ What AI can and can't actually do in GTM (with receipts from 450+ teams) ✅ The 5-step workflow that creates AI content that doesn't suck ✅ Why your buying signals matter more than your CRM ✅ How to measure ABM with a simple 50/50 split test ✅ The discovery framework that actually qualifies deals ✅ Why "GTM Engineer" is now a real role at 89+ startups ✅ What your 2026 budget should actually be (by sector) If you're frustrated with GTM right now, it's not you. The old playbooks died. The new ones are being written by operators who understand one thing: Clarity creates compounding. AI just accelerates it. 📬 Full breakdown in this week's newsletter (link in comments) What's your biggest GTM frustration right now? P.S. Shoutout to Scott Finden, Yurii Veremchuk, Janis Zech, Stan Rymkiewicz, Jamie Walsh, Tim Busschops, Dimitar Stanimiroff, Lillian Pierson, P.E., Canberk Beker, David Zeledon, Sumit N., Jen Allen-Knuth, Dan Ptak, Andrei Zinkevich, Kate Syuma, and Kieran Flanagan for the insights that made this newsletter possible.

Been excited to be at the Tekpon conference! Although I had some serious cold and fever the night before :( and missed on a lot of great convos. Some hot insights for you like my tea this morning. AI scales the playbook — but relationships still close enterprise deals. The new norm is at least 1 million $ per employee. Sara Maldon was talking about some pretty cool automations you can pull with make.com, cut the research time and increase the customer facing time with clients. Vincent Jong gave some good benchmark on how efficiency should look like in the AI first world. Also a very helpful table about what AI can do well and what it cannot do well. Frank Sondors 🥓 Bill Stathopoulos Jeko Kolev had a pretty cool conversation about AI's role in today's #GTM strategy. Todd Paris came with some incredible insights on difference in terms of ranking factors for LLMs, what do they like, their personality and how to optimize for that. Some personal thoughts: Found: AI wins when it automates sales ops (post-call follow-ups, CRM enrichment, research), freeing reps to focus on human conversations. Realized: ABM + co-created content = faster access to decision-makers and higher-quality pipeline. Identified: First‑party signals (hires, multi‑language site relaunches, investor moves) drive better account selection than noisy intent feeds. Found: Enterprise buyers want bulletproof solutions — GDPR, SOC2, and provable ROI beat flashy demos every time. Realized: ICP clarity is non‑negotiable — know who uses the product vs who signs the check (marketing vs CFO/ops). Identified: Product‑led, API‑first businesses that prioritize engineering scale revenue per employee and reduce dependence on large sales teams. Noted: Top-of-mind benchmark — aim for ~$1M revenue per employee in AI-first product companies; anything less risks being out-competed on efficiency and cost structure. Credibility quote: “AI helps SDRs by doing the grunt work — prospect research and CRM enrichment — but it doesn’t replace the relationship you need to close enterprise deals.” This left me with a question: If you’re scaling #GTM with #AI this year, are you prioritizing automation or proving measurable ROI to finance — and how are you or are you tracking revenue-per-employee as a success metric?

In this newsletter, I'm bringing you, as usual, the most actionable and truthful stuff I've found over LinkedIn, Twitter, and Substack. Subscribe more to get more insights and learn something. I hope you do learn something from this. Really! P.S. There are a few good tips, such as: Why you should have three potential lists in your ABM outreach How you can design a workflow which will help your product-led growth

Most salespeople with long sales cycles are losing deals they've already started. You spent months building relationships. Had great conversations. Then... silence. The prospect goes dark. You move on. But here's the thing—they're still in-market, still have the problem, still need a solution, life is just too effing busy. You just fell off their radar. I personally effing hate this! If somebody does not answer, I feel a huge disrespect, in case like this I have to tell myself, calm Stefan! They did not mean to hurt you! To solve this I've been testing Extrovert for the past few months and it's solving a massive problem: keeping deals alive that would otherwise die in your CRM. Here's what actually works for long sales cycles: 1- Restart conversations with leads you've forgotten about The biggest mistake in enterprise sales? Assuming a dead lead is actually dead. ↳ Every week I'm getting 5-10 active conversations restarted with leads I'd completely forgotten about. ↳ The tool analyzes your existing conversations and suggests natural ways to re-engage. ↳ It's not cold outreach—it's rekindling relationships that already exist. ↳ These aren't new leads. They're warm opportunities you already invested time in. This alone has changed how I think about pipeline management. 2-Influence through strategic commenting (not just direct outreach) Robert Cialdini taught us the difference between persuasion and influence. You can't just pitch—you need to be visible. ↳ GoExtrovert identifies which prospects in your pipeline are posting content. ↳ It suggests thoughtful comments in your voice (not generic AI garbage). ↳ Your prospects see you're engaged, knowledgeable, and present. ↳ This works especially well with consultants who get high visibility. When your ICP sees you commenting intelligently on their feed, you're building influence before the next call. 3-Pair your comment strategy with cold outreach Here's what most people get wrong: they think commenting OR outreach. It's AND. ↳ Use commenting to warm up cold accounts before reaching out. ↳ Stay visible to existing deals through consistent, valuable comments. ↳ Create multiple touchpoints without being annoying. ↳ Think of it as air cover for your ground game. The best results come from an integrated approach—not choosing one channel. 4-Organize prospects by who you need to influence vs. sell to Not all prospects serve the same purpose in your sales motion. ↳ Some are decision-makers you need to close. ↳ Others are influencers (marketing, sales leaders) who can advocate for you. ↳ Create separate lists and engage differently with each group. ↳ Track posting frequency to prioritize who to engage with. I'm doing a webinar soon with Oleg Sobolev from Extrovert where we'll dive deep into: → Restarting old conversations that went cold → Rekindling closed/lost opportunities → The new LinkedIn commenting strategy and how to maximize results Stay tuned for details.

The 417 Touchpoint Reality Most B2B companies are failing at math. HockeyStack just dropped data that should terrify every marketer: It takes 417 touchpoints and 5,493 impressions to generate deals over $100k. Most ABM playbooks account for maybe 5-10% of that. The uncomfortable truth? → The pipeline you're trying to close this quarter started 9+ months ago → By the time someone agrees to a demo, 70% of their decision is already made → If you're not on the buyer's shortlist when they START researching, your odds drop below 10% What works in 2026: ✓ Always-on playbooks that generate 1st party signals ✓ Time-based playbooks that build on each other ✓ Signal-based touchpoints (hiring, management changes, content engagement) ✓ Fully personalized 1:1 for active focus accounts Stop building for the buying cycle you think exists. Build for the messy, 9-month reality where decisions are made long before the first demo. All of this and more in my newsletter! Part 1. #ABM #B2BMarketing #DemandGeneration