Fabiano Di Tomaso

Fabiano Di TomasoSep 17, 2026

Another growth question in my linkedin inbox... But before I can answer it, I need to know one thing: 𝘄𝗵𝗮𝘁 𝘀𝘁𝗮𝗴𝗲 𝗶𝘀 𝘆𝗼𝘂𝗿 𝗰𝗼𝗺𝗽𝗮𝗻𝘆 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗶𝗻? Not because the answer is hard. Because GTM is not one job. Different stage = different job. I learned scaling a fintech from a few '00K to $7M ARR, growing from near-zero to 150+ people, while launching multiple 0→1 products. That’s why static growth playbooks break down. The tactic is not "wrong". It’s just doing the wrong job for where you are. Here is how I see maturity stages: 1. 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 → reduce uncertainty → optimize for learning speed 2. 𝗚𝗧𝗠 𝗙𝗶𝘁 → prove the motion → optimize for conversion + retention quality 3. 𝗦𝘆𝘀𝘁𝗲𝗺𝗶𝘇𝗲 → turn what worked into a system → optimize for repeatability 4. 𝗦𝗰𝗮𝗹𝗲 & 𝗘𝘅𝗽𝗮𝗻𝗱 → increase throughput → optimize for leverage → Founder-led is what you need early… then becomes bottleneck. → Multi-channel is great… after you understand the customer. → Process helps after signal, not before. You can work insanely hard and still underperform by optimizing for the wrong goal. 𝗤: Which is more expensive: scaling too early, or staying founder-led too long? ___ 🔔 FOLLOW Fabiano Di Tomaso ♻️ REPOST to help others 💾 SAVE to find it later

Fabiano Di TomasoSep 14, 2026

Last week a founder shared a slide celebrating 112% NRR. But when we looked at the dashboard, 22% of their starting revenue had walked away 😬 This is the danger of relying on headline outcomes. They hide the system underneath. To see how... Let's imagine two companies. Both start the quarter with $100 in recurring revenue: 𝗖𝗼𝗺𝗽𝗮𝗻𝘆 𝗔 → loses $5 to churn / contraction → gains $17 in expansion = 95% GRR, 112% NRR 𝗖𝗼𝗺𝗽𝗮𝗻𝘆 𝗕 → loses $22 to churn / contraction → gains $34 in expansion = 78% GRR, 112% NRR Same NRR. Different retention dynamics, i.e. Gross Revenue Retention (GRR). One company is retaining most of the base, then compounding through expansion. The other is losing much more of the base and relying on expansion to offset the leakage 👀 Neither is "good" or "bad" by default. But they are not the same business. Don’t stop at "Is our NRR good?" Ask instead: "What happened underneath to produce this NRR?" Interpret NRR along with: → GRR → logo retention → cohort behavior → revenue concentration The metric reports the outcome. The underlying system determines whether that outcome is 𝗥𝗘𝗣𝗘𝗔𝗧𝗔𝗕𝗟𝗘. ___ ♻️ REPOST to help others 💾 SAVE to find it later 🎙️ COMMENT, share your take 🔗 VIEW my FREE newsletter: https://lnkd.in/dcNyj--P

Fabiano Di TomasoSep 16, 2026

I’m auditing a scaling team right now that can ship 10x faster than last year... but most of them are just producing 10x more waste. Because when execution gets cheap, your upstream mistakes - strategy, priority, focus - get expensive. Meaning: we know speed is not the constraint anymore. Definition is. "Faster" on a weak operating system looks like: → 𝗠𝗼𝗿𝗲 𝗰𝗮𝗺𝗽𝗮𝗶𝗴𝗻𝘀, less signal on the real customer problem → 𝗙𝗮𝘀𝘁𝗲𝗿 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀, no idea which metric deserves attention → 𝗠𝗼𝗿𝗲 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝘀, no clue which constraint to address first AI on top of a broken system doesn’t create leverage. It just creates FASTER CHAOS. The fix is not "more prompts." It's better judgment, EARLIER. 𝗤: Is "execution speed" still a competitive advantage when anyone can ship 10x faster with AI? ___ 🔔 FOLLOW Fabiano Di Tomaso ♻️ REPOST to help others 🎙️ COMMENT, share your take