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The average LinkedIn outreach campaign gets about 1 reply in 10. Our micro campaigns for a B2B services firm got 7 to 9 in 10. Here's how we build a micro campaign: tens of people, one strong shared signal, a message that names it, and a small offer. Then a setter team turns the replies into booked calls.
Roman J. Georgio
Tell us who you sell to. We'll pull the pain themes your buyers raise in Reddit discussions, show how often each comes up, and link you to the threads.
Every revenue channel has a period where it is underpriced, underexploited, or not yet saturated. Whoever finds that window first gets an advantage, whoever executes it better turns the advantage into revenue, and whoever systemises it makes the whole thing repeatable. Traders have had a word for this for a long time, and alpha turns out to be the most useful way to think about gtm as well.
Roman J. Georgio
Fit tells you which companies could buy. Only a signal tells you when. A buying signal is a change, at a named company, on a known date, that you can go and check for yourself. This is the full landscape of 27 signal types in nine groups, the public record behind each one, and why several signals landing on the same company inside a week is the thing worth acting on rather than any single alert.
Harshil Jani
Most teams calling themselves AI-native are at L1. It's the same scattered go-to-market, just typing faster. The AI Maturity Framework has six rungs: Manual, Assisted, Integrated, Owned, Connected, Autonomous. Each rung has a specific wall above it. No context graph, no named owners, no command centre, no trust in long-horizon loops. Locate your rung honestly, find the wall directly above you, and build the one thing that clears it. Adding more agents is the generic wrong move at every level.
Sebastian Lourenço
Marketing leaders are experimenting with AI agents but building in silos. The true advantage comes when you have a clear strategy. From AI-assisted persona targeting to competitor signal scanning, these 10 applications show how a unified agent layer transforms B2B marketing performance.
Sebastian Lourenço
Four intimate technical workshops over six weeks. How we got senior engineers from Google, JPMorgan, Airbnb, and Snapchat in a room for CoralOS — four times — and turned attendance into a distribution pipeline.
Sebastian Lourenço
Generic AI content has four causes: training data distribution, RLHF typicality bias, probability mechanics, and the writer's prompt. Only the last one is under your control — and context engineering is how you fix it.
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