Insights · Field Notes
Notes from inside the machine.
What we learn building AI into B2B revenue engines, written down while it is still specific. Opinionated, practical, and useful without a call. No list to join: the feed is RSS, and the concierge answers questions about any of it.
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The AI GTM Landscape, 2026We mapped 168 AI tools that B2B revenue teams buy, in 15 categories that follow a deal from the first contact record to the renewal. Selected, not ranked, and nobody paid to appear. The poster, the full list as a CSV and an embed code are free.
AI Lead Scoring That Sales Will Use: Six Decisions Before the ModelMost lead scoring projects fail before any model is trained, on six decisions nobody wrote down: what the score predicts, what changes because of it, what data it may use, how it explains itself, and how you will know it works.
Slow Lead Response Is Rarely the Rep: The Timeline AuditWhen follow-up is slow, the rep gets the blame. Rebuild the timeline of a lead from form submit to first touch and the delay usually sits in the gaps between systems. Five gaps, how to measure each, and the fix.
The Week-One CRM Data Audit Before Any AI Touches Your PipelineRecommendations built on unaudited data are guesses with better fonts. The six checks we run inside a CRM in the first two weeks of an engagement, what each one usually finds, and the fix that lasts.
The State of AEO in B2B SaaS, 2026We ran 274 well-known B2B software companies through the same reader a buyer's AI assistant uses. 61% now publish an llms.txt, 76% carry structured data, only 4% block an AI crawler, and one in twelve could not be read at all. The numbers, the category gaps, what a model actually sees in the first 5,000 characters, and what to fix first.
What a Buyer's AI Sees When It Reads Your HomepagePaste your homepage into an assistant with no context and ask what the company does. The answer is what buyers hear when they ask ChatGPT, Claude or Perplexity about you. Here is how to run that cold read in one click, what the common gaps look like, and how to close them.
AEO for B2B: The Four Checks That Decide Whether AI Can Find YouBuyers ask ChatGPT, Claude, and Perplexity before they search. Four deterministic checks (llms.txt, AI crawler access, structured data, sitemap hygiene) decide whether those assistants can read your company, and what they say when they cannot.
The Five Questions Deal Teams Skip in GTM Due DiligenceData rooms answer the questions they were built to answer. The five that decide whether a revenue engine is real (invoice-level retention, aged pipeline, founder gravity, paid-spend dependence, CRM-to-billing reconciliation) are the ones deal teams routinely skip. Here is why, and what to ask for instead.
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