GTM Atlas — Build your GTM brain

Author: Maja Voje, Founder of The GTM Strategist, author of Go-To-Market Strategist
Source: atlas.attio.com/build-your-gtm-brain
Date: May 6, 2026

Who is Maja Voje

Best-selling author of Go-To-Market Strategist — methodology adopted by 10,000+ companies worldwide. Fifteen years driving growth from Google to Heineken, scaled 850+ startups. Now advises B2B teams on GTM AI strategy.

Core Thesis

Every early-stage team is now competing in a sea of sameness — same AI tools, signals, and outbound. Open LinkedIn and 70% of what you see is AI-generated.

The teams pulling ahead are building systems that compound: a persistent GTM brain that gets smarter over time, pointed at the right customer, sending the message that actually cuts through.

Prompting is the worst way to use Claude. Context engineering is the real unlock.

The GTM Brain Architecture

A team still prompting is running a chatbot. A team doing context engineering is running a brain.

The GTM brain has five components:

  1. CLAUDE.md file — the single most important file: ICP summary, positioning, current priorities. Keep it short and scannable.
  2. Context files — GTM strategy in structured form: signal libraries, competitive battlecards, messaging matrices.
  3. Skills — markdown files that tell Claude how to run specific tasks using that context (account research, ICP scoring, signal-to-sequence).
  4. Workflows — decision trees and process specs for humans running the system.
  5. Outputs — everything the brain produces, archived alongside the context that produced it. Six months of outputs is a feedback loop.

ECP Before ICP

You have to win early to earn the right to go upmarket toward your ICP. Focus on what is immediately obtainable: sub-segments with burning pain points — early adopters with higher risk tolerance, willing to co-design, not blocked by compliance and long negotiations.

Four-Bracket Qualification Model

Every account sits inside four brackets:

  1. Firmographics — table stakes. "50-250 employees in US tech" is 2M companies on LinkedIn. You're spraying and praying if that's your only filter.
  2. Behaviors — separate conversion-indicative behavior from noise. Visiting pricing page 5x in 4 days is a signal. Liking CEO's LinkedIn post is not.
  3. Timing and momentum — the "why now" window. Company that received $2-5M funding, 3 months after round closed, is a sweet spot.
  4. Revenue potential — $100 prospect gets self-serve. $100K prospect gets proximity and care. Don't celebrate when Walmart lands on your website if you're not selling to Walmart.

Reverse engineer the weighting from actual traction. Ask: which clients do I want 500 more of? Don't build ICP around snow leopards (one-off deals).

Three Things That Cut Through

  1. Proprietary signals — defined from your product analytics. If an activated account invites 5 people from the same company, that's when sales should reach out.
  2. Proprietary research — the research that even big teams skip. One intelligent, well-researched message beats 50 templated ones. Seeing 3-5x conversion rates, sometimes 10x.
  3. Human touch — with all the AI, human touch matters more than ever. One question: is this relevant to me?