Brian Cassiano Bittencourt — VP Marketing & Growth @ Woba | CMO · CRO · Marketing/Growth Director | AI Expert Building AI-Native GTM | Stanford Alumni | Ex-Wellhub
VP Marketing & Growth @ Woba | CMO · CRO · Marketing/Growth Director | AI Expert Building AI-Native GTM | Stanford Alumni | Ex-Wellhub
Brian Cassiano Bittencourt ranks #617 of 19,190 LinkedIn creators in Computer Software, and is a standout voice in Brazil. They have 17.3K followers and published 22 posts in the last 30 days at a 0.3% average engagement rate.
- 17.3K followers
- 22 posts / 30d
- 0.3% avg engagement
- 347 follower growth / 30d
The roast
Brian claims he is building AI-native GTM, yet he has 16,000 followers and manages to engage exactly zero of them. He’s the first VP in history to master the art of generating millions in pipeline while struggling to generate a single comment from a human being.
About Brian
Over the past 15 years, I've built and scaled Growth, Marketing and Revenue operations that generated tens of millions in pipeline, at companies like Wellhub (back when it was Gympass) and Woba, the largest flexible office network by subscription in Latin America. My thesis is simple: the future of GTM is AI-native. It's not about using AI as a tool. It's about redesigning funnels, automation and revenue operations with AI at the core of the architecture. That's what I build, and what I'm looking to bring to operations ready to scale revenue with intelligence. In practice, that means leading Growth, Marketing and RevOps teams with a focus on revenue efficiency: CAC, LTV, pipeline and unit economics drive every decision. I've built B2B, B2C and B2B2C strategies, structured ABM operations and growth loops, and led rebranding and market expansion initiatives. Three convictions guide my work: data becomes business decisions (not just dashboards), technology is a scale lever (not a cost center), and channels are systems (not isolated campaigns). I started my career in large scale operations like Deloitte, founded my own venture, and moved into the world of startups and scale-ups. That journey taught me how to build lean, high performance, high autonomy teams. I've been on both sides: building growth engines from scratch and optimizing mature operations for efficiency. I know the difference between scaling fast and scaling right. Stanford Alumni. I never stopped learning because the game changes too fast for those who do. Topics I care most about: AI applied to GTM, strategic growth, channel architecture, and the future of Revenue Operations. → Connect if you want to exchange ideas on Growth, AI or GTM.
Highlights
- Consistent Creator — 18 posts in 30d · top 5%
- Top 5% in Computer Software — Ranked #227 of 4695 creators
- Top 10% in Brazil — Ranked #12 of 225 creators
- Big Audience — 17,337 followers · top 10%
Recent posts
Uma vendedora da Cursor chama a ferramenta interna dela de "minha frota de agentes". Não copilot. Frota. Enquanto a maioria dos times de GTM debate qual prompt usar no ChatGPT, a Cursor colocou 400+ pessoas operando dentro de um sistema de AI que já sabe as contas delas e como elas vendem. Resultado, medido em pipeline e não em slide: 3x mais reuniões qualificadas e ramp de AE caindo mais de 50%. A diferença não foi comprar um modelo melhor. Foi construir um sistema que opera pelo time. Destrinchei o ChatGTM (e mais 3 movimentos que importam essa semana) na Native de hoje.
9 reactions · 0 comments · 0 reposts
Foi muito legal ver a sala cheia para falarmos de AI. Semana passada tive a honra de participar do painel de IA Aplicada da CoreNet Global Brazil Chapter. Dividi o palco com dois grandes profissionais: Carlos TUNES (IBM) e Fernando Valadão Buniotti (Hospital Israelita Albert Einstein), com a mediação afiada do Tiago Alves. Levei um spoiler da régua de maturidade de IA em Workplace que construímos aqui na Woba, do N0 (não usa) ao N5 (AI Native, operação que se reotimiza sozinha). A real é que a maioria do mercado ainda está no N1, reativo, mas temos muito potencial para evoluir cada vez mais
43 reactions · 9 comments · 0 reposts
Passei meses usando o Claude como um chat solto. Pergunta, resposta, fecha a aba. Umas 30 vezes por dia. E achava que tava "usando IA". A virada não foi um prompt mágico. Foi parar de tratar a IA como busca e começar a tratar como sistema de trabalho: contexto fixo, critério de aceite e rotina. Coloquei isso num plano de 7 dias — do jeito que eu faria de novo se começasse do zero hoje. O dia que mais muda o jogo é o 5: sem critério de aceite, a IA tenta te agradar. Com critério, ela tenta acertar. Só isso já
16 reactions · 1 comments · 0 reposts