How Every’s Team Used AI to Ship Its Biggest Launch Ever (47 min)

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• Release date: 2026-07-22
• Listen on Spotify: Open episode
• Episode description:

  Yash Poojary, a growth engineer at Every, dropped an idea for a campaign in Slack at 7 p.m. Instead of building it himself, Every’s head of growth Austin Tedesco took a screenshot of the Slack thread, dropped it into Codex, typed "Can you do this?", and went to the gym.By the time he got back, Codex had built four audience segments, drafted emails for each one, and pulled a social image that had worked before. It took Austin 10 minutes to make some tweaks and schedule the whole thing to send the next morning. Within a few hours, it generated more than $25,000 in revenue. That story came out of the launch week for All Access, Every’s new $625-a-year membership built around the Builder Pack. It includes $7,000 in credits and free usage from ten of the AI products Every uses every day, including Claude Max, Codex, Cursor Pro+, PostHog, Notion, Framer, Render, and Flora.On this episode of AI & I, four of Every's own builders—COO Brandon Gell, head of marketing Douglas Brundage, as well as Yash and Austin—sit down to show how they use AI, breaking down their personal stacks and giving insight into their own strategies and mindset for building.If you found this episode interesting, please like, subscribe, comment, and share!To hear more from Dan Shipper:Subscribe to Every: https://every.to/subscribeFollow him on X: https://twitter.com/danshipperTimestamps for YouTube:0:00 Intro 0:35 All Access Explained 3:01 Yash's Tech Stack and How He's Automating Testing Pipelines 8:02 The Idea to Execution Loop 10:25 How an Agent Turned an Idea into $25K 17:50 The AI Sandwich Workflow 22:03 Making AI Tools Accessible to Solo Builders 28:50 Douglas on Brand and Design34:51 Tips on What to Build First 43:46 What's Next for All AccessLinks to resources mentioned in the episode:Brandon Gell on X: https://x.com/bran_don_gellYash Poojary on X: https://x.com/poojary_yashAustin Tedesco on X: https://x.com/tedescau?lang=enDouglas Brundage on X: https://x.com/DABrundageIntroducing Every All Access: https://every.to/on-every/introducing-every-all-accessGet the Builder Pack: every.to/builder-pack Go to https://attio.com/every and get 15% off your first year.

Summary

• 💰 Record Revenue Launch: Every achieved its largest subscription revenue spike by launching the $625 All Access tier featuring the Builder Pack of AI tool credits and benefits.
• 🤖 Agent-Driven Automation: Team members use Claude and Cursor agents to fully automate A/B testing, email campaigns, and analytics setup, freeing time for creative strategy.
• 🎼 Orchestrating AI Tools: Professionals describe shifting from playing individual AI ‘instruments’ to conducting multiple agents across coding, design, and writing tools simultaneously.
• 🛠️ Duping to Learn: New builders are advised to duplicate a favorite product using the full AI stack as the quickest path to hands-on mastery and discovering personal workflows.
• 🚀 Idea-to-Execution Speed: One /lfg command in Codex turned a Slack idea into four targeted email campaigns that generated over $25k in revenue overnight while the founder went to the gym.

Insights

• How can bundling AI tool credits and discounts into a subscription tier unlock massive revenue growth while lowering barriers for individual builders?
  • Time: 0:00 – 0:25
  • Answer: Every generated their largest subscription revenue increase by launching the Builder Pack, which partners with AI tools to provide credits and access, making expensive stacks affordable for users experimenting with AI.
• What happens to productivity when AI agents automate repetitive setup and testing tasks, allowing builders to focus purely on ideas and creative decisions?
  • Time: 4:04 – 5:07
  • Answer: Team members describe using Claude and Cursor agents to handle A/B testing pipelines, email cohort creation, and PostHog configuration, shifting their work from manual execution to high-level ideation and rapid iteration.
• How does treating AI models and tools as an ‘orchestra’ to conduct—rather than instruments to play—change the way creative and technical professionals approach complex projects?
• Why might starting with ‘duping’ an existing product using the full AI builder stack be the fastest way for newcomers to learn effective AI-native building?

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