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A few weeks ago, Natalia Quintero wouldn’t have called herself technical. But since the beginning of January, she has woken up at 6 a.m. to vibe code with Claude. The AI project manager she built saved her 14 hours a week.
Getting there meant scrapping the system three times and starting over. But the result handles everything from onboarding new clients to generating weekly updates across all projects.
Natalia is the head of AI consulting at Every. As part of the role, she's spoken with over 100 organizations in the past year and worked with a select two dozen, including hedge funds, private equity firms, and Fortune 500 companies. She’s seen what separates companies thriving with AI from those floundering, and it comes down to patterns that have nothing to do with having the most resources or the fanciest tools.
Dan Shipper had her on AI & I to share what she’s learned from this front-row seat to AI adoption. Quintero reveals how a private equity firm cut investment memo creation from three weeks to 30 minutes, why AI adoption needs to come from the top down, and what happened when she learned from her early morning experiments.
She also explains why the companies going furthest with AI are the ones that give employees permission to fail—and how that counterintuitive approach is revolutionary.
If you found this episode interesting, please like, subscribe, comment, and share!
Want even more?
Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:
Subscribe to Every: https://every.to/subscribe
Follow him on X: https://twitter.com/danshipper
Ready to build a site that looks hand-coded—without hiring a developer? Launch your site for free at www.Framer.com, and use code DAN to get your first month of Pro on the house.
Timestamps:
00:00:00 - Introduction
00:01:30 - Why successful AI adoption requires coordinated, top-down effort
00:07:05 - How a private equity firm reduced investment memo creation from weeks to 30 minutes
00:13:30 - The benefits of connecting AI to proprietary context
00:15:20 - The plan-delegate-assess-compound framework for engineering teams
00:17:55 - How non-technical team members are becoming vibe coding addicts
00:20:50 - Building Claudie: an AI project manager from scratch
00:23:00 - Why creative exploration time outside the 9-to-5 is essential
00:27:50 - Live demo: How Claudie automates client onboarding and tracking
00:38:40 - The human side of AI: spending less time in spreadsheets, more time with people
Links to resources mentioned in the episode:
Natalia Quintero: Natalia Quintero (@NataliaZarina)
What Natalia learned from working with companies on AI adoption: https://every.to/on-every/the-next-chapter-of-every-consulting
Every’s compound engineering plugin: https://github.com/EveryInc/compound-engineering-plugin
By Dan Shipper4.9
2929 ratings
A few weeks ago, Natalia Quintero wouldn’t have called herself technical. But since the beginning of January, she has woken up at 6 a.m. to vibe code with Claude. The AI project manager she built saved her 14 hours a week.
Getting there meant scrapping the system three times and starting over. But the result handles everything from onboarding new clients to generating weekly updates across all projects.
Natalia is the head of AI consulting at Every. As part of the role, she's spoken with over 100 organizations in the past year and worked with a select two dozen, including hedge funds, private equity firms, and Fortune 500 companies. She’s seen what separates companies thriving with AI from those floundering, and it comes down to patterns that have nothing to do with having the most resources or the fanciest tools.
Dan Shipper had her on AI & I to share what she’s learned from this front-row seat to AI adoption. Quintero reveals how a private equity firm cut investment memo creation from three weeks to 30 minutes, why AI adoption needs to come from the top down, and what happened when she learned from her early morning experiments.
She also explains why the companies going furthest with AI are the ones that give employees permission to fail—and how that counterintuitive approach is revolutionary.
If you found this episode interesting, please like, subscribe, comment, and share!
Want even more?
Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:
Subscribe to Every: https://every.to/subscribe
Follow him on X: https://twitter.com/danshipper
Ready to build a site that looks hand-coded—without hiring a developer? Launch your site for free at www.Framer.com, and use code DAN to get your first month of Pro on the house.
Timestamps:
00:00:00 - Introduction
00:01:30 - Why successful AI adoption requires coordinated, top-down effort
00:07:05 - How a private equity firm reduced investment memo creation from weeks to 30 minutes
00:13:30 - The benefits of connecting AI to proprietary context
00:15:20 - The plan-delegate-assess-compound framework for engineering teams
00:17:55 - How non-technical team members are becoming vibe coding addicts
00:20:50 - Building Claudie: an AI project manager from scratch
00:23:00 - Why creative exploration time outside the 9-to-5 is essential
00:27:50 - Live demo: How Claudie automates client onboarding and tracking
00:38:40 - The human side of AI: spending less time in spreadsheets, more time with people
Links to resources mentioned in the episode:
Natalia Quintero: Natalia Quintero (@NataliaZarina)
What Natalia learned from working with companies on AI adoption: https://every.to/on-every/the-next-chapter-of-every-consulting
Every’s compound engineering plugin: https://github.com/EveryInc/compound-engineering-plugin

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