Summary
Today, the Every consulting practice is announcing specialized playbooks for tech and finance companies to go from AI-curious to AI-native. Our consulting team has worked with hedge funds and investors with combined assets under management of over $100 billion, and has trained teams at top tech companies using a methodology that’s earnedmore than 7,000 stars on GitHub. Below, Every’s head of consultingNatalia Quinteroshares what we’ve learned working with these companies—and how any team can get started.—Kate LeeWas this newsletter forwarded to you?Sign upto get it in your inbox.For the past year and a half, we’ve been doing AI consulting for companies like theNew York Times, the hedge fundWalleye Capital, and mental health tech company Headway. What we’ve learned has reshaped how we think about AI adoption—and what it takes to get results.When we started, we noticed that something fundamental was missing in how professionals were using AI. These tools had drastically improved our own productivity across the editorial, product, and consulting teams, from synthesizing notes and automating meeting actions to extracting value from messy data. But the companies reaching out to us were at a loss for where to get started, or whether AI would even be worth the effort.So we decided to share what we’d learned from using AI every day. We took on a small group of clients in finance, media, and tech to help them implement AI in their workflows. A year later, we’vespoken to over 100 companiesabout their needs and frustrations, and have worked closely with nearly two dozen organizations.The practices we’ve been teaching have changed as fast as the tech. A year ago, our training focused on prompt engineering, engineering inside of the ChatGPT user interface, and developing robust Projects that referenced up to 20 documents. Now, while those principles and features are still important, they feel ancient.Today, we’re building custom plugins that connect AI to proprietary data, teaching teams to use Claude Code for end-to-end automation, and deploying agents that run entire workflows without human intervention. The technology hasadvanced rapidly, and we’ve been developing frameworks to match:compound engineering, which has been recognized by the creator of Claude Code, andagent-native architecture, our guide to building products in this new era.Our team of applied AI engineers, designers, analysts, writers, and editors are living this future every day. And our experiences have confirmed our long-held theses: We’re moving rapidly to anallocation economy, where individuals won’t be judged by the limits of subject matter expertise, but instead on how well they can allocate and manage AI resources to get work done. The key skills needed to get the most out of AI are the same skillsgood managerspossess—goal setting, clear communication, effective feedback, andconstant learning.Today, we’re unveiling the next chapter of Every Consulting, and to mark this, we’re sharing how we see the state of AI adoption at companies today.Want to learn more? Join our consulting information sessionon February 13. Or if you’re in finance, joinour March 13 workshopto learn how we use Claude Code to automate earnings previews, reviews, valuations, and more.Every is accepting a limited number of consulting engagements for 2026. If you’re interested in working with us,get in touch.Become apaid subscriber to Everyto unlock this piece and learn about:Why the best AI implementation at one hedge fund started in the back office—not with investorsHow a firm turned 50 hours of work per investment memo into minutesThe four levels of AI maturity, and why most companies are stuck at level oneSubscribeClick hereto read the full postWant the full text of all articles in RSS?Become a subscriber, orlearn more.Book information
Genre
Business and Economics
