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Your employees are losing their minds to AI
We Analyzed 4,500 AI Use Cases. Here's What We Found.
Most employees use AI regularly, but only 2% report use cases that involve meaningful automations, because companies aren’t helping people figure out what to use AI for.
AI-native engineering: the 2/2/2 framework
Building an AI-native engineering team isn't just about using new tools. At Section, we use Domain-Driven Teams and the 2/2/2 framework to ship feature-complete value every six weeks.
How Klaviyo helped 1,800 employees find a great AI use case
In 2026, AI cannot be an optional career-builder for a handful of employees – it needs to be a business expectation for everyone in the company. Klaviyo took the first step into mandating AI use in Q4 and their AI Transformation Lead shared how it went.
Why you can’t get your AI automations to work
If you’ve ever tried and failed to automate a seemingly straightforward workflow, it’s likely not on you. Machine & Partners’ Edmundo Ortega is breaking down how our legacy systems hold us back, and how that’s already changing.
10 lessons from running a startup in 2023
This was a hard year for Section, but we’ve come out of it fitter and stronger. Here are 10 lessons that I’ve learned about running a startup – hoping they provide some inspiration to you.
How to prioritize AI projects
If your company is all-in on AI like Section, you might’ve spent the last few weeks coming up with exciting AI projects to tackle in the new year. After the fun brainstorming work comes the less glamorous step of figuring out what your organization actually has the time and budget to execute. We're sharing a simple risk-reward framework to prioritize your AI projects.
Your employees are losing their minds to AI
AI dependence is already degrading cognitive capability in the workforce – and AI upskilling for employees needs to go beyond tools to protect the thinking that makes their work valuable.
The AI Conversation Is Growing Up
The AI conversation is growing up. And the companies pulling ahead are the ones who are moving fast from experimentation to system change.
