The Track
A Section Blog
Can you build a team of just AI tools?
How to build a custom GPT
Follow these step-by-step instructions to build a custom GPT model that completes specific tasks for you.
How to set an AI policy for your company
In this post, we'll cover the four parts to a strong AI policy – your stance on AI, operating norms, rules/guidelines, and real-life use cases.
Where's the money going to be made in AI?
Not every AI investor will make their money back. In this post, we dig into the AI business models that will work, and those that will be the next Pets.com.
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 customize ChatGPT to your needs
Working with AI right now is like working with a brand new coworker. They don’t get your processes or your way of thinking. You have to give them a lot of context, and even when you do, the results aren’t exactly right. While many people give up, we promise it's worth it to train your AI tool to be your best possible copilot.
How to make your competitors look bad without even mentioning them
Laddering (as defined by Scott Galloway) means highlighting your strengths in a way that inherently points out your competitor’s weaknesses. We’ll explain how to use laddering to deposition your competitors, using Writer, one of our favorite AI case studies right now.
How the Royal Family’s AI-powered mental health agent overcame privacy concerns
Most orgs feel unready for the challenges that Gen AI brings to risk management. Yet many AI applications will have to navigate the line between user value and user privacy. So we sat down with specialist, Brian Kolodny, to understand how he traversed matters of privacy when building a mental health bot for the Royal Family’s foundation.
Our Guide to Building Enterprise AI Applications
Every company needs to be thinking about where AI slots into their product or service, but all the noise and hype makes it hard to determine what a valuable vs. novel use case looks like. Machine & Partners’ Ed Ortega is sharing 2 frameworks to narrow down your laundry list of AI ideas.
