The Track
A Section Blog
Yes, you will lose your job to AI
Try these 3 things before giving up on AI
In this interview, Jeremy Utley exposes the confirmation biases that cause us to bounce off AI – and how you can get a result that will make it stick.
How to get AI to nail a task in 4 steps
If you want AI to take over your grunt work, you have to put in some upfront effort to show it how. Our Education Product Lead, Tara Aranha, is giving you 4 easy steps to follow.
The best open-source AI chatbots in April 2024
While big players like OpenAI, Anthropic, and Google have been stealing the spotlight, a crew of underdogs have been working on models to give them a run for their money. But how do they stack up?
The VC perspective on successful AI startups
You might have a cool idea for an AI startup, but is it venture backable? General Catalyst's Christopher Kauffman will tell you.
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.
Sponsor your direct reports, don’t just mentor them
Your team needs both mentorship and sponsorship to thrive. We'll unpack the difference between a mentor and sponsor, and share DEI expert Mita Mallick's guidance on why both roles are essential.
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.
