The Track
A Section Blog
The hidden reasons you’re not getting AI ROI
AI is good enough, the humans need help
Newsflash if you’re waiting for AI to get better before you invest: It’s already pretty good, it’s the people using it that need to get a lot better – and fast. Greg is taking over this week’s newsletter to show you why.
When to use a specialized AI tool vs. an LLM
If you’re hitting the limits of your LLM because you need more data or niche training, you’re likely doing a lot of high-end knowledge work – and that’s where specialized AI tools come into play.
We tested two Deep Research tools. One was unusable.
Two LLMs have released Deep Research features without much of a splash. So if you’ve been wondering about them (and don’t want to pay the $200/month price tag), read on for our Chief of Staff’s take on ChatGPT vs. Gemini.
How an agency is preparing for AI clients
AI has put a big question mark over the future of agencies. So we talked to David Freas, Managing Partner at Supermoon, about how he’s transforming his brand agency with AI agent teammates – and for AI agent clients.
What you actually need to know about how AI works
Right now, AI chatbots seem like magic, and that’s dangerous. It makes it easy to overestimate their abilities. You don’t need to know every technical detail of how AI works – but you do need to know enough to understand its limitations.
Dive into what you really need to know about how AI works.
How we built a generative AI bot
By summer 2023, we were convinced we needed to use AI to improve our student experience. From August to October, we designed, built, and prototyped an AI course tutor called ProfAI. In today's post, we'll walk you through how we did it.
Squishy vs. hard ROI: Why leaders need both
One of the hardest parts of AI ROI is figuring out how to report qualitative wins to execs who want quantitative reports. At our AI:ROI Conference, Michael Domanic shared the framework for approaching these two disparate kinds of ROI.
AI’s progress may be holding your team back
On paper, the rapid release of new AI models and features looks like a win for knowledge workers. In reality, teams are drowning in AI overwhelm. Here’s how leaders can help them scale an ever-steeper learning curve.
