How to Get the Most from AI This Summer

**Nathaniel Whittemore** (0:00)
Today on the AI Daily Brief, we're talking about your AI Summer Adventure. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, Robots & Pencils, Rackspace, Blitzi, and Airtable. To get an ad-free version of the show, go to patreon.com/aidailybrief, or you can subscribe on Apple Podcasts. To learn more about sponsoring the show, send us a note at sponsors.ai.dailybrief.ai.
All right, it is a weekend, a summer weekend no less, and we are going to go action-oriented today. For this week's Big Things slash Long Reads episode, we're actually going to do two things, both of which are focused on the very practical. The first is that Professor Ethan Mollick has published the latest version of a blog post, which he's done a number of times. That's all about which tools he recommends for different tasks. He called it an opinionated guide to which AI to use to do stuff. And so we're going to look at all his recommendations in case they might influence the way that you want to experiment and change your workflows.
Secondly, though, we're going to be introducing the latest training program from AIDB. This one is at summeradventure.ai and is a choose-your-own adventure to expanding your AI skills. We'll talk about how it works and give you a preview of some of the projects. But let's start over with Ethan. The first thing that he notes in this new opinionated guide is that a lot has changed since the last time he did this. In fact, he writes, what it means to use AI to do stuff encompasses so much more stuff than it used to. Until recently, using AI meant talking to a model through a chatbot in a constant back and forth conversation. Now, it means using an agentic system where the AI is capable of doing the equivalent of many hours of real human work in one go. So, by combining the brains of an AI model with a set of tools that let it plan and act for you. Basically, an agentic system gives an AI a computer to use. So reddit top even divides his advice into these two categories. And effectively, he says, if you are just looking for some low stakes answer, such as asking a chatbot for a recipe or even asking it to help you write a letter or something, pretty much any model that you might use, including any of the free models, is going to do well enough. On the other hand, for anything where you really care about the answer, you're going to want to be using one of the premier models like Fable or FiveSixSoul, set to a reasonably high thinking level. And when it comes to doing real intensive work, Ethan argues that there are effectively only two choices right now, which is ChatGPT or Claude. Now, it is worth noting that that means that Gemini is officially out of the rankings, at least at this point, which I don't think will come as a surprise to anyone, but still is pretty notable about the state of things. Now, Ethan's next section is called giving your AI a computer. And although he isn't using the word harness, he's effectively talking about the systems that you're going to put in place, including controls, permissions, etc., that are going to shape what the models can do. He says, for example, I have the systems connected to my email, a non-private part of my Google Drive and lots of other applications, but you have to decide what you are comfortable with. And it's clear that the nudge that Ethan is giving is to actually use these sort of connectors. He writes, once you're set up, you can do pretty powerful things. For example, I told both systems, connect to my Gmail and help me prep for the MBA seminar I'm giving on Monday the 21st, including building some presentation and demos as inspiration. Answer any outstanding messages on the topic. Both systems got to work. They connected to my email and figured out the task, including correctly figuring out that the next Monday the 21st was in September, not August. And after that, they just started working, which is what agents do. They did research on the web, decided on a presentation demo, thought about how I might want to respond to the colleague who emailed me and more. About 10 minutes later, both returned answers, having created a range of teaching materials and writing an email to the colleague. This is impressive stuff that would have taken a couple hours of human work. But he says, while Claude only prepared a draft, ChatGPT actually sent an email to my colleagues. What happened? Well, it was my fault. I had previously given ChatGPT permission to send email on my behalf, and Claude was told to ask me first. So he says in one of his first big lessons, when you use these systems for real work, the permissions matter a lot. Both companies let you decide whether the AI must check with you before acting, such as sending an email, buying something or changing a file, until you trust the system and understand its mistakes, leave everything to ask for approval first, which is the default.