Building a Personal AI Model Map [AI Operators Bonus Episode]
episode
The AI Daily Brief: Artificial Intelligence News and Analysis
12 min
2 speakers
7 chapters
transcribed
Transcript
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Transcript generated automatically by AI and may contain errors.
What is the purpose of the AI Operators bonus episode?
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All right, friends, today we are going to do something a little bit different.
One of the things that I was contemplating at the end of last year was actually doing a spinoff podcast called AI Operators. The idea of AI Operators would basically to be what I was calling a skills cast, where instead of focusing on the AI news, it would be all about using AI tools, building AI projects. And ultimately what I decided is not not to do that per se. It's still something that's very much on the table. But where I wanted to start at first was to experiment with it in the context of the existing AI Daily Brief community. And the New Year's AI resolution kind of gave me the perfect opportunity for that. For those of you who haven't heard or watched it, on New Year's Eve, for the last episode of 2025, I put together basically a self-guided AI resolution program, which was 10 weeks of projects that anyone could do to try to upgrade their AI skills heading into 2026.
Now, of course, we weren't just going to leave that an episode, so I vibe-coded up a website to go alongside it. The website has the program with all of the different resolutions and projects that you can do, as well as an ability to share what you did with the rest of the community. we've actually had literally hundreds of people share their projects already in just the first week. And part of what makes this so fun is that because this is all vibe-coded, and because, candidly, the stakes are fairly low, basically any time that someone has had an idea to improve the experience, we've been able to just jump on it and do it. So for example, this team feature came when one of my Patreons said, hey, I'd love to be able to do this with the team, prompting me to think to myself, well, that's just about the most obvious thing that I didn't think of.
And so sure enough, I was able to push a Teams update about 10 minutes later.
How can building a personal model map enhance AI usage?
And now in the past week, we've had over 200 teams sign up to do this together. By the way, big shout outs to the Google Cloud Startups team. By far the biggest team in the group. They have had 90 people join. We've also got a team from Meta that has about 35 and a ton of smaller company teams that have 5, 10, 15 people on it. So really, really fun to see what you guys are all doing. Now, coming back to this operator's bonus episode, though, we are now in week two, model mapping. And the idea of this, in short, is to help people do a set of tests so that they start to get a feel for what models and tools they like for different use cases. One of the lowest hanging fruit sources of alpha, in my estimation, for how to take more advantage of AI than most is to have this sort of personal map for what you think different tools are better or worse at.
Now with this, I'm not saying you have to go subscribe to the premium version of all these tools, but even knowing which among them are best at the free level gives you more power to use the best option for your particular use case at any given time. And so the idea of week two was to have people go choose a set of models, test the same prompt for a particular use case, and create a personal reference document for when to use each tool. And I think that that's cool, and I think that people who are doing that are getting a lot of value out of it. But I wanted to take it a step farther. One of the big shifts for me over the last couple of months, but especially coming back in 2026, is pretty much for everything that I'm doing, I'm asking myself, is there a way to build something, some software, some application that would actually make this better?
And so I started brainstorming with Claude, thinking about what sort of software might be valuable as part of this model mapping experiment.
What is the Model Map Builder app and its key features?
What came out of that brainstorm was a recognition that actually just from an information density perspective, testing a bunch of different use cases across a bunch of different models could get very unwieldy very fast.
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Chapters
7 chapters
1
What is the purpose of the AI Operators bonus episode?
0:00–2:13
2
How can building a personal model map enhance AI usage?
2:13–3:43
3
What is the Model Map Builder app and its key features?
3:43–5:07
4
How do you select and test AI models for different use cases?
5:07–6:29
5
What scoring system is used to evaluate AI model performance?
6:29–8:04
6
How can users contribute their own use cases to the Model Map?
8:04–9:10
7
What future developments are planned for the Model Map tool?
9:10–11:54