This is Your Second Brain on AI

Episode Notes

Transcript

Announcer:

Web 2.0 innovation collaboration software, metadata got the world turning as fast as it can hear how technology can help legally speaking with two of the top legal technology experts, authors and lawyers, Dennis Kennedy and Tom Mighell. Welcome to the Kennedy Mighell report here on the Legal Talk Network

Dennis Kennedy:

And welcome to episode 399 of the Kennedy Mighell Report. I’m Dennis Kennedy in Ann Arbor,

Tom Mighell:

and I’m Tom Mighell in Dallas.

Dennis Kennedy:

In our last episode, Bridget McCormick, CEO of the American Arbitration Association and former Chief Justice of the Michigan Supreme Court joined us in our fresh voices on legal tech series to talk about a bunch of cool things, including some of what the AAA is doing with AI in dispute resolution. Great stuff and highly recommended if you haven’t listened to it already, and if you have, there’s enough there to make it worth a re-listen. In this episode, we wanted to return to our multi-year multifaceted second brain project. Tom brought up this topic and I suspect that means he’s made some advances he wants to share. Tom, what’s all on our agenda for this episode?

Tom Mighell:

Well, Dennis, I wouldn’t say advances that I want to share, but thoughts that I want to share, things that have occurred to me, and then I guess we’ll talk a little about what we’re going to do about that. So in this addition of the Kennedy MAH report, we will indeed be talking about our long running second brain projects and whether we are on the verge of a major breakthrough or something completely different in our second segment, we’ve got a great audience question. Yay for audience questions. And as usual, we’ll finish up with our parting shots, that one tip website or observation that you can start to use the second that this podcast is over. But first up, our second brain project. So I’ll try and cut this down short. For those of you who are just now listening to the podcast, we’ve had a number of episodes where we’ve talked about the concept of building our second brain, having a place where we can store that information that’s important to us, whether it’s information we want to come back to and write about later information we want to keep that will help us in our jobs or in our personal lives or in some other way, but that your first brain was not capable of holding.

What would that second brain be? We talked about how to capture that information, where to store it, how to manage it, how to keep it updated, how to access it and how to use it as usual. Dennis has been able to get much further along. We ended up choosing Notion as our tool of choice for our second brains. Dennis has gotten a lot farther along on it than I have, but I would say that I recently have, and I’ll be full admission. I read an article in the past week that made me a past couple of weeks that made me think and have an epiphany about the direction of my second brain. So I wanted to talk about it, to talk about what I was thinking and I’m thinking and learning that I think Dennis May be in a certain way thinking the same thing that I was all along. So Dennis, as we start talking about this, are we just going to say that you’ve incorporated AI now into your second brain, like you have your first brain or do you have other thoughts about this?

Dennis Kennedy:

Well, I’ll talk about AI later. So I want to describe the inflection point I reached on the second brain experiment. Some of the lessons I learned and what made me decide to make a pretty significant pivot. So we both built extensive notion databases for knowledge management and in my case especially, I created some elaborate organizational structures and I successfully, I would say aggregated a lot of information from various sources and made it usable in some ways. But I think the emphasis was on organization and some curation workflows for building that. Then I realized that I had created a library. What I really was interested in from the beginning was what I would call actionability or that I had created another way. It says I created a library when what I really wondered was a laboratory. And so I was actually kind of an impressive in this way in information architecture that didn’t really have a lot of behavioral impact.

So some people will call that I’ve seen this described as the beautiful graveyard phenomenon. So I had this well organized content that never gets access or applied in the way I had imagined from the beginning, and that led me to this epiphany, Tom and I don’t know this is the same place you were getting to, that I recognized that this approach of aggregation and curation without clear pathways to action actually created this own elaborate system of digital hoarding that Tom, in your way of saying there are filers and pilers and acknowledging I’m definitely a piler. I just kind of created better looking, better organized digital piles of information that I wasn’t able to pull much stuff out of anyway, and so that was the wall that I hit. So that’s my introduction to where I got with the second brain, which was actually very far. I just realized that I had definitely hit this wall.

Tom Mighell:

Well, and you and I have a different approach to it. We’ve always had a different approach to what we keep because whether you had a second brain or not, you err on the side of keeping every single thing forever. You kept all of your podcasts, you had four years worth of podcasts that you hadn’t listened to because you never know what was in those podcasts. My approach to my second brain was keeping what I thought I would want to have later, keeping the things that I thought would be important. I was being a little more discriminating in what I was putting into my second brain. But then recently, and frankly, you and I have gotten to the same place, but I got there in a different way. I needed someone to tell me what I was thinking. I read an article by a woman named JoAnn Weinberg.

The title of that article was called I Deleted My Second Brain, and I will tell you as I was reading it, it was as if I had written the article in the future because every single word and so I’m going to read you things that she said, but as if I’m saying them because there’s so many of the words that she said that echoed the feelings I’ve been having about my second brain. And so talking about you say a beautiful graveyard, she calls her second brain a mausoleum, a dusty collection of old cells, of old interests, of old compulsions piled on top of each other, like geological strata. It was the promise of the total system. That’s what we’ve talked about a lot is what is the total system. You weren’t just taking notes, you were building what she calls here, a lattice of meaning.

It was all connected together somehow. But see, the architecture of the system started to shape my attention. It really is what took it over. I started reading to extract notes. I started listening to summarize, I stopped wondering and I started processing. That’s all I was doing was processing everything. And what was interesting to me was I was, and what she says here really struck me. She says, I was outsourcing the act of reflection. I didn’t revisit ideas, I didn’t interrogate them. That’s going to come back. That’s important. That’s what we’re going to talk about in a minute about the laboratory aspect. I filed them away and trusted their structure. But a structure is not thinking. A tag is not an insight, an idea not reen encountered, might as well have never been had. So when we first started our digital brain projects, we thought we were solving the problem of forgetting.

I think that’s one of the things we were solving. But however, we created a new problem in my opinion, which is that of deferral. The more that our second veins grew, the more we are deferring the work of thought to some future self who would sort tag, distill and extract the gold and in the current format. For me, that’s never going to happen. I’m never going to do it that way, at least not in the way that the second brain is organized right now. So it took reading this article for me to have the same epiphany that I think you had, which is this is not sustainable. The good news is, and the things that we are going to talk about I think in our second half is that we now have tools that will make a pivot, if not perfect, at least very exciting and very doable and to accomplish the goals that I think you were talking about just a few minutes ago.

Dennis Kennedy:

Yeah, I would say that the insight I’ve found really helpful was that I had created the second brain in notion, and the idea would be that I had curated this great information that I had somehow selected in some way or had kind of identified to put into this system. Then when I wanted to do something and access that information and find new connections between things, I had this place I could go do it and that would be infinitely better than just following what was happening on social media or feeds that came in or email newsletters or anything like that that I would have this time. I would go in there and there would be all this great information that was relevant to me. And what I found was that I never went back to it to do exactly that and that I identified as the big problem, which I think Tom will later will we talk about what I’m thinking about going forward is one of the things I’m trying to get to, and so what I would say the insight here is a big one is that I had optimized for storage but not for retrieval and that because if I optimize for storage and I don’t optimize for retrieval, then those systems are going to fail in what I thought was the primary purpose.

And if we go back to our notion of jobs to be done, I realized I created something that did not address the job I wanted to be done at all. But I wanted to say that necessarily what I did was a failure because it helped me see much more clearly what it was I needed and why. I kind of focused on the wrong part, the sort of storage, and I had kind of pretended it was aggregation and curation, but a lot of it was just pure storage with the idea that I would go back to it and that kind of led me to what I felt was this brick wall or this dead end. So I dunno. So that was part of my thinking time and I know that we kind of joke that I went much further than you had, but it seems like in your own experience as reflected in this article that you kind of found yourself at a similar kind of point in time or a place.

Tom Mighell:

Well, I found myself in the same position as you did without having gone through all the work that you did. So I just felt like I’m not accessing this, I’m not doing anything with it. Like you said, if it’s just there for storage rather than retrieval and application, it’s failing at something. And so I think that where we thought that the capture was important, we weren’t thinking about the actionability as much or we didn’t really have a tool or an idea for solving the actionability where I think there are tools for doing that these days. We want to talk about that in our next part, but we need to take a quick break for a word from our sponsors first

Dennis Kennedy:

And we are back. Tom, let’s talk about the new approaches we are trying in our second brain projects or maybe better to say planning to try. And I suspect both of us will be using ai, but I don’t think that AI is a tool. I think it’s more of a framework that will be trying that is going to make all the difference.

Tom Mighell:

Well, yes, but I think your ideas are probably much more fully formed here. But let me walk through what I’m thinking now and frankly I think that there is some strange connection that still exists between our brains because we both decided to use Notion. We’ve both identified a similar issue with our second brains and we’re both gravitating towards the same solution right now. I don’t really have a hypothesis of what I want to do. I haven’t really started yet. My idea though, I think is closely following yours, which you’re going to explain in a lot more detail in just a minute. That article, the person that wrote the article, I deleted my second brain. Her solution was to have no system at all. Delete what you don’t need, don’t capture anything, read what you like, don’t manage knowledge, live it. I’m not headed in that direction.

I still want to capture things. I still want to make it actionable. What I’ve decided to do is I’ve decided that of all the AI tools that we have, I think that Notebook, LM is a strong, very powerful tool that can serve this purpose to a greater or lesser extent, which is what part of the experiment’s going to be as a set of resources. I’m going to combine that with Read wise that may be different from what you’re doing. I still use Read Wise as my reader app. I still read articles, newsletters, podcast transcripts. I capture what’s interesting to me, which I might want to refer to later. All of that information syncs automatically with Google Drive, which makes it easy to transfer to Notebook LM if I want to. And then I also use the Read Wise app for the spaced repetition. I’m revisiting things on a regular basis.

So to a certain extent I’m getting that benefit of surfacing information I’ve captured in the past to either learn from it or remember things or get ideas. So those are the two main tools. And what I want to do is know is whether I can sync the read wise notes with Notebooks and Notebook lm, but for right now, I’m satisfied with just having it in the Google universe. In the meantime, I’m curating notebooks on my own. I’m creating notebooks on topics of interest. I’m learning how to make those notebooks work together. There are supposed to be ways that you can, even though there are limitations to the size and number of resources in the notebooks you have, there apparently are ways to make work, but notebooks refer to each other or look at each other. And I’m looking at that. I’ve got, just for an example, I have a notebook that I’ve put all of, we’ve talked about the health podcast that I’ve listened to and the articles that I’ve gotten.

I’ve put all that health information into one notebook that has good, solid, vetted, scientifically proven information from a lot of well-respected people that I can then query and ask questions about and what are recommendations about X, Y, and Z. I’ve started a notebook on AI case law so that I can see what are the courts doing and how are they approaching. It’s my own version of the tools that lawyers are using that there are probably some Harvey or Lex or others are able to already do this. I’m creating my own version of that as I move back into content creation, which I may be doing. I may have a notebook there to store ideas to help me with content, although there are better options for that. It may be something that I’m using for content creation. I plan not to call this my second brain, but I’m not really sure what that title is going to be. And that’s really as far as I’ve gotten so far. So Dennis, I’m sure you’ve gotten a lot farther on this. What are you thinking?

Dennis Kennedy:

I have a new name, so that’s a good thing. So I’m calling mine the Knowledge Forge. I think it captures more what I want to accomplish and I’m looking at ai, I’m looking at Notebook lm, and the important part about Notebook LM is that it has kind of captured what was the holy grail in it for AI personally from about two and a half years ago, three years ago, where you said, I wish I could use the AI model but kind of confine it to my personal information. And so that’s the retrieval augmented generation idea or, and so Notebook LM allows you to just pull in all your documents and things like that as long as you can get ’em into a PDF or a Google Doc, which is totally easy to do. And then it works on your own sources and you can pick and choose the ones you want. And so you have a lot of flexibility. So this to me is like the holy grail because Tom, if you recall when we first were going to put our book into training it on a large language model, it was going to take two full days of computer processing to get one chapter done, take forever. And we’ve talked about on the podcast, the notebook lm, it takes less than a minute.

So then I said, actionability is a thing, and I already knew I was terrible at tagging and other things like that, and I was finding out I am bad at going back to this stuff. And so I realized that there is, people talk about like, well, I want AI to be better than me. I want to do the best work, that sort of thing. And I’m worried about what it does and how effective it is. So I found out that AI can do a lot better than I do. I just have good intentions that I don’t follow through on. So I was joking around with a friend of mine this evening and I said, I’m starting my prompts lately with this, and I say, I want to honor my laziest self and have the AI do as much of the work as possible. Here’s the description of me, make reasonable assumptions, act as my stand in and generate a complete first draft of the answer without asking for any more input from me yet. And I’m just like, I’m just going to let the AI take the first pass completely. So I said, here’s the problem with the actionability is that what I really want to do is I want to say, here’s all this stuff that’s in the notebook lm, and I just want to be able to ask things or have it surface things for me. I don’t want to have to tag it, I don’t want to have to organize it. As I said before, Tom, I’m a piler. I’m not a filer.

I’m at an age now where I’m not going to change that. So can the AI do a lot of that work for me? And if I just tell it, Hey, look, I’m lazy. Here’s what I want you to do, do all the work for me, and then we’ll kind of iterate on that. And so those are some of the notions. And then to work with the notebooks. So I have a bunch of notebooks related to certain things. Some of ’em are similar to yours, some of ’em are different because of some of the things that I’m doing, but that’s sort of the general picture. And then I made sort of one big improvement that I’ll talk about in a minute, but I want to get your reaction to how I’m actually using this, but how I started to think about using this as well.

Tom Mighell:

Well, frankly, I mean what you described is what I’m thinking too. I feel like I’m not quite as far ahead, but we’re really thinking very similarly about that. So hit me with your idea and let’s see what it is. One of

Dennis Kennedy:

The issues with AI is that it’s not persistent and it will drift and it will go in its own direction, and it makes that by its nature, it’s going to kind average some things out. And it’s really hard to, if you say, I want the best such and such, you’ll get a different answer probably every time or it won’t. You have no idea why it says something is the best. So my idea was to say, what if I just gave it that definition of what something that was important was and what I was looking for and said, here’s the protocol. So when I ask you this question, then you use this protocol to give me the answers and you give it to me in this output. So here’s the concept, Tom. So I have this notion of haystacks and needles, and so the idea is that, and I’ll use the example of AI chat sessions.

I could use it all of my articles that I’ve ever written, stuff like that, that’s the haystack. So it’s just a bunch of stuff. I would like to pull the best part out of that. I don’t really want to go through all of that. I’ve probably spent years saying, oh look, I’m just going to go through this stuff and pull out the best stuff, and I have never done it. So I said, what if I just say I grab the haystacks in a size of a document that notebook LM will handle? Then I create this document that I call needles, or I actually call it needles text. It’s a little bit different name in that, but you get the idea. Then I say a needle is, and then I give it the categories and I say, here’s what I want you to do. I want you to go through find these things and put ’em in this format that tells me what these things are, and then I have them.

So you could say, I have let’s say a 50,000 word document that’s captured a bunch of chat sessions. Then this needles prompt will give me something that’s just a couple pages with the highlights of it. So you could say, well, how do I know that I’m not missing something? And the things that we usually say, how do I know that a human couldn’t do better? And I would say, what I knew is this human me is never even going to do this. So whatever I get from this is actually going to be useful to me and it’s going to be consistent and the things it’s looking for and the criteria it uses. And because I’m refreshing each time and I’m referring to it in notebook lm, each time that I’m generating these needles, I get this consistency and a memory and persistence that I wasn’t able to get before, and that’s really attractive to me.

Then I also yesterday did this thing which I call needles from needles, which then I said, okay, even those needles are too much as they grow. Why don’t I just say for each of these things go through all the needles I’ve generated in other documents and I am much more rigid and say, just limit it to this number of things on this. This is more important than that. This is what I care about. And so I’m getting this thing that says, oh, in these documents, here are the breakthrough concepts. Here’s a really interesting analogy that’s unexpected. Here’s some potential projects. So there’s a bunch of criteria that I had AI help me generate to kind of get into the final form. And so that to me is kind of breakthrough in my second brain is that, and it goes back to that laziness notion where I say, okay, I’m not going to do this.

And the roadblock is always, I’m going to be that constraint. I’m going to be the roadblock. I’m going to be a problem. I’m just going to AI just bulldoze through that because it’s going to give me something that I have that’s usable instead of me never getting around to doing it, and it’s been really successful for me. There’s still the next step, which will be the experiment, which is to say, will I really go back into this stuff and use it in the way that I thought I would to say like, oh, let’s take some ideas and what’s unexpected and how might I use it for this? Here’s what I’m thinking about those kinds of things. I have some other ideas on that, but I think that’s seal the experiment piece. So in taking that undifferentiated amount of material and boiling it down to something useful, I think I really have something Tom that I’m really pleased with. But that next step to say now that I got something that by definition is much more actionable in some ways suggests what those actions could be for me, will I as the human actually follow up on that or will round three be where I say, you know what, as a human, I failed again. So I’ve figured out a way for AI to do that actionability piece for me. I think as the human, I can probably still do that better, but it is interesting to think about whether AI could do some of that for me.

Tom Mighell:

So I’m really interested to see how this works out for you. I want to learn more about it, and I don’t want to go down too big of a rabbit hole here, but I do want to ask before we need to move on to our next segment, I do want to ask, this is a technical question, so I know that with other tools, chat, GPT, Claude, other tools, I have a place where I can put the types of instructions that you’re describing. I can put in, here’s what I want you to do and here’s how I want you to focus. I’m not necessarily that familiar of how to do that in notebook. Lm, where do you put those instructions? Because do they go on the notebook level? Are they on a higher level? Where do you find that? Where do you put that information in?

Dennis Kennedy:

So that’s in the source level. So what I do is I create the whole protocol and I upload that as a source document, and then when I run the prompt, so you put the instructions as a source, essentially the instructions are, yeah, I call it protocol. So the instructions are a source, and you say, so when I’m making the query the AI prompt in notebook, lm, I’m saying there’s two source materials. So one is the source or sources that I want, how you normally think about it. And the other source is always going to be this needle identifier rules do text document. That’s always going to be a piece of it. I sometimes do this thing now where I say I have a description of myself too and some of the things that I think are important in how you think about me, and I will also check that.

So I would say now that becomes part the source material. And then in theory, and it seems like it works fine for me that it will kind of tailor its answers a bit more toward me and my interests. And so I’m playing with things like that. So it’s this notion of protocols. So it just becomes another source document that you just remember to check every time when you’re checking the other sources you want to work with. And then I’ve also used these protocol documents in the tools like Claude and Gemini and stuff, and I just have a text expander thing that says, okay, based on this protocol, grab the needles from this whole chat assessor, stuff like that. So that’s the concept.

Tom Mighell:

Alright, well, I’m interested to see where this goes, Dennis. I expect a full report. I expect we’ll probably come back on a later episode to talk about our irrespective experiments as we continue to refine what a second brain or whatever we’re going to call it, a knowledge forge or whatever looks like if you out there are trying something similar, if you have found our frustration and you’ve already done something like this, please let us know. We’ll talk at the end. We’ll tell you our phone number to leave a voice message or drop us a line. We’d love to learn about what you might be doing. In the meantime, we’ve got to take a break for another message from our sponsors. And now let’s get back to the Kennedy Mighell report. I’m Tom Mighell

Dennis Kennedy:

And I’m Dennis Kennedy. We wanted to remind you to share the podcast with a friend or two that really helps us out in this segment. We have a great question about Android versus Apple, one of those timeless issues from longtime listener and legal tech pioneer Jerry Lawson, and here it is.

Caller:

This is Jerry Lawson. I’m calling with a question about Android Envy. My understanding is that Google has done a much better job of incorporating artificial intelligence features into its products as a long time iPhone user. I’m a little jealous. I’m reluctant to switch over to Android now though because Apple has the history of delaying entering a new market until they are confident they have a category killing product. What do you think?

Dennis Kennedy:

So

Tom Mighell:

Tom, this is right in your wheelhouse. What’s a you? My answer may surprise you, my first response is you should not change your phone universe for one feature or set of features. As much as I love Android, and just because Google has a headstart on Apple in the area of AI does not mean that you should drop a phone that you’ve loved for a long time, that a phone that gets the job done for you. I would hate for you to drop a phone because you liked certain AI features only to learn. Oh my gosh, this Android phone doesn’t do these five things that my iPhone used to do. If you choose to change to Android, it should be because the entire platform is more appealing. So I’m going to make my argument there and say, here’s why Android is superior to iOS customization far and away the best reason for having an Android phone.

You are not walled in by iPhone’s restrictions, although for a lot of people, those restrictions are what give you comfort, comfort and certainty that it’s always going to be a certain way. So customization may give you too much freedom and may be frightening for some of you. The Google ecosystem integration is a huge aspect. If you use Gmail, Google Docs, Google Maps smart devices, they will no question work better for you on an Android device. They just don’t work the same. And I’ll show you in a minute why it’s just so amazing. Notifications so much better on an Android device than iPhone. Even though iPhone’s getting a little better call, screening has been far superior to iOS for a long time. Apple recently introduced a call screening function that I’ve been using on an Android phone for at least two years now. I can’t remember the last time I received a spam call.

It’s so good and awesome. Other reasons include lower relative prices, better multilingual dictation, keyboard functionality, easier file management, better computational photography. There are a number of reasons that you would want to switch overall, but let’s talk about the AI issues and Apple versus Google. I think you’re right, Jerry. Apple is a master at entering the market when it can bring the best in class, and that means sometimes waiting for a long period of time to do that. The problem here is that AI innovation is moving faster than Apple is moving. If this is one area where the area of the innovation is outpacing the time that Apple usually takes to do all of this, and I think that Apple struggles with that. I think there are struggling with that here, which makes me wonder, will Apple always be a little bit behind the curve on ai?

I am not sure I’ve heard a rumor. I’ve heard several rumors. I heard they were going to actually license Google Gemini software to Power Siri. I’ve heard they were going to buy perplexity or even open ai. And even if one of those proofs true, it’s a sign that Apple’s tried and true model doesn’t really work as well with AI as it might work in other areas. I’m not sure, but that’s just the feeling I have. I feel like AI is a different thing for them and I think they’re struggling with it. That said, here are some of the really cool AI features. I just got my brand new Pixel 10, which if you go to the website on Google, it will say the pixels are built for Google’s ai. And it is true. The absolute best feature on it is a new feature called Magic Q.

What it does is it’s an assistant that surfaces contextual information and proactive actions across all of your Google apps, but not just Google. The other day I got a text message from a friend of mine asking, what time do you want to meet on Monday? And right below that before I even had a chance to enter what my message was, right below that was a button that surfaced that said Open, and I pressed it. It gave me an option of whether I wanted my Outlook calendar, which is my work calendar or my Google calendar. I pressed Outlook. That’s where I keep my work schedule. And it went to the correct day that the person was referring to in the text message. It went straight there. I didn’t even have to do anything so I could immediately see what was going on. To me, just that little thing was amazing that it knew enough about it to help me make that decision.

There’s a lot of other options that Magic Q can do that’s just amazing. Voice translate now provides natural sounding, translated conversations that are generating the translations in your own voice, maybe a little creepy, but also kind of cool that it’s doing it. The translation in AI is getting a huge amount of improvement. If you choose to use it. Your voicemail can be replaced with an AI assistant that transcribes and manages calls more intelligently. There are a lot of features in your camera. There’s a camera coach that now analyzes a scene and recommends the best composition and creative shots. You can now edit a photo just by talking to it, having a conversation with it. Please remove this, move this person over here. Take that person out, put a green hat on this person. Not sure if it’s AI related, but the other night I took a photo of the moon with the new hundred X zoom and I never believed I could take a closeup picture of the moon with a smartphone. It was just amazing. All of that said, Jerry, I would say don’t make your decision just solely on the AI tools. Make it because there are other compelling reasons to move for Android. I’m happy to join you in the land of freedom outside of the walled garden where you can customize and do things that you want. But I also would totally understand if you want to wait around to see what Apple does with iPhone. Sorry, Dennis, that was a long amount of talking. Anything you wanted to add to that?

Dennis Kennedy:

Yeah, I mean, I agree with you. The key to phones is the ecosystem. So I think you have to make a strong decision of why you would want to change ecosystems for something that’s changing as quickly as ai. And also, I think the phone, when you talk about phones and ai, I think it really brings up the fact that we’re using AI to cover a whole bunch of different kinds of artificial intelligence. And so you can think, oh, this is large language models, but some of the things Tom described have nothing to do with large language models. They’re different types of ai. I think the thing about Apple is that it’s doing a lot of work under the hood with ai, so I’m comfortable with that. There are things that I really like. I would not make the change. The other thing is that even if you’re thinking like, oh, I need to do this because of large language model ai, the fact is that not that many people use this stuff well enough that it’s going to make a difference.

And if you do use it well enough, you can make almost any AI do the stuff that you want. So I don’t really see a need to change the platform. I think that one of the things that’s important to consider, because lawyers especially are now big about their data privacy is Apple’s approach to data privacy is I think would be much more comforting and reassuring than you’re going to find in the Android world. But it has implications on the development of ai, that’s for sure. So I think there are a number of things to consider. If I were in the Android world, I wouldn’t change for ai. If I’m in the iPhone world, which I am, I’m not going to change for ai. So I don’t think you need to have Android envy at all. Jerry, I take, what you need to do is do what you, and I’ll speak to you directly, Jerry, to do what you’ve always done, which is get your hands on and try to AI and see what you can do with what you have. So now it’s time for parting shots. That one tip website or observation you can use the second this podcast ends. Tom, take it away.

Tom Mighell:

So my parting shot is related to our second brain project, which is, it’s another tip about notebook. Lm. I found a Chrome extension that is super, super useful. It’s called Cortex. Cortex is an extension that will embed a button into any of the AI tools that you use. Claude Open ai, I believe it’s in Google Gemini as well. But it will embed itself in there so that when you have a conversation with OpenAI and you want to save that conversation in Notebook, lm, you literally just have to press a button. It will open up and say, which notebook do you want to save this source to? And you can immediately save that conversation to any notebook that you want. Dennis, I think you’re going to say in a minute that it solves all kinds of problems that you’ve been having. I’m looking forward to using it because it makes it very simple to get information from an AI that you use a lot of times and put it into another place where it can be of other use for you.

Dennis Kennedy:

Yeah, Tom, this is a game changer in a lot of ways. I wish I would’ve had it over the last day and a half. I would say one of the problems with the extensions though, is that I tend to use the AI apps rather than the web versions, but you just have to when you say, I’m going to harvest some of these chat sessions, just going to the web version of it. But yeah, I saw what this was. Tom and I immediately downloaded the extension, and unfortunately I just got all caught up on uploading my conversations into Notebook lm. So I’ll have to do some more to try it out. So my parting shot is just a shout out to my own concept of personal quarter, the offsites in my new PQO as I call ’em newsletter, which I call Personal Strategy Compass. I actually used my mid-year personal quarterly offsite to help me think through my recent decision to retire from Michigan State University in the Center for Law Technology and Innovation. It was a great run, and as I realized through using the personal quarterly offsite process, I have some other things I want to do now and I’m going to be doing those, and you’ll hear more about that. And as Sherlock Holmes once said, the game is afoot.

Tom Mighell:

And so that wraps it up for this edition of the Kennedy Mall report. Thanks for joining us on the podcast. You can find show notes for this episode on the Legal Talk Networks page for our show. You can find all of our previous podcasts along with transcripts on the Legal Talk Network website. If you’d like to get in touch with us, remember, you can reach out to us on LinkedIn or like Jerry did this episode, reach out to us and leave us a voicemail at 7 2 0 4 4 1 6 8 2 0. So until the next podcast, I’m Tom Mighell. And I’m Dennis Kennedy, and

Dennis Kennedy:

You’ve been listening to the Kennedy Mighell Report, a podcast on legal technology with an internet focus. If you like what you heard today, please rate us an Apple podcast. As always, a big thank you to the Legal Talk Network team for producing and distributing this podcast. And we’ll see you next time for another episode of the Kennedy Mighell Report on the Legal Talk Network.

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