ProductivityCast

This week, we continue our dive into the world of Artificial Intelligence with another episode in our series, The AI-Powered Professional. Today, we are exploring AI in Everything, focusing on the shift of AI from being a standalone tool to becoming a core, embedded capability within the software we use every day, making AI truly everywhere. The biggest productivity gains are coming from smarter versions of the platforms we already rely on, rather than from brand-new tools. (If you’re reading this in a podcast directory/app, please visit https://productivitycast.net/153 for clickable links and the full show notes and transcript of this cast.) Enjoy! Give us feedback! And, thanks for listening! If you'd like to continue discussing AI in Everything (The Integration of AI: Maximizing AI Within Your Existing Platforms and Tools) from this episode, please click here to leave a comment down below (this jumps you to the bottom of the post). In this Cast | AI in Everything (The Integration of AI: Maximizing AI Within Your Existing Platforms and Tools) Ray Sidney-Smith Augusto Pinaud Art Gelwicks Francis Wade Show Notes | AI in Everything (The Integration of AI: Maximizing AI Within Your Existing Platforms and Tools) Resources we mention, including links to them, will be provided here. Please listen to the episode for context. Microsoft 365 Google WorkspaceTodoist  Extended mind,  Opinionated  Raw Text Transcript Raw, unedited and machine-produced text transcript so there may be substantial errors, but you can search for specific points in the episode to jump to, or to reference back to at a later date and time, by keywords or key phrases. The time coding is mm:ss (e.g., 0:04 starts at 4 seconds into the cast’s audio). Read More Voiceover | 00:00 Are you ready to manage your work and personal world better to live a more fulfilling, productive life? Then you've come to the right place. Welcome to ProductivityCast, the weekly show about all things personal productivity. Here are your hosts, Ray Sidney Smith and Augusto Pinaud with Francis Wade and Art Gelwix. Ray Sidney Smith | 00:18 Welcome back, everybody, to ProductivityCast, the weekly show about all things personal productivity. I'm Ray Sidney Smith. Augusto Pinaud | 00:25 And I'm Augusto Pinaud. Francis Wade | 00:26 I'm Francis Wade. Art Gelwix | 00:28 And I'm Art Gelwix. Ray Sidney Smith | 00:29 Welcome, gentlemen, and welcome to our listeners to today's episode, where we are going to be continuing on in our AI-powered professional series. Today we're going to be exploring AI in everything, basically focusing in on the shift of AI from being a standalone tool—which we mostly have today—to becoming more of a core or embedded capability within software we use every day, making AI everywhere. We're seeing that happening in the market as well. Art Gelwix | 01:49 I would say the biggest impact that I see right away is within my note-taking applications. I've seen—especially in the web-based ones—a direct integration of AI at the base level within the application, primarily because it has your information there to leverage and to be able to run through its models. Augusto Pinaud | 02:31 I would say the same: the notes and the knowledge base. All those things that I have collected and refer to regularly, having the AI there has been really fantastic. Francis Wade | 03:57 The biggest impact for me has been on my writing. Not so much in the tools I used to use, because I switched—I'm no longer using the tools I used to use; I'm using new tools. The improvements for me have not been within the existing apps; they've been in entirely new capabilities. Ray Sidney Smith | 04:51 I'll say that the first place I saw AI really put into my own productivity stack was in email, specifically within the Gmail interface in Google Workspace. That's my primary email, although I have accounts across almost every major email system because I test them for work. The change in my workflow was remarkable. Francis Wade | 08:36 I'm seeing a new way of managing working memory. Supposedly, we can only keep seven or eight items in memory at a particular time. If I'm doing research for an article, for example, I can scan sources, but once I get above eight sources, I'm not very good at keeping them all in play. I end up using the ones I remember most recently, rather than remembering 20, 30, or 40 sources. Ray Sidney Smith | 12:46 It's akin to asking, "Did you use spell check or grammar check in your Word document?" That's the equivalent—it's silly. Francis Wade | 12:54 It's the exact equivalent. Years ago, people asked if you used Grammarly or said you weren't supposed to use it for class. Now we don't even think about it. I believe this is where AI is going. It's a question of skillfully manipulating your tools to expand your capabilities. Ray Sidney Smith | 13:18 Augusto, then Art—go for it. Augusto Pinaud | 13:22 That is exactly what makes it powerful. I've been a heavy journaler all my life, but now some of that has shifted to AI. This weekend, I was working on a new book coming out and working through some stuff with AI. It gave me something where I was unsure, so I asked another chat to give me a summary of all the discussions we'd had on this topic so I could feed it to an AI agent. That process took 30 seconds. In the past, that would have taken a significant amount of time to review and rethink everything. Art Gelwix | 16:21 I love this idea of the AI intern because it provides a clear perspective on its role within your tools. In note-taking, if you expect AI to be an expert generating perfect solutions on everything, you'll be disappointed. But if you treat it like an intern—asking it to pull action items from meeting notes with reasonable expectations—it will be 80-90% accurate based on the context and training you've provided. Ray Sidney Smith | 18:10 Augusto, go ahead. Augusto Pinaud | 18:11 Exactly. We are all leveraging years of accumulated context rather than just installing a raw tool and expecting magic. For instance, I was writing the other day, and the AI pointed out where a statement contradicted something I wrote years ago. When I checked, I realized the old context assumed cell phones without data plans, whereas today everyone is connected. That prompt forced me to update my thinking and improve the article. Ray Sidney Smith | 20:58 When we talk about working inside an ecosystem, there are key advantages for corporate and enterprise environments—namely security, permission controls, and privacy boundaries. These environments keep data much safer than external, unmanaged tools. Art Gelwix | 23:08 I agree completely. AI works best for everyday users when it's invisible—like the underlying search and feature enhancements Google brings to Gemini. It should be a powerful feature within a tool rather than the main attraction. Ray Sidney Smith | 24:52 Augusto? Augusto Pinaud | 24:53 Apple's strategy lets others take early risks while they refine how AI integrates for non-technical users. Eventually, native integrations will leverage on-device context to automate everyday tasks smoothly behind the scenes. Ray Sidney Smith | 26:04 Apple is primarily a hardware and services company, so their timeline and incentives differ from software-first platforms like Microsoft or Google. They can afford to take a measured approach to embedding AI across their hardware ecosystems. Francis, go ahead. Francis Wade | 27:03 For the majority of users, background integration will be fine. But for those looking to optimize, we currently lack a structured framework for identifying exactly where AI can improve a workflow. Right now, it's mostly trial and error. Art Gelwix | 29:46 Building on that, working with AI requires learning its strengths and communication style, similar to onboarding a new team member. Problems arise when people expect AI to conform rigidly to flawed organizational processes without adjusting how they prompt or guide it. Ray Sidney Smith | 31:37 To wrap up this segment, embedded AI in major ecosystems like Google Workspace or Microsoft 365 offers two main benefits: reducing context switching to prevent decision fatigue, and enabling automated cross-tool workflows through standards like the Model Context Protocol (MCP). Ray Sidney Smith | 31:43 MCP acts as a universal open standard connecting different AI models securely to external data sources. It ensures controlled, deterministic outputs while allowing applications to communicate safely across systems. By connecting models and automation tools like Zapier, teams maintain quality control over outputs while linking spreadsheets, email, and notes fluidly. We'll pause here and continue discussing practical applications of embedded AI in our next episode. Ray Sidney Smith | 36:36 While we are at the end of our discussion, the conversation doesn't stop here. If you have a question or comment about what we've discussed, please visit our episode page at productivitycast.net. Feel free to leave a comment or question at the bottom of the page; we read and respond to them there. Voiceover | 38:54 That's it for this episode of ProductivityCast, the weekly show about all things personal productivity, with your hosts Ray Sidney Smith and Augusto Pinaud, with Francis Wade and Art Gelwix. Download a PDF of raw, text transcript of the interview here.

This week, we advance our series, The AI-Powered Professional, by exploring the "AI Coach." We'll dive into how AI is moving beyond simple task automation to becoming a force multiplier for personal transformation, focusing on "Accountability and Behavioral Design." We'll explore how these tools leverage data, psychological principles, and customized nudges to help us close the intention-action gap, consistently execute goals, and build lasting, productive habits. (If you’re reading this in a podcast directory/app, please visit https://productivitycast.net/152 for clickable links and the full show notes and transcript of this cast.) Enjoy! Give us feedback! And, thanks for listening! If you'd like to continue discussing The AI Coach: Accountability and Behavioral Design from this episode, please click here to leave a comment down below (this jumps you to the bottom of the post). In this Cast | The AI Coach: Accountability and Behavioral Design Ray Sidney-Smith Augusto Pinaud Art Gelwicks Francis Wade Show Notes | The AI Coach: Accountability and Behavioral Design Resources we mention, including links to them, will be provided here. Please listen to the episode for context. Loss aversion Stickk Positive reinforcement ELIZA Raw Text Transcript Raw, unedited and machine-produced text transcript so there may be substantial errors, but you can search for specific points in the episode to jump to, or to reference back to at a later date and time, by keywords or key phrases. The time coding is mm:ss (e.g., 0:04 starts at 4 seconds into the cast’s audio). Read More Voiceover Artist | 00:00 Are you ready to manage your work and personal world better to live a more fulfilling, productive life? Then you've come to the right place. Welcome to ProductivityCast, the weekly show about all things personal productivity. Here are your hosts, Ray Sidney Smith and Augusto Pinaud with Francis Wade and Art Gelwicks. Ray Sidney Smith | 00:17 Welcome back, everybody, to Productivity Cast, the weekly show about all things personal productivity. I'm Ray Sidney Smith. Augusto Pinaud | 00:24 And I'm Augusto Pinaud. Francis Wade | 00:25 I'm Francis Wade. Art Gelwicks | 00:26 And I'm Art Gelwicks. Ray Sidney Smith | 00:27 And welcome to our listeners to this episode of ProductivityCast. This week, we basically advance ourselves in our series, our ongoing series, The AI-Powered Professional. And we're going to be exploring today basically everything that we want to dive into how AI can move beyond simple task automation, simple task completion, to more of helping you with personal development, but just accountability and behavioral design. So let's talk about some of the tools we can use, some of the principles behind it, And we're going to start off with really discussing why we need... Technology to coach us in the first place. So Let's go ahead and dive into what the problem is, and then we can opine on whether or not AI can help us. So why would you need an AI coach? Who cares about having an AI coach? Francis Wade | 01:22 I had a friend who was a master's in exercise physiology. Shed clients. She was training them and she was meeting them at the gym every morning and She eventually gave it up because she said that with her Exercise Physiology Masters She was doing nothing more than bringing them all to bed. And delivering them to the gym. And standing by while they exercise. In other words, she wasn't actually applying anything she learned. All she was doing was being an accomplished nanny. It illustrates the reason why we do need this kind of assistance is because we're not, left to our own devices, we're not reliable. And there's a whole part of the coaching experience or delivering coaching experience That really is just about reminding on the one side and then holding accountable on the other. All the words. A lot of it has to do with just creating structure. And if that could be outsourced to AI, then, hey, Hold to us. Art Gelwicks | 02:22 AI coaching to me is... Better defined as coaching light. It doesn't carry any of the gravitas of an actual human coach. You can ignore an AI if it's telling you something that you don't really want to do? Yeah, it'll prompt you. It'll bug you. It can do all the things, but it's really... It's a way to get those reminders without the confrontation possibility. As part of the exercise. And I've seen people start to use AI in that kind of coaching approach and seen applications where they start to integrate this AI reminder into a process to encourage you to go through. And that's nice, and that's convenient. But it is still a device. So... I would definitely qualify AI as... Coaching light. A true coach is going to look at you and go, Yeah, but you can ignore that. You can't ignore me. Ray Sidney Smith | 03:17 Yeah. So stepping back to the core problem, which is that humans are really good at... Accomplishing things, utilizing accountability as one of the motivational paradigms. So we don't want to feel like we have reputational harm by not completing something. And so we can use accountability for that purpose. As I've talked about before, we have four layers of accountability that we can really think about. And the framework is that you have kind of self-accountability where you can keep yourself accountable to do something. You can have one-to-one accountability, whether that's a friend, a family member, or a professional. A professional coach, professional trainer, service provider and you are having them hold you accountable to do that thing, then you could step up to a group of then you can step up to what I call public accountability, where you claim publicly you're going to do something so that a vast majority of people beyond your close network know about you doing that thing. And so with these four layers of accountability, we know that we can get things done. And with AI coaching, we're really in that one-to-one accountability space. And I, like Art, really fundamentally believe that right now, at least as the technology is evolving, and how it's designed. Can't really replace a human coach. It can fill in gaps really well. I think that humans have the challenge of self-reporting We tend to be poor judges of our own consistency. We are not objective. And the AI can provide that objective, nonjudgmental, data to you on your actual behavior versus your stated goals. And since we have a human coach. Has a limited ability. To be available? The AI coach can basically provide nudges To be at a precise moment and place so you can have it monitor where you are, when you are and say, here goes this thing that you said you wanted to do and help you define whether or not you want to deviate from that plan. So say that I am in a particular application at work and I all of a sudden go to Instagram. The AI coach can now say, hey, Ray, I noticed that you went to Instagram instead of your work email. Is this a distraction? And now it can help just by that little nudge, helped me move myself toward the future. Planned activity as opposed to the unplanned activity that I was planning. We've had this indeterministic software for some time, but now we have AI versions of this, which is that it can block. Tools completely so that you can't go to a particular And that's a form of kind of coaching light, as Art was saying as well. So there's this notion that we're going to be able to do this. Providing a boundary to our access to things and that helps us stay on the pathway. So there's a lot of different reasons I think that can help us here in the coaching space but it's not a human. And even when we get to the concept of embodied AI, where we have robotics that are humanoid or humanoid-like robots, that then have AI embedded in them and they can be in your physical presence, I still don't see them as being the same thing as a full-blooded, bag-of-meat-and-bones person in front of you with the potential reputational harm of not showing up to do the thing. There is just something... Human to human about that I don't think a robot's really going to replace. Francis Wade | 06:54 Interesting you say that because my experience is that an AI coach, and I've not used the Actually, I have used an AI coach for my writing. But an AI coach... Is somewhere between just a Blind reminder, an alarm clock. On steroids. And a real person. It's moved up into that realm. But it's not doing the moving. I am. So what I'm doing is essentially I'm empowering people A voice. An automatic voice. To be more human than an alarm clock. And I think I could do some of the things you're talking about if I were to do it. I'm sure you've heard about the ideas around setting up a countermeasure mechanisms that involve creating a punishment for yourself if you don't. Accomplished the task. And I think there was a website. Allowed you to set up these punishments. And it was extremely effective. So there's nothing to stop us from having an AI persona. That For example, we say, if I don't stick to my diet this week, AI, you have the full permission to go into my... For the record. And tweet out to the whole world that you're punishing me in public for not... And you do something that's that I don't want you to do. And like, you praise up. Political party that I want to have no part of or something like that. But I sort of a punishment that creates a bit of a game that may not be necessarily dangerous or damaging in the long term, but it's at least somewhat annoying. I think I would respond to a game like that because I don't want my account tweeting out support for a party that I don't support. If that were the punishment, That would be enough motivation for me. ...

Stop treating AI like a simple search engine and start using it as your own personalized, tireless mentor. This episode explores how to leverage AI-powered tools to bridge knowledge gaps, master complex skills, and accelerate your professional growth through the science of adult learning. (If you’re reading this in a podcast directory/app, please visit https://productivitycast.net/151 for clickable links and the full show notes and transcript of this cast.) Enjoy! Give us feedback! And, thanks for listening! If you'd like to continue discussing The AI Learning Partner: Socratic Skill Acquisition and Rapid Mastery from this episode, please click here to leave a comment down below (this jumps you to the bottom of the post). In this Cast | The AI Learning Partner: Socratic Skill Acquisition and Rapid Mastery Ray Sidney-Smith Augusto Pinaud Art Gelwicks Francis Wade Show Notes | The AI Learning Partner: Socratic Skill Acquisition and Rapid Mastery Resources we mention, including links to them, will be provided here. Please listen to the episode for context. Andragogy vs Pedagogy Socratic Method Comprehensible Input / Comprehensible Output (in the context of language learning but generalizable) "The illiterate of the 21st century will not be those who cannot read or write, but those who cannot learn, unlearn, and relearn." ~ Alvin Toffler Future Shock by Alvin Toffler The Ultimate Deliberate Practice Guide: How to Be the Best  Strat Cinema (by Francis Wade) Raw Text Transcript Raw, unedited and machine-produced text transcript so there may be substantial errors, but you can search for specific points in the episode to jump to, or to reference back to at a later date and time, by keywords or key phrases. The time coding is mm:ss (e.g., 0:04 starts at 4 seconds into the cast’s audio). Read More The AI Learning Partner: Socratic Skill Acquisition and Rapid Mastery Raymond Sidney-Smith | 00:00 Welcome back, everybody, to Productivity Cast, the weekly show about all things personal productivity. I'm Ray Sidney-Smith. Augusto Pinaud | 00:06 And I'm Augusto Pinar. Francis Wade | 00:07 And I'm Francis. Raymond | 00:08 Raymond | 00:08 Wade. Welcome, gentlemen, and welcome to our listeners to today's episode. Today, we're going to be continuing our AI-powered professional series, And in this particular episode, we're going to focus in on how AI is... Helping people become better learners. Basically, how these tools are transforming personal and professional development. And so we're going to be talking about passive consumption, how we use maybe some Socratic method, and how we can do all of this through the creation of AI acting really as a personalized mentor tool. To basically challenge our understanding, accelerate our learning curve, and help us achieve proficiency, hopefully faster than before. And so let's talk about what traditional learning really looks like, and then we'll Talk about what the... Problems are in that space that we're trying to solve for when we're utilizing AI. Francis | 01:09 So the traditional model is that you sit down and receive knowledge from someone else. That there's an expert. Behind the scenes. But what's happening now is way more fluid than that. It's that. I'm somehow reaching out to an entity and it's reaching out back to me in real time. And it's an AI entity.  So no experience is give and take between you Something that's really smart. And where I am. And this give and take is not Obviously, it's not one directional, but It changes over time because I've noticed that cloud for example, is becoming better at finding stuff for me or teaching me stuff.  So it's like having this flexible space in which I'm being exposed to more things, I'm learning more things, I'm remembering more things. Because it's reminding me of more things. I'm accessing more options. And in so doing, I'm becoming a better professional. In my case, I'm thinking in particular of writing. I'm becoming a better writer. It couldn't have happened with a human being. The way it's happening with AI. And for the last year and a half, I'm really grateful for it because this kind of flexible space is Absolutely making me a better professional.  So it's again, It doesn't compare to anything that I've experienced before. So it's something that's brand new and it's evolving. I. Raymond | 02:38 Do, too. Augusto | 02:39 Hello. It is interesting. I'm going to talk about two cases that I recommend. For social media for artificial intelligence. One is I sometimes work with clients who have beaten up. Okay, beaten up as a child, beaten up as an early adult, beaten up. And one of the things that AI produce a different experience. Delusional, but a different experience is that AI will try to make you feel good. And I have recommended to a couple of my clients, go and have a glass of wine and a chat with your chat GPT. Okay, feel good. Because Feeling good, it's very important for productivity. It's very important for learning. It's very important. If you go, okay, I'm going to study this book. And you get into that, I'm going to study the book. But then you go like, okay, well... I don't know how to learn or I can't get into this material. The learning, the growing is very hard. Feel nice.  So that's one thing. But the second is how much Really? You can adventure. Into new topics, even if you don't want to master them. Okay. I remember Good day. Before Google, yes, because I'm that old. Okay. Where if you wanted to repair your car, okay, your best hope was to go to AutoZone or the equivalent and find a Hanes manual. Okay. And that thing was like the golden source. You could have every screw of that car had was on that manual. It was incredible. Then came YouTube and we asked how we did it before YouTube where you can see the video. Now it's even better. I have a chat for every vehicle we have in our house. Okay? And I can go and ask, not for, okay, how do you fix, no, for this specific model of this specific year of this. And it saves even more time. I enjoy a glass of wine once in a while. I'm very bad at it. Okay? According to a friend of mine, the reason is I don't drink enough wine. Okay? And if you get very good at it, you need to drink enough wine. I fail. Okay. But this is what is interesting. I've been putting into ChatGPT, okay, the wines that I enjoy. Okay. When I, and, What happened the other night, I was having dinner with some friends. We were in their house, and a friend of mine pulled three bottles of wine. I said, pick one. In the past, I will have picked based on the label. Guilty of charge. I know nothing about it. This time, I pull my phone, take a screenshot or a picture of the three labels and say, what matched my profile? And it picked something completely different to what I was going to pick. But It was actually fitting to the profile. It was a glass of wine that I enjoy because in the past what happened is I get the glass of wine and No, this one was. You can go from the mundane And you can really go with this. To the expert level. I was having a work issue with a VDI. For the people who don't know what a VDI is, it's a virtual desktop interface. And I basically have a client who gives me this VDI to do work with them. Fantastic. Except that I could not make it work for what I wanted to make it work. Chat GPT to the rescue? No. Okay, I went put all the details blah and it says the problem is you are trying it was an audio issue you are trying to make This on your iPad. The solution is try to remove I remove one of the layers it worked better and then I went and bought a And they're flying. Problem solved. The problem is the machine and the VDI cannot go and convert the audio to the VDI audio, to the iPad audio, to Bluetooth. Great. And remove two of those layers and problem solved. But these were things that in order to get to those conclusions, the number of trial and errors And the time that you need was... Among us. And now you can get those answers with two or three good prompts very quick. That bring me to the last point I'm going to make. I remember the first time I read Alan Toffer sentence saying, The analfabets of the future will be those who are unable to learn and unlearn. If he will be alive today, he will say that alphabets of the future will be those who can make prompts. And this is something when people say, then AI is going to take our work and the world and all this. Yes, it's going to change it. No question about it. And Terminator will be in the right of the corner. That said. The right prompt will really make this tool A tool? And if you don't learn how to do prompt and just think you can do what you did with Google, You are. Much likely dead in the water. Raymond | 07:48 There are a couple of things that I think AI can help with here in terms of learning. When you have full agency over your life, the way in which you learn is going to be different. When you have an employer who may be asking you to learn as you onboard into a new company, you may have to watch a whole bunch of learning videos to onboard into the company. That is a fundamentally different kind of learning than a teacher teaching you, a professor teaching you, a topic so that you can get a degree and move on in the education system.  So we need to think about the way in which we are thinking about learning as adults and that I think that perspective alone changes when you start approaching AI as what I talk about as basically being a learning partner. Because this becomes not just, I mean, there's so many different categories. I can go in a lot of different directions, but I will, I'll say that one, just learning on the fly, it becomes this wonderful learning experience....

In this episode, we continue our discussion of the AI-Powered Professional by returning to the AI Researcher persona. Picking up from the prior conversation (episode 149) on information overload and information toxicity, Ray, Augusto, and Francis explore how AI can help professionals move from traditional search toward more collaborative research, synthesis, comparison, and knowledge discovery. They discuss deep research tools, source verification, using multiple AI systems to challenge each other, Google NotebookLM as a grounded research workspace, AI-assisted book reading and writing, proactive information discovery, and the importance of treating AI research outputs as drafts or hypotheses that still require human judgment. (If you’re reading this in a podcast directory/app, please visit https://productivitycast.net/150 for clickable links and the full show notes and transcript of this cast.) Enjoy! Give us feedback! And, thanks for listening! If you'd like to continue discussing The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 2) from this episode, please click here to leave a comment down below (this jumps you to the bottom of the post). In this Cast | The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 2) Ray Sidney-Smith Augusto Pinaud Art Gelwicks Francis Wade Show Notes | The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 2) Resources we mention, including links to them, will be provided here. Please listen to the episode for context. ResearchGate Google Search Google Scholar Academia.edu ChatGPT Claude Google Gemini DeepSeek Google NotebookLM Google Alerts Feedly Feedly Pro Zapier Evernote Evernote AI Raw Text Transcript Raw, unedited and machine-produced text transcript so there may be substantial errors, but you can search for specific points in the episode to jump to, or to reference back to at a later date and time, by keywords or key phrases. The time coding is mm:ss (e.g., 0:04 starts at 4 seconds into the cast’s audio). Read More Voiceover Artist | 00:00 Are you ready to manage your work and personal world better to live a more fulfilling, productive life? Then you've come to the right place. Welcome to ProductivityCast, the weekly show about all things personal productivity. Here are your hosts, Ray Sidney Smith and Augusto Pinault with Frances Wade and Art Gelwix. Ray Sidney Smith | 00:19 Welcome back, everybody, to ProductivityCast, the weekly show about all things personal productivity. I'm Ray Sidney Smith. Augusto Pinaud | 00:25 I am Augusto Pinaud. Francis Wade | 00:26 And I'm Francis Wade. Ray Sidney Smith | 00:28 Welcome, gentlemen, and welcome to our listeners to this continuation of our discussion on the AI-powered professional. In our last conversation, we were really defining the problem around information overload and many of the issues that the modern professional or knowledge worker really deals with as it relates to all of the information. In our lives today. And what we wanted to do in this episode is continue that conversation. And talk through really how to take the sometimes overwhelming amount of information, but the treasure trove of information that we have every day coming into our world and really utilizing it in productive ways. I think that today, Thanks to AI, we no longer need to think about the concept of a search engine. We need to really think about this from the perspective of it being a collaborative engine and there is this kind of reality that it could be considered an answer engine, a research engine, all of these kinds of ways in which we can coin it. There are lots of different use cases today. We're particularly focusing in on the research And these more sophisticated AI tools can now perform tasks previously reserved for a research assistant or for you to take intensive manual effort to produce. And so let's talk through some of the ways in which you're utilizing AI for research purposes. And let's think through perhaps some of the pitfalls that people fall into as they're trying to use AI for research. Francis Wade | 02:12 I've been in a whole different world as a result of deep research in the last year. I remember before It was available. I used to do... Research via looking for documents like ResearchGate, I can search for a PDF using Google. I could search Google Scholar. You could go to academia.edu and What it would give back to me, these different sources, is Stuff that was close to what I was looking for, but not exactly what I was looking for. Matter of fact, it was often not close at all because I would have a specific question. And I'm trying to get a specific question answered. But I have to find somebody who actually answered that question in a document. Or maybe a book or in something. And usually I'd be looking for an academic source. And usually I wouldn't find anything.  So that's just, The game I would play was would be hunt and never find and that was 50%, 75% because I'd be looking for Esoteric stuff. Today, however, I have at my fingertips multiple A few different subscriptions to deep research and chat GPT does it for free up to a particular limit. And I can ask a very specific question. And to my shock, I can receive a plausible reply to my question Right. Pulls from credible sources for the most part. In the beginning, it When it first came out, they would pull from hallucinated sources, which was pain in the neck. But today... They've gotten to the point where They give credible... Specific answers to my very specific questions.  So my research has just multiplied by, it's hard to even compare what it was like No, Versal, what it was like before. Because I do so much of it now. It's really been a game changer.  So that's at the high level. The game is completely different for me right now. See you next year. Ray Sidney Smith | 04:15 And it will be different in a year from now even. More so. As the technology gets better. Francis Wade | 04:21 - I've told people that different parts of my work. Have undergone more change in the last year than in the last decade. 30 years before that, 20 years? And this is certainly one era that is completely different. Augusto Pinaud | 04:37 Sometimes digging and research in a topic and sometimes more than the papers, find the books. What is the book that, okay, I read this book. Now, What other... Go. Into this line and with books go on the opposite line.  Sometimes it's not only The papers, it's the one to give a more... Book rented? What books? Hey, I'm dealing into... And sometimes once I want to deal or work or research into this particular idea, Bye. Where can I find those books? Because you think, okay, I want to get, how do you get granular and now fast? But then now how do you find those book, those authors, who are the authors who I'm researching this, the same areas that I'm research, it doesn't matter if they're agreeing or disagreeing with you, but how you find them, that was a labor Of love. A lot of times, to find those books and to find those authors.  And then after that, then you needed to start Figure out which one was good, which one was bad. That job? One from weeks to hours. And you in hours can get a list that is better than what I was able to produce in months. This gets very interesting, the issue. Who's this? The expectations that now the people have. Because for what you're describing, similar to mine, it's not only get the information, now that just you were able to get to the sources pass through. But the other part of the process is still, you need to still read it, still download them, still digest them, still trying to connect those dots. That is still takes the same amount of time, but then First part, it's fantastic. The issue I see with this is I find a lot of people who think that find the sources is enough. And find the sources is just a step one of X number of steps to be able to get to the next conclusion. Ray Sidney Smith | 06:47 So I think about AI in a research context, when I say this is an AI researcher, Bye. That AI can still hallucinate. I know Francis is a little more, maybe more trusting than I am when it comes to these tools. But I've found ways to revalidate information even after it has pulled research And again, I Preface this always with everything I do with AI, I presume to be a first draft when it puts it out. And so I'm reviewing everything as though an intern handed it to me and it's an intern's work product.  So I need to make sure that it is correct. So we were all on the same page there. I think there are certain areas where AI is really good right now and where it will get better. I think that the deep research functions within all of the major tools that AI chat bots are pretty good right now.  So you have this deep research function in Claude Gemini, and ChatGPT. Personally, I've found that Gemini's does the best. I'm not sure why, but I just feel like it gets the most right when you prompt it correctly. And I don't like the verbosity around the deep research that Google puts out, but it's fine. It gets the data right, which is what I care about most. And that's one piece, which is you have this complex question and you need it to go out there and scour lots of sources and come back to you with an answer. And you don't know what the sources are. And I think in that sense, it can go ahead and find sources and then go ahead and do that analysis and synthesis that is really complex and therefore laborious and make it simpler.  Though Concern I always have with folks is that We're a little too trusting. So I'm going to, again,...

In this episode, we continue our series on the AI-Powered Professional by introducing the AI Researcher persona. Ray, Augusto, and Francis discuss how AI is reshaping research, learning, and knowledge work by moving us beyond simple retrieval toward active knowledge synthesis. Along the way, they explore the problems of information overload, low-quality information, over-trusting AI-generated answers, news and social media overwhelm, and what Ray calls “information toxicity.” The ProductivityCast team also discusses practical ways to curate inbound information, reduce cognitive friction, use AI-generated briefs and drafts responsibly, and stay in control of your attention while working with smarter tools. (If you’re reading this in a podcast directory/app, please visit https://productivitycast.net/149 for clickable links and the full show notes and transcript of this cast.) Enjoy! Give us feedback! And, thanks for listening! If you'd like to continue discussing The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 1) from this episode, please click here to leave a comment down below (this jumps you to the bottom of the post). In this Cast | The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 1) Ray Sidney-Smith Augusto Pinaud Art Gelwicks Francis Wade Show Notes | The AI Researcher: From Information Overload to Active Knowledge Synthesis (Part 1) Resources we mention, including links to them, will be provided here. Please listen to the episode for context. ResearchGate Academia.edu ChatGPT Google Gemini Google Workspace Microsoft Copilot Feedly Evernote Social Fixer The New York Times The Onion Raw Text Transcript Raw, unedited and machine-produced text transcript so there may be substantial errors, but you can search for specific points in the episode to jump to, or to reference back to at a later date and time, by keywords or key phrases. The time coding is mm:ss (e.g., 0:04 starts at 4 seconds into the cast’s audio). Read More Voiceover Artist | 00:00 Are you ready to manage your work and personal world better to live a more fulfilling, productive life? Then you've come to the right place. Welcome to ProductivityCast, the weekly show about all things personal productivity. Here are your hosts, Ray Sidney Smith and Augusto Pinault with Francis Wade and Art Gelwick. Ray Sidney Smith | 00:18 Welcome back, everybody, to Productivity Cast, the weekly show about all things personal productivity. I'm Ray Sidney Smith. Francis Wade | 00:24 And I'm Francis Wade. Ray Sidney Smith | 00:25 Welcome, gentlemen, and welcome to our listeners to this episode of ProductivityCast. This week, we are going to be continuing our dive into the world of artificial intelligence, which I like to call smart software, with another episode in our series of the AI-powered professionals.  So today we're going to be focusing on research and what I'm coining here is the AI researcher persona and how these new tools are really transforming the process of learning and researching and knowledge work for us. We're moving to a place where we can understand retrieval as basically active knowledge synthesis. And we're going to be talking through some of the challenges that folks face with regard to information overload and otherwise.  So let's first talk through the problems with research today. What do you find are the good or the positives around research today? And what are some of the problems that we experience? One of them we're going to talk about, which is information overload. But there are others that are out there.  And then we can give that context. Color with regard to how we can use AI as a researcher to help us with that process or those problems.  So what do you feel like are the primary problems today with research. Francis Wade | 01:47 I think in the past, very much a hit or miss kind of proposition. Where if you could find someone who had done the research... Answer the research questions that you have. You were extremely lucky. And the game was, how can I increase odds of success how can I be luckier So that meant that dwelling in places like Research Gate. Maybe at academia.edu.  Yeah. But ResearchGate was my goal, though. And For certain topics, especially the two that I specialize in, which are task management and strategic. Planning. I've pretty much got to the bottom of everything that I could find easily. It took a few years for each one, but I've sort of gotten to what I think is like the bottom. Where I read what they have to say. And I've noticed sort of where all the faults are why in neither field the research academics do is very useful in the real world?  You know, it's very esoteric and it's meaningful. Academics tend to write for each other. And for journals. And for advancement in their field. They don't like to go into areas that are cross bouldery that I like to mix and match different fields. They don't go interdisciplinary. It makes a real mess of the nice, clean, lines that they like to follow. And I don't like to go into areas that, you know, If you become an expert in an area where there's no conferences and no journals, no chairs and no departments anywhere in the world. If you go into an area like that, you know, you're sort of dooming yourself to obsolescence.  So with those problems, It means that for the two areas that I'm interested in, there's a, Not a lot of useful research. There is to find.  So finding something useful used to be a lucky proposition. And I would have to basically find someone who has enough experience in both areas to be able to do research in both areas so that they would have the questions. And finding that was like a needle in a haystack.  So it's always been difficult in the two areas that I Try to find research written on. It's always been an uphill struggle. Augusto Pinaud | 04:02 I think it's important to make an distinction between professional researching practices and the non-professional one. I agree in the professional researching the impact of AI has been incredible because now these people who Say. Knows better when they're trying to search and look into information. Cinta was not available. When you go to the noun informal research. It's interesting because I feel that we used to have Three levels of research, bad research, middle ground research, and good research. And now with the AI, we have gone and disappeared that middle because people think that they can find the answer that they believe is legit. Doesn't matter if it's true or it's fake information or what it is. They can go bump into any of these agents. Get an answer. And because of that, people stopped digging. Into is this really legit? But when you think in the world of productivity, When the first book of David Allen came out, we were talking about 2001, It was hard to find the information. It was hard to find the principles behind unless you have access to them. 25 years later, you can find A ton of information. The question now is, How did you know that information is legit or not? And that's why I think that middle ground has disappeared. You have the people who goes and do a prompt, and get an answer and assume Dad. The answer they're getting is the truth. And because of that, that's the stop of the research.  So what was part of the issues 20 years ago is, okay, I want to research this topic and now I have 20 books. No, they just go, ask two questions, get what they think is a truth answer, and take that That's a fact. Then you have the other level that is the people who are going to get that and try to figure it out. Is this a fact? They're going to try to dig out or it's not a fact. And what is the fact? What is interesting for me with AI is That middle ground, that guy who will have get that fact and tried to see why. I don't look legit or not legit. That disappeared. What I have seen is people getting the output that AI is giving them I'm taking them. It's a truth. It's an absolute truth that is even more scarier. And I have seen this In academic settings, I have seen this in professional settings, okay, where people go What is the obsolescence of this? Okay. Can you repeat that? I didn't get an answer.  So when that is, they never really dig. Hold on, did you want to do the vendor? Did you, did the chat GPT was floating you know, That, I mean, how been... Wonderfully. Last week. My son is a baseball fan, so he was watching the baseball and he wanted to see the score, so he asked, Madame Eyre. And But I may say, the game has not started. It was time for the game to start. That's true. The radio. Fuck. And you know, like, You've got me in the life. Damn, man. Give us whatever is for them. I've nothing to do. With the reality. And it was a great moment of, teach an opportunity because of that. If we will have the initial answer, what most people do, This other game has no authority. Okay, and you move on. But the reality is minimal. The game had started. We were in the middle of the game and there was a different score than what she was giving us on the third answer. And that is what Most people don't notice when they go into this research. AI will give you an answer. The question is if that answer is actually the answer or. Ray Sidney Smith | 08:11 Not. When it really matters, right? Learning that the game is not trivial, maybe not to your son, but to the rest of the world, you know, when it's... I will. Augusto Pinaud | 08:19 Make sure to tell him that right thing, that when the game is on, it's not trivial. You are going down in that scale of people he likes. You're going down, my friend. Ray Sidney Smith | 08:27 The unfortunate part is if you say, hey,...