
The AI Assistant: Automating Administrative Friction and “Shadow Work”, Part 2
2026-05-11
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53:09
In this episode, we continue our conversation on The AI Assistant as part of The AI-Powered Professional series. Picking up from Episode 147, the ProductivityCast team shifts from using AI merely to offload administrative friction and shadow work to thinking about AI as a true collaborative assistant. Ray, Augusto, and Francis discuss how to define roles for AI assistants, train them with useful context, manage multiple AI tools and personas, review AI-generated work as drafts, and build prompt workflows that help professionals get better results while staying firmly in control.
(If you’re reading this in a podcast directory/app, please visit https://productivitycast.net/148 for clickable links and the full show notes and transcript of this cast.)
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In this Cast | The AI Assistant: Automating Administrative Friction and “Shadow Work”, Part 2
Ray Sidney-Smith
Augusto Pinaud
Francis Wade
Show Notes | The AI Assistant: Automating Administrative Friction and “Shadow Work”, Part 2
Resources we mention, including links to them, will be provided here. Please listen to the episode for context.
Microsoft Copilot
Google Gemini
Google NotebookLM
ChatGPT
Claude
Evernote
Zapier
Raw Text Transcript
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[00:00:00] 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.
[00:00:18] Welcome back, everybody, to ProductivityCast, the weekly show about all things personal productivity. I'm Ray Sidney-Smith. Marco is jumping out. And I'm Francis Wade. Welcome, gentlemen, and welcome to our listeners to today's episode, where we're gonna continue our discussion on AI, and this is our series on the AI-powered professional.
[00:00:44] in our first episode, we started the discussion about the concept of utilizing generative AI. in this episode, we also started the process of talking about what an AI assistant is really [00:01:00] like, talking about some of those administrative frictions, being able to get rid of, and automate that out of, your world to some extent, and dealing with shadow work as well, defining shadow work and so on and so forth.
[00:01:13] We're gonna continue this topic into discussing today about really how to partner with your AI in a lot of ways, what the collaboration process really looks like. And so I'd like for us to discuss shifting using AI tools as a mechanism of just kind of offloading something, which it can do, but then becoming a more collaborative partner with that particular AI tool in order for it to become a true AI assistant.
[00:01:45] And so I'm thinking of things like how do we ensure that AI is taking over the right kind of work and that it's not taking over the work that we should be doing, and how do we maintain control and accuracy? And of [00:02:00] course, there are a bunch of boundaries and ethical considerations that we should be thinking about and some thoughts about the future.
[00:02:05] So let's start with what are some of those first principles, for us to be able to create a true collaboration partnership with our AI assistant?
[00:02:19] Sure. I'm thinking about this from the perspective that If I want to work with my AI assistant, I need to choose particular categories of work in which it can actually collaborate. So for example, I want it to be able to help me take a rough sketch that I've made on either my iPad or on paper, and then to have the AI turn that into a full-fledged drawing, a full-fledged cartoon perhaps.
[00:02:49] So the AI assistant is acting as my cartoonist, and so that's a role that I want the AI assistant to do. And while I can draw my [00:03:00] own cartoons, 'cause I've taken this drawing class, I feel competent to draw, you know, one part of a cartoon, but then it can fill in the rest by creating the other panels of the cartoon.
[00:03:13] And this is really helpful to me because now I can make the first drawing. It can be roughish, you know, to give it the idea of what I want, and now I can help it help me, quickly generate more panels and get the cartoon done by virtue of that. But the idea is that it's now a role that I want it to continually be helping me with, and so that is the cartoonist role.
[00:03:38] That's just one. I mean, like that, it doesn't, it doesn't have to be just role. It could be any number of things. But it's just like, that's the kind of thing that I'm thinking about. well, in the last episode, we sort of established the notion that, an AI assistant is like an intern who remembers everything, but doesn't have a whole lot of judgment.
[00:03:56] isn't, a really good judge of, you know, the [00:04:00] things, whatever it is that we happen to be expert at. It, it's too much to ask the AI to rise to our level of, insight and understanding. Having said that, there's a whole bunch of stuff that now looks to me that, it looks different to me because I can now see it as automatable.
[00:04:23] Like the example that you gave of, doing repetitive drawings or repetitive, animation. There's a bunch of things that I, and the list keeps growing, which is why I don't have a fixed answer. but it does start with this notion that I have an untrained intern that has infinite memory and infinite patience and doesn't have an attitude and works at all hours.
[00:04:48] And if I train that intern, then there's more and more things that the intern can do, and there's gonna be a new app tomorrow that- allows the intern to [00:05:00] do even more. So it's hard to say what specific role because the roles keep changing, and they keep being added to. if anything, I would say there's maybe a rule, which is that, try to give the intern as much as possible, but always be the person of last kind of decision.
[00:05:20] Be the one who's at the end checking to make sure the intern didn't make some, you know, gross error. So if there's any rule, that's the rule that I'm applying right now. Try to find more and more to give and then be the person at the end to do the checking. and then don't try to stress the intern out with judgment calls.
[00:05:42] and even the limit-- even the line on what I call a judgment call is changing with AI because it's getting better, You know, the AIs that I use, I use memory, so it understands me and what my judgment calls are, better and better each day. So it's a tough question to answer.[00:06:00]
[00:06:00] So just stepping up a level, I would say that just the concept of establishing roles for the AI is the first principle. It's not necessarily that you're going to ever be exhaustive in terms of creating the roles, because sometimes the role you need for a specific chat is defined in only that chat, and then there will be ones where you're gonna need that as an ongoing kind of recurring thing.
[00:06:29] It depends. You know, last episode I was talking about that wine help. You know, help me identify wine that I may enjoy based on my profile and educated that profile. But same thing on, on the professional side. I have a client who we, because of what they do, they, it's a report that is run every morning, and that report gets to them.
[00:06:53] And the problem is it's impossible to, to analyze it long enough. You know, you can see the report daily. You can maybe go a [00:07:00] couple days back. But human, it's hard to really create trends and things from that specific report. Where it's been very cool is a play on the role we create a chat for that neural network, okay?
[00:07:15] And now that report is dumped, for lack of a better word, into this chat. But this has now allowed us to identify trends not in three months, not in 90 days. Hey, this server last time this failed, okay, it was seven months ago. And it failed for three days. That information no human can provide for me. Okay?
[00:07:38] But allows you to start seeing that, and that make it very, very specific. Okay? Same thing, when you write. After you train, yeah, it required to train the intern, but after you train, say, "Okay, this sound like me. This doesn't sound like me." You know, one of the things that I love to do is when I get an [00:08:00] idea, okay, let me discuss this idea with the content of, okay, or the ideas or the understanding that AI has of X person.
[00:08:08] And you can say, "Hey, I want to look what will be the perspective of this text if Einstein read it." assuming you, you know what, physics and stuff. But that give you... Is the perspective you're going to get accurate? Well, it may be, it may not. But it will give you a counter that is very interesting.
[00:08:30] One thing that I do very often is find the arguments in favor and against this i- this concept, this idea that I'm working on. And it now get... You know, I think the definition, part of the definition or the issue is this, for a lot of people, is the first time they get access to an assistant, to an administrative assistant,
[00:08:53] For most people, that is a concept that they heard, that they, you know,...
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