AI Won't Kill Remote Jobs It Will Supercharge Them (Marissa Goldberg)

I think that the biggest opportunity is around growing the potential for async first work. I think that it's extremely hard and takes a certain personality to instill an async first environment to a remote workplace. And it relies a lot on discipline, it relies a lot on communication. It's very, very hard for teams to get into that rhythm. I think what AI is doing is making it so, so much easier to distill information, to make it available when it needs to be available. So it could have a really big potential in creating more async first work environments and hopefully then increasing remote work opportunities and making sure that there's more schedule autonomy. So while I'm extremely happy that location flexibility was added with Pandemic Remote, where like, everybody went remote overnight, realized that it was possible and that, you know, the company wouldn't go under, and it was actually great to be remote, they still haven't tapped into all, all the, the perks that could be part of remote work. There's a lot of location flexibility. Now. We can build on that autonomy with time flexibility. Instead of just having standard nine to five work days, making them more conducive to, to parents and people with disabilities and people who maybe are on like the autism spectrum or any of those kind of things where you need to work differently, we can apply those principles and create a personal work day that would work works best for you and make sure that you are insanely productive doing it all. So I'm really hopeful for the opportunities that it presents.

Hi, everyone, and welcome to this next episode of the Freedom of Work podcast. So we're on this show today. We're going to be talking all about the sort of incentive section of remote work and AI and all the bits in between. And we are joined by Marissa. So we'll be hearing a little bit about her personal journey into remote work, sort of any misconceptions, challenges, and how she's helped teams and individuals thrive in this distributed environment. So, Marissa.

Yeah.

Should we dive in and you can start telling the audience a little bit about yourself and what inspired you to start a remote work package?

Yes, sounds good. I'm Marissa Goldberg. I'm the founder of Remote Work Prep, and we provide AI powered operational solutions to distributed teams. I'm also the author behind the remotely interesting newsletter for remote leaders and the Idea Kitchen newsletter, sharing simple recipes for using AI.

Yeah, no, I really love the recipes with AI. That's the first thing that sort of caught my attention alongside the remote work thing. I think they're both really Good, interesting things that people are wanted to utilize. So, yeah, I guess let's start with remote work prep then. So what actually inspired you to start this journey?

So I started working remotely back in 2015, so quite a while ago. And I realized pretty early on that there weren't a lot of resources for remote leaders in how to effectively manage distributed technical teams, which was what I was doing at the time. I loved working with people all around the world, but there were issues when it came to collaboration, when it came to time zones, and I really wanted to find the best solutions so that I could continue working in that manner. So I started experimenting, I started sharing, and it was just supposed to be on the side. I was an engineering manager at the time and it wasn't supposed to be anything big. But then people started coming to me, like, how is your team in less meetings than me, but getting more done? Like, how do I make this work? What do I do? So I started coaching on the side, started remote work prep in 2018, and then 2020 happened and as you know, everybody went remote overnight. So things kind of exploded from there.

Yeah, I think that's actually quite a rare story considering that you sort of seen it coming before it even flared up and happened. I think it's. It's great to sort of people start acknowledging saying, like, how are you actually not speaking to each other in person but being so productive? And I think they're the core questions that people ask themselves and start to question this sort of remote work lifestyle. Definitely. So guess when you first started off, was there any sort of maybe misconceptions that you've heard about remote work or that you've encountered and how you've sort of proven that wrong along the way?

I think that the, the biggest misconception that I still hear people talk about today is that under work is more common than overwork. And what I've actually found is that overwork is way more common than under work. In all the teams that I've worked with over the past seven years, what typically happens is people really enjoy working remotely and they want to prove that they're working constantly. So they're kind of showing constant availability in Slack, constant availability for meetings, keeping their phone on during night and day. So as soon as they wake up, they're logging into Slack and responding to pings before they go to bed. That's the last thing they do. And honestly, it leads to a ton of burnout. And the practices that companies put in place address under work instead of overwork, which just Exacerbates the problem.

Yeah, absolutely. I think that is the biggest misconception because people think that people are at home, so they're slacking and they're not as productive as if they could be in the office face to face where their managers may be one desk away. I think, yeah, the reality is completely the opposite. I think remote workers are very like feel proud and privileged to have what they have. So maybe they're scared of the risk of losing it, so then they maybe don't have as clear boundaries. Especially being at home, you can't sort of switch off because you're not walking physically out of the office. And yeah, I think having that sort of switch off period is definitely what the misconception is. And it gets difficult for those remote workers definitely to have like a natural break, a natural line break in the day. Because if maybe you're based in the uk, but you've got a US team, they're going to be coming on a little bit later in the day. So maybe your most productive hours are a little bit later than usual, but maybe that morning you've actually been really productive in your own project. So, yeah, it's really hard to find that balance and making sure that you are maybe visible to the leadership team when they're online, but making sure you're not being too visible without affecting your own sort of. Yes, burnout, definitely.

Absolutely. And that's why it's so important for the company and leadership to kind of set the standards, encourage people to create virtual boundaries, educate their team about what best practices are so that they don't get burnt out. Because in the end, if the team member is burnt out, that's bad for the team member, it's bad for the company. So all around, not a great position to be in.

Yeah, definitely setting those sort of boundaries from a leadership perspective and making sure that they feel that they can be, the employee can be trusted in whatever they do. So that doesn't mean that they have to overwork to feel like they're being trusted as in individual, rather than viewing the outcome of the project that was delivered in the morning when maybe they were offline and like measuring that in that type of way. Yeah, definitely. Some. I guess as we're jumping forward into the world of remote work and distributed work, I guess the world that is the word that's popping up a little bit more is this word of AI and it can be used a lot in day to day words. But also in this remote work setting, I think people are starting to question how they can use it more. So in terms of remote work, then, are you seeing any AI tools perhaps change remote team management today?

That is a big question, because there's a lot of them at this point.

I know.

It can be as simple as ChatGPT or Gemini or whatever chat tool you're using. There's also niche tools like presentations, tools like Gamma, and then there's, of course, you can go into agent workflows using things like Zapier agents. So there's a ton out there right now, and it really depends on the problem you're looking to solve.

Yeah, no, definitely. I think that's the core of it, isn't it? Whether you're. The ChatGPT is maybe you're using like a marketing team team one, where you've sort of trained it to know your brand voice and your vision and your values and what will be on your careers page, for example, and you're building it from scratch to help you maybe build a rapport with that and have that for your team. But yeah, exactly. If you're maybe in a sales position, you may want to scan your customer calls. If they're common problems occurring, how can that be done? And that could be done something with cpa. So, yeah, I think that's probably one of the key messages here is to start at what is the core problem that you're trying to solve? And maybe if you're doing something so repetitively, could you maybe automate that? I think sometimes it's also tricky when people are trying to automate something that they don't know actually how to do it in the first place. I think it's like there's a problem. It's like, let's try and maybe solve it first and then have a little look at how we can automate it. Because if you don't know much about the problem that you're trying to solve and then you're automating it straight away, it's like you don't actually know if it's worked or not and how to measure that, whether you've actually tried to do it in the first place.

Yeah, it's really hard without that context. And one of the biggest issues that we're currently seeing is that because it's in the headlines and because there's this narrative being pushed that if you don't use AI, you're falling behind and people don't know what exactly to use it for, they instead start with a tool. So they think, oh, I've heard this tool in the media, a Million times now I might as well try to use it and try to implement it on my team. And that's a quick way for things to go south and not for that tool not to be used for that tool not to be helpful, even if it's an excellent tool because you're starting with the tool rather than with the problem that you're looking to solve.

Yeah, absolutely. And you actually may be creating more of a mess than what you actually had as the problem in the first place. So, yeah, I think that's definitely key.

And then.

Okay, so yeah, I guess that's what we are hearing in the news quite a lot. People want to adapt and change the way they're utilizing technology because they don't want to fall behind. But then also we've got the other side of people saying that AI will replace your team. And I think if there's like the two pieces, people want to stay on top of it, but then people want to utilize it and people don't want it to take over. It's all like this influx of different voices coming all around this topic. So I guess how can leaders maybe avoid this mindset?

They need to set the standard and they need to set kind of what their goal is with AI and how they're going to be using it. So with the teams that I work with, we always make it very clear up front. We take a people first approach to AI. We think that it is not going to take your job, it's going to give you superpowers. So when we look at like what are we applying it to? We're asking three questions. We're asking what do we want to protect, what do we want to free people from and how can we use AI to give our team superpower? So we're starting from those questions and kind of curiosity and wonder versus force and lecture and these kind of negative emotions. So that's where we start from, is we try to instill curiosity, wonder, we incentivize experimentation, we incentivize making mistakes. Mistakes. Because people are going to make mistakes early on. So. And we incentivize education. So that's where we like to start.

Yeah, I think that's also a really nice point to make, like making mistakes because that's humans make mistakes, but also AI can make mistakes. So I don't think at the moment anybody knows exactly the right answer in the first place. So people can't be fully reliable on something because it might not have interpreted all of the data right, for example. And yet definitely this, like I Like the protect and free and superpowers. I think that's a really like nice thing to think about because yeah, curiosity is like and the imagination is just there with the human brain, isn't it? So having these type of things, creating relationships, being creative only by that person, so utilizing those tools in a way that can help the initial thought for example is going to benefit you. But yeah, as you said, you don't want to force it upon people and it becomes then overriding maybe their thoughts and what they thought originally and it sort of takes away exactly that human element. So yeah, I really think that's a nice sort of takeaway there.

And then you have to over communicate too. Like you have to be like, you have to understand that the narrative that's being pushed online and in, in the world is extremely negative right now. So if you want it to be more positive within your team and within your company, you have to set that standard and override what's being told outside the company.

Yeah, no, definitely. And have that voice as leadership to push that through to people so that, yeah, people aren't feeling like they're going to be replaced as well. Just pushing that through as a voice of leadership. And I know you also mentioned this sort of human centered approach to AI. I think that is the key to this. But what would you sort of be, what does this mean in practice? Do you have like an example of where this is sort of been utilized?

Absolutely. So what we're looking for is things that cause a lot of friction that people feel are very manual. One of the first questions we ask is do you like this task? If it's something that they love to do, that's not something that we, we want to touch. We want them to continue enjoying that, that task. But if it's something that's time consuming, that's taking away from the skills that they're really good at and they really love to put into place, that's a great place to utilize AI. We're also looking at things where, like you talked about, where people have a lot of in depth knowledge where they've done this thing a million times over and over and over again. They know the system inside and out. They know the pitfalls that we're looking out for because then we have the training data in order to create something that's going to actually be helpful versus something that's kind of just patched together and isn't actually going to be used to solve the problem. So that's, that's what we start with.

Yeah. No, definitely. I like that question. Do you actually like this task? And if you like it then maybe there's a way to make it easier for you to still actually enjoy the task because that might be something that energizes them in a day to day life. Maybe that task is why they come to work. So the second you start maybe saying oh, should we automate this? It's like, oh, feel like you're sort of treading on.

Took away the joy.

Yeah. The career path though that, the certain tasks that they love in that day. So making sure that it's maybe those, yeah. Repetitive tasks or diligent tasks where you sort of have a sigh and you have to get into it or you're putting it off till the end of the day. And I think those sort of tasks are the, the ones that yeah, should be looked.

Why not use AI for you know, like I can make your day better by automating something that's, that's a perfect use case for it. Some examples are things like when you have to communicate something over and over again in remote work. We know this from, you know, having worked this way for years. But sometimes like you're taking a doc and then you're turning it into something a shorter form or you're, you're converting it into like for Slack versus for Notion and it's not necessarily the best use of your time, especially if you don't enjoy it. So why not use that data? Because you're starting with a great source of data. That's another key thing to kind of flip it into different forms and format it very quickly so you can move on to the tasks that are more suited to creating scale and doing good things with your company.

Yeah, no, I think that's also a good point about like the like document and everything as well, especially in the remote team because I know things like Notion and documentation sites. They have an AI bot now. So if you've got all of your career benefits on there or maybe certain things that you want to search through the benefits scheme on and if it's all in a notion document, someone who is joining the company can search that so that the message doesn't have to repetitively be sent to somebody. They can just say or like a question to the HR team. They can just literally search there and if it's not there then maybe prompt them to say I'm having struggle in finding the answer to like maternity or my PTO or something like that. And then have that as like a first instant step saying search our Database first through the AI tool and if it's not there then maybe you put that forward. So yeah, making sure definitely everything is documented. So then it's standardized and then it's all sort of in there. So then, yeah, it can be automated and sent out. And yeah, use AI like the chat tools as well. I think they work really well, especially with the frequently asked questions pages and things like that on a sort of website. I also think that works well from like a customer point of view.

It's also been great for an async first company point of view because you're giving more resources to team members who are across different time zones. So like one person may be asleep, the other person has a question for them and before they might have had to wait until they woke up or you know, like it would have been a very manual process to put all that information in one place so that they have it later. Now it's much easier to one get that information documented, have people find that information and make making sure it's sourced in a way where it's solving the actual question instead of wasting a ton of time sifting through tons and tons of documentation.

Yeah, exactly. Because that's only going to waste time of the individual trying to find the information, but also the person that thought they put it on there originally and it becomes chaotic and it wastes time and it's very, it's less productive than. Yeah, if they would have maybe asked them in the first place. So yeah, absolutely.

A lesser known example of this as well is being able to document the ones that they still can't find so you can capture all of those searches and that way you can ensure that you have the resources that these teams need in order to find their solutions afterwards. So taking an iterative approach, instead of assuming, oh, I put in this AI solution, it's one and done, it's really using the tool to learn and grow as well.

Yeah, definitely. Because as I said, someone from the UK or the US might type the question differently in the way that it's formatted in the system. So I might say like holidays, how many holidays do I get? But someone in the US could say PTO and it's like. Or someone in different country could say something else. So the wording that what each person in that different country, that how they describe what their benefit is, for example, may not be in the system correctly. So yeah, I really like that if there's a way for it to understand that maybe, oh, people in this country are actually asking it in this way, let's also make it so this may be some form of backlog that if they ask this, this, this and this, it all relates to this one search.

Exactly.

Yeah, I think that's really good way of sort of using that documentation as well with Async. And then I guess we sort of spoke about these examples, but in terms of the sort of productivity and teamwork flow as well. Do you have like a practical example of where AI has improved that again without replacing people?

Absolutely. So one of the. One of the areas that has been little known, like a lot of people aren't really talking about it and it's less shiny, but it's extremely practical and usable, is adding Slack emojis to a thread, having AI look for that Slack emoji, and then automatically summarize and move that information into the correct place. So if you're using Slack for a while, you know that it can kind of become this crazy, crazy system that you can't really find stuff in. It's really hard to search. The threads tend to get long. And so if you're like searching and you end up finding the actual thread that you were looking for, you then have to spend time reading all through all these messages. So what we've built for several teams that has been extremely popular is if they add it, like checkered flag emoji to a long thread, like a thread where they're making a big decision, the bot will then automatically grab all of those messages in that thread and then create and then add it to a database. It could be anywhere, but let's say a notion where it says like, this is the decision that was made. These are the choices that were considered. These were the main stakeholders involved and this is why we decided to go that direction. And this has been really helpful because, like two weeks down the road, because you're working on so many different things and the team's like, why do we make this decision? Or later on when a new person is added to the team and they don't have the context and they start questioning why things were made a certain way. It's all there and it's really easy to find. And then of course, you can add a bot within Slack so you could say, oh, what did we decide about X? And it can pull from this database. So that's one that's been great. Use case of using AI agents to kind of like fill a hole that people didn't necessarily know they needed.

Yeah, because I think Slack is an amazing tool and I know it has all of The AI sort of summary things. But I think in that way I think it's good because it says these were the things people were thinking about, those were the decision and this was the decision. I think it sort of takes it another step further into why people use Slack. It's a big sort of company wide decision making tool, project management tool, communication tool. And to have that all summarized in this sort of AI agent I think is a really unique way of like project managing different channels. And I know the channels can get almost exhausting. You have to mute certain channels, you have to make sure that you're in certain channels and especially with remote work it's you want to make sure you're maybe at a certain social channel or the UK one or et cetera, et cetera. So it's sometimes already a little bit can be overwhelming for someone first joining the company if they have to see for everything, make sure they know where everything is before they then have to find a thread to make sure they know who's who in the thread as well. So maybe for a new person it could be also good to say, oh, this person, this person and link to the Slack or LinkedIn and things like that and having it all linked. So yeah, I think that's a really good way of definitely helping the team's workflow. And especially for a new person joining.

It also has multiple use cases, so it doesn't necessarily have to be for decisions. Another big one that managers are using it for is performance reviews. So with performance reviews it tends to be like whatever was most recent, whatever's top of mind. With this agent you can add the emoji to different notifications and things that team members have sent and then it pulls it into one place where you can see, oh, for the last quarter this is what they worked on. These are the wins that they had, these are the call outs and it's all in one place. So it's very easy to create those performance reviews with all of the information from that quarter versus just what's top of mind.

Yeah, no, I also really like that because I think the thing with performance reviews is when people have to sort of self assess and self analyze themselves on a set page and it has to, you have to sit down and think, okay, what did I do this quarter? Whereas this is a way of me maybe communicating with my manager and saying, oh by the way, this project's complete if you want to take a look at the link here because you'll always be linking in Slack as well. And it's Very integrated with different systems, Trello, Jira, et cetera. So if you all in that with the emoji, I think that's really, really good. Genius.

It's one that has been extremely popular and I think it's because it fills a hole where we are relying on humans for what humans are good at and relying on AI for what humans are not good at. So in this case, memory is not necessarily the best thing for humans to be relied on. Another example of this is I'm not a great designer. I have an engineering background, my designs are pitiful and so if you ask me to build a presentation, it's not going to be extremely pretty and it's going to take me a long time to put together because I'm just not skilled in that area. Versus I create all the content, I know exactly what I'm sharing and I put it into a tool like Gamma and then it's just pulling exactly from my content so that it's, you know, what I intended to say. But it's creating a beautiful piece that's actually going to be easily read and shareable and saving me time in the process as well. So that's another one. It's all about filling those gaps versus just using a tool for the sake of it.

Right, exactly. And I think that's the key there because a lot of companies will have templates on maybe a shareable Google Sites or Google Sheets. Sorry, that can. Or Google Slides that can be copied and then utilized with all of the maybe logos in there, the typeface, how to sort of sell each slide, which is perfect because it's got all the details in there. But. But I completely get this because the content's already there and it's been discussed maybe in a Slack channel about the presentation. It's going to be shown. So yeah, I really like that. It's like you're filling maybe a gap that you didn't really know that was needed, but it's really beneficial to making that project a lot more seamless and helping and assisting with what is maybe already existing and already there. My lord, I see not how this pertaineth to the data analyst position.

If thou can extract a sword, thou can extract data. Thunder and badgers. From whence do ye hail, mighty peasants?

Vancouver.

Vancouver, nay, we cannot employ internationally. The fees, the red tape, it must be put back. Be gone, Canadian.

So as I was sort of looking at your different blog posts and stuff, I came across these two terms which was human in the loop. Safeguards and transparent interfaces. So how do These two things help teams trust AI and maybe want to give a little bit of intel about what are these two things in case anyone doesn't know as well first.

So human in the loop first Human in the loop is critical for a human centered approach to AI. And honestly, if you're going to get the best results from AI, you need a human in the loop process right now. And what that means is that a human is involved in the process. So it's not just handing everything to AI and being like, go do it and then just trusting that they'll get everything right and not hallucinate or anything like that. Typically it involves things like at the beginning of the process, you have documentation that a human has built has or a system that a human has done multiple times over the years. So it's using something that you're very used to, you're giving it to AI to improve in some way and then you're following up with a human, verifying that what they did was accurate and to the quality that they would expect. So you start with a human, you add an AI to increase speed and scalability, and then you end with a human to maintain quality. So that's just one example of it. So that is human in the loop. And then when it comes to the transparent interfaces are important because as we know, AI can hallucinate, AI can just say things without them necessarily being true. And so some people just have some understandable trust issues with some of the answers provided. So the increasing transparency is big. Just when we talk about like remote teams, we want to be transparent by default for a number of reasons. But to increase trust, to increase communication, collaboration, all of those kind of things, it's the same thing when it comes to AI. So we want to know like, where did these answers come from? What are you pulling from? And it could be as simple as kind of like having a notebook. Lm they'll have a little number next to a paragraph to show like, oh, this is the source that I pulled this information from. Perplexity kind of does something similar. It's just really increasing the knowledge behind how the AI got to that answer.

No, definitely. Yeah. I think both of these are like really great ways to sort of see how teams can trust AI. But yeah, Human in the Loop I think is. It's a nice little. Rolls off the tongue really nicely. But yeah, I think what you mean, like keeping the human up the beginning and the end and utilizing that in the middle, sort of making sure that they have the ethical side or the judgment side. From the human and making sure that it's sort of protected against that AI, maybe blindness and not knowing it as a contextual basis or what is sort of truly it means, I think, and I think that also goes to show with the transparent interfaces, it can, yeah, it can definitely create an answer if you asked it many times to what the answer was to something that even the answer isn't there makes you think what the trust about it. So yeah, I think that is, that's something that people are also beginning to question, which is good because it means that the human element is still key to that approach and people first approach.

And it will be for a long time. It's also an efficiency mechanism. So if you just kind of like the difference between giving one line instructions to like ChatGPT versus giving it context and documents and a structured prompt, you can tell that there's just mega differences in quality and the speed in which you're going to find the correct answer, find the solution that you're looking for just between those two. And that's why human in the loop is just so important.

Yeah, no, definitely. I really like this term. It's one that I'm going to be continuing on to use. So thank you for that, Marissa. I guess then as we've been talking about sort of teams and these tools, I guess sort of from an overarching view of leadership, is there like one thing that leaders perhaps overlook when they are adopting AI in their teams?

I think they overlook the thing we talked about before in that the narrative is extremely negative and if you want people to be on, if you want people to be focused on like how they can use it in their jobs, you need to be upfront with why you want them to use it, how you're approaching it, taking a people first approach, being very clear about what to use it for versus what not to use it for. Because this is still very new and we need to educate people on what it's good for and what it's bad for. What are the risks to look out for? How do you know about hallucinations? There's just a number of factors and it's just like any new skill. So if you were to like learn the violin or learn how to play the piano tomorrow, you're going to make mistakes. It's not going to sound right at first like. And you need to expect the same thing when it comes to AI. This is a new system, it's changing every day, so it's really hard to keep up with. So being able to reward Mistakes and reward experimentation, but especially rewarding it in a way where it increases transparency. So we tend to like to have like an AI experiments channel in Slack to share like, oh, this was my before and after. This is where I got stuck. This is where AI gave me something totally ridiculous. So we want to share it publicly and be transparent by default as with anything else with remote teams. And that really helps people feel comfortable with, hey, I'm not the only one who doesn't know how this works. I'm not the only one who's getting a bad answer. And everybody can learn together.

Yeah, no, I think transparency is, is definitely key in this sort of AI adoption, especially where people can openly maybe showcase their roadmap. Have you said, I really like that having like a channel where people can openly say I have this problem. I'm maybe trying to utilize AI in this way. It's not really working. And also people have maybe used that tool before they can help you. We can work together as a team to make sure that you're getting the best outcome and that transparent relationship that you can have and make sure that everyone's maybe in it together also is protecting you as a group as well. Because yeah, not there's going to be mistakes and I think it's nice that mistakes get made by us and AI so we're not just standing alone by that. I guess then it's. As we're speaking all about AI, I think it would be nice to. For the listeners as well. If there's any sort of personal AI tools that help you to maybe stay productive while you are working remotely.

There's a number, I think because of what I do with Idea Kitchen. I'm on the end of the spectrum where I'm using it for a lot of different things right now that I don't necessarily think is for everybody, but things like preparing for meetings, making sure meeting notes are taken, making sure that they're then turned into the format that's going to be useful for later, making sure they're automatically shared to appropriate channels. These are all things that, that, that people can use every day. Other things that they could use are a lot of people are not using the, the scheduled task feature in ChatGPT and they can use that for things like, oh, I'd like to get a weekly summary of all the AI updates for the week with XYZ tools. So the specific tools that they use so they're not just receiving all news which can be very overwhelming and honestly not that applicable to you. You can use a Prompt like that with scheduled tasks tasks in order to get something specific to you. Other other things are just on the personal side like I love to use it for things like meal prepping and for. I've. I recently had a skincare product that was discontinued that I was in love with and using deep research to find new skincare that had similar ingredients. So kind of like a dupe. Those are all great use cases. So like things that that you wouldn't necessarily think would be helpful end up being really helpful for saving time and saving energy. And I just encourage everybody to kind of like experiment because I think the most useful places to put it are things that you actually use it for versus just the shiny things people are are saying.

Yeah, no, definitely. I think first starting off is that yeah I think tools like the when you've got a meeting and it's sort of summarized and making sure that the format is there for people to also say I think that's a really good tool that's been outcome by meetings because especially if there's an hour long meeting that you maybe can't attend because of different time zones or various situations. If there's a summarized meeting at the end of it it's really easy that there's a summarized thing and at the end of it often has has assigned tasks to different people as well. So even if you weren't in the meeting you can have an assigned task to do certain things and making sure that once you read those notes you can maybe jump into the recorded meeting if you needed to. But yeah, a lot of the time it's really well summarized with assigned tasks at the end of it which help you if. Yeah if you can't attend the meeting and then yeah also I love this the prompts thing. Yeah I didn't know this was a thing and I will definitely be looking into that a little bit more utilizing things so you get the most out of what you're currently using. But yeah, also experimenting as well is definitely key and I think maybe it goes on to maybe what the second question I was going to say was about what advice you'd give someone maybe hesitant to try AI tools but I think that perfectly answers it. Just experiment and. And I guess just try things.

I will expand on that just a little bit. So the biggest piece of advice is to not let yourself get overwhelmed. So if you try to keep up with everything everywhere all at once it's just going to be too much right now for anyone including myself who's doing this and doing a whole newsletter on this. So I have to be like deeply involved in the space. I think most people need, most, most busy knowledge workers need is they need just in time solutions. So instead of looking at everything everywhere, you are focusing on the problems like we talked about, then identifying that this could be a good use case for AI based on just knowledge of first principles. Like these are the things AI is good at, these are the things that humans are good at. And so if we come up with a problem that's in this box, we're going to try to find AI solutions for that specific thing instead of just trying to keep up with every AI tool, every AI use case going to get too overwhelming. So just the just in time approach is, is great and you don't need to keep up with everything because it's going to change tomorrow anyway. So even if you know what's happening today, it's, it's a, it's a fresh new ball game tomorrow.

Yeah, I guess that pulls into like the meeting summaries, things that are just easy for you to pick up with or a quick generating maybe a first reply email to something or if you get looped into a thread, summarizing the thread threads, things that can make you maybe. Yeah easily pick up on things and help you to get the grips of something quicker than maybe you would have if something like this didn't exist. Yeah, I really like that. And then I guess how do you think AI can reclaim focus time and reduce context switching for remote workers?

I think we're still building on this so in a number of ways. So one, we have async resources where like we talked about where someone's sleeping and there's like a chatbot ready to answer those questions. There's tools that will pull in all of your data across several different tools. So like Slack and Notion and everything all together and that way you can find everything in one place versus like thinking, oh, where, where do I actually go to find this? So having those solutions as well, I think that we're still working on it in a way. So one of the things that I'm currently building is kind of like a coach that will help you through like oh hey, your context switching every hour. We could do XYZ to help with that. So that instead of having to come up with the solutions themselves, they're kind of given a prompt of like, hey, you could go this direction, you could try this thing in order to reduce that context switching and have your workday be a little more flow intensive versus interruption intensive. So I think we're still getting there and I honestly I'd give yourself grace with all of this. I think that we'll get there eventually, but it doesn't need to be perfect right now.

Yeah, no, definitely. I really like that sort of utilizing it in a way to help you maybe prioritize tasks tasks or if there's, if you're getting maybe loads of notifications from different teams and different people. But you want to maybe specifically only focus on messages from your manager today because you're both working on a certain priority of a task. Just having that nudge to be like I'm going to mute all these people for you because you keep going and looking at that in a project with your manager, for example, and having that if it could nudge you to see and help you see what matters.

I also think that not everything needs an AI solution. So in this case, like this is a very common issue. And to instill virtual boundaries will help you without using AI solutions. So making sure that you have, that you're muting, you're turning off slack when you're doing deep work, that you have a specific schedule that you're using different browsers for your work in your personal life. Like I have a whole list of, of virtual boundaries I can share with you but like making sure you have the best practices in place is always important because that foundation is necessary in order to add on to it. With AI powered solutions.

No, definitely like you can be as productive as you can be, but maybe only in a certain amount of time. And I think little things like this like setting a timer for two hours or maybe even 20 minutes and just making sure that for that 20 minutes you are only doing that one time task. Sometimes a time pressure for me and I know other people helps you to just solely focus on that because once that time is off or say the Internet's turning off, if you don't do that task, it's just having that and that's also can be something that you do yourself. Definitely.

Yeah, I use that with, I use the Pomodoro clock with Brain fm. So it uses kind of like focus music and it keeps you in a rhythm and then you have, you hit your relax tax period and then you take a little break. So that's, that's a great tool for that. Not AI related, just a regular tool that I've been subscribed to and paying for for years. Another AI one that is related is one of the things I do when I go to lunch is I start a deep research prompt right before I go to lunch. So. And it's related to whatever task I want to do when I come back from lunch. So if I need to write an article on xyz, I'm going to say, hey, deep research, can you find me like this information? And that way as soon as I, I come back from my computer where it's typically like hard for me to dive back into work, where I get distracted by notifications, I see this brand new research report and I start scrolling through and I'm like, oh, okay, there's an idea, there's an idea. And I'm instantly like jumping back into work versus kind of having to like force myself back into work.

No, I really love this. I feel like this is definitely something I'll take on board because it's, it's the lunch lull, isn't it? You feel it may be the half an hour before lunch because you're thinking about lunch, because you're hungry for lunch, because you're kind of a little bit, or you've just got back, you sit down and then you slowly go through your emails and it's like you've maybe used up two or three hours thinking and doing and doing the afters of lunch, for example. So just in this instance, this is not what always happens. But yeah, I totally get. But it's having that being able to delve back in I think is a really amazing tool to have. And having that research and scan which is what you were going to be doing while you sat down and waiting for it to do that, it's already starting doing that. So yeah, I really like that one and I'm definitely going to be taking on that tip. I really like that.

That's great.

And then I guess as we look in to sort of the future of remote work with AI, we've spoken a lot about different tools and managing remote teams and sort of even the day to day life there. But I guess maybe of your opinion or from your sort of research, what's the biggest opportunity you think that AI is bringing to remote work in the next five years?

I think that the biggest opportunity is around growing the potential for async first work. I think that it's extremely hard and takes a certain personality to instill an async first environment to a remote workplace. And it relies a lot on discipline, it relies a lot on communication and it's very, very hard for teams to get into that rhythm. I think what AI is doing is making it so much easier to distill information, to make it available when it needs to be available. So it could have a really big potential in creating more async first work environments and hopefully then increasing remote work opportunities and making sure that there's more schedule autonomy. So while I'm extremely happy that location flexibility was added with Pandemic Remote, where like everybody went remote overnight, realized that it was possible and that, you know, the, the company wouldn't go under and it was actually great to be remote, they still haven't tapped into all, all the, the perks that could be part of remote work. There's a lot of location flexibility now. We can build on that autonomy with time flexibility. Instead of just having standard nine to making them more conducive to parents and people with disabilities and people who maybe are on like the autism spectrum or any of those kind of things where you need to work differently, we can apply those principles and create a personal workday that works best for you and make sure that you are insanely productive doing it all. So I'm really hopeful for the opportunities that it presents.

Yeah, no, definitely. I think with what you were first saying, I think making asynchronous work just seem completely seamless because it's, it is an extremely hard task for companies that are remote to make sure they are implementing this because it's very easy for a company to slip into one to two to three meetings a week with the same person that are then an hour long. And then it's suddenly not seeming like the async culture that was originally meant to be in place because things aren't being actioned after the call. So you're having another call and another call. Maybe there's not any project management tools that are in place so you can allocate different tasks after the meeting. And yeah, I think that is making sure that then that's where it's seamless. As you said, like no more digging through Slack thread channels, making sure that through a notion doc it's searchable and that the context is all there rather than digging through and it's only going to sort of get better as well. And also with the async work is that people aren't waking up maybe in America and thinking, oh, I was the last person to wake up today trying to make it like an async workday that maybe doesn't have the 24 hour set 9 till 5, but having it as just a sort of continuous clock so that global people don't feel like they're the last to wake up in the, in the, the world of the project, I think that's gonna help and how things have developed and summarized and as it sort of continuously works, it's going to be a great way to unlock that and it's only going to help them be better. For that Async collaboration especially, there's a.

Huge potential for innovation. Yes, I'm very excited, definitely.

But then obviously I guess there's that sort of the human centered side. So do you think there's any sort of risks if, if AI is adopted without this human centered approach?

I think that I'm one person, so I can't really say, oh, this is the future of the world. However, I do take the approach of looking at history and thinking about like how is history repeating itself here? We had the introduction of computers and computers were supposed to take our jobs. Then the introduction of the Internet. There was things that people were upset about, like when spreadsheets were invented and thinking that would do away with accountants. Has it? No, it has done away with accountants not using spreadsheets and doing like manual ledgers. But we still have accountants. We still constantly bring in new jobs. So with each phase of computing we've brought in new interesting jobs with like the Internet or with mobile or with social. There's always something new up ahead. I'm not going to be worried about it taking over human jobs until. Until the companies that are actually building the AI, like OpenAI and anthropic and so on and so forth are no longer hiring people which if you look at their job sites, they are hiring a lot of people right now. So that is just not my concern right now. I think that we. I will continue taking the approach of a human centered approach to getting it added. I continue to believe that's the best, most useful way to get it added into your day to day life. And I think it has the potential of creating a great future and making your workday a lot better. So that's kind of my thinking right now. But of course I'm one person.

Well, of course. No, I really like that approach. I think it's definitely where we need to be at the moment, that human centered approach and utilizing it. And yeah, it's actually creates more jobs as AI engineers. There's so many now more jobs than there was. So yeah, it's nice to look at in this way and definitely good to approach it in this way and not go full force with the AI because you're then going to lose the human centered element of the sort of whole thing. So yeah, thank you for that. And then I guess as sort of a final maybe takeaway of how leaders, how can leaders balance technology adoption with protecting team culture and sort of human strengths at the same time?

Going back to that question about what do we want to protect is always the first question when it comes to implementing AI in a human centered way. So being very clear on what are our values, what is important to us, what can AI not fill the gap in right now? What can it fill the gap in so that we can increase the areas that humans are fantastic at in terms of taste and judgment and intuition. So just finding those holes and being very clear on the path about the values that you're going to build with.

Amazing. I think that's a really final good summary of everything that we have been speaking about today. So I guess as sort of summary we've sort of talked through how AI is definitely not replacing people, but it is sort of amplifying that human potential, making sure that we're using it in ways to grow and freeing up time to be maybe a little bit more creative and connect whilst those sort of automated and maybe tasks that you are dreading on doing or looking at that element. And yeah, looking ahead, I think it's going to create more ways and better ways of working, reducing perhaps context switching, empowering teams to work smarter and not longer and making sure people are still using that, that as a thing. But yeah, thank you so much. I think it's been, we've really gone through and found some amazing key points from this topic. I know it's a topic that people are interested in at the moment and speaking about. So yeah, thank you so much for joining me. I guess with anybody's got any questions, once this goes live, Marissa will be typed on our LinkedIn. And yeah, if you've got anything further to share around the topic, Marissa, you can send that over and we can also share that, that to, to anyone that asks any questions. But yeah, thank you so much again for joining us. It's been absolutely amazing and I'll speak to you soon and thanks everyone for tuning in.

Yeah, thank you so much for having me today. I'll make sure to include the recipes on exactly how to do the things we talked about today and check out Idea Kitchen if you're looking for ideas on how to use AI.

Amazing, thank you. Bye.

Thank you. Bye.