AI Is Amazing. So Why Does It Still Suck for Project Managers?

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Galen Low: Hey folks, thanks for tuning in. My name is Galen Low with The Digital Project Manager. We are a community of digital professionals on a mission to help each other get skilled, get confident, and get connected so that we can amplify the value of project management in a digital world.

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Okay, today we are talking about the plethora of frankly amazing AI tools out there to help you manage your projects, and the absolute abysmal user experience of copying and pasting between them just to get the results you need for your project communications.

With me today is Devin Mahoney, CEO and Co-founder of QTalo, but above all, a project manager hell bent on easing the pain of project management using AI.

Devin, thanks for joining us today!

Devin Mahoney: Galen, thanks for having me. I'm super excited to be here and talking to this audience.

Galen Low: I thought maybe what I'd do is just kinda like start by zooming out because you and I, we've known each other for I guess like over a year now. When QTalo was in its, baby days, I guess I would say. And what I love about what you do at QTalo is that you've got this like really specific focus on zeroing in on challenges related to project communications.

You've been talking to reams of project managers doing the jobs. And the pain and the challenge that they're running into, and you've built your product around that. Everything from adapting project communications for their intended audience to streamlining the proverbial communications coming from everywhere problem so that project leaders like don't have to be burdened by that.

That like they don't have that friction in their day that we accept as like normal. But you've said, listen, that's doesn't have to be the case. Like we can use technology to help us around that. Really what struck me is that like QTalo has, like AI in its DNA, you set out to figure out how AI can be used to solve these problems.

I'm just wondering what was it that made AI the right ingredient for your mission of fostering a more efficient, more engaged, and more effective project management workforce?

Devin Mahoney: Galen, it seems obvious to us project managers, but it's not obvious to everybody else who's working on one thing at a time.

Wouldn't that be crazy just to work on one thing? For a project manager, your data is living in dozens of different places. It's in Slack, it's in email, it's in Jira, it's in your documents. The context for your project is fragmented across all of these different places, and so the reason that we have AI here is 'cause AI can help us in just all of these streams in real time, stitch them together and surface what matters to the PM.

We are trying to automate that, finding the needle in the haystack. Work so that dms can focus on planning, they can focus on risk, they can focus on their stakeholders instead of just chasing steps. Result here is less context switching. It's faster decisions and it's a consistently informed team without adding a ton of new manual steps.

Galen Low: I love that. It's like that there's so much like trauma that's like kind of bubbling up in my head as you say that because I very often do this where I'm like switching between apps. I'm like looking for that thing and I'm like, gosh, I wonder how much of my life has been spent just like trying to remember what TAB I'm trying to go to, or getting distracted by that.

Slack pops up and I'm like, oh yeah. Like I can solve that quickly. And meanwhile that really important thing I was supposed to do, like it gets pushed further and further into the future and it's like such a reality. And there are, there's just so many tools. Like one of the things that you and I had chatted about leading into that I should mention that like the working title for this episode is AI is Wonderful, so why does it suck so much to use? Which is like our way of ribbing, the sort of usability of the tech right now. Can you like talk to me a bit about what you mean when you say that AI sucks to use?

Devin Mahoney: Yeah. Galen, I love AI. I'm in here every day. It's helping me with everything. And so I just love using, it's just this magical thing for a project manager.

It shows up in two places. It can show up as an add-on into your apps. So if you're using Trello and Clickup, it's oh, here's our little AI fairy and it's gonna do something for you. Or it's a standalone ChatGPT style of okay, I am gonna chat with my friend, the AI and it'll help me with something.

So those are the two kind of flavors? No. When AI is a feature inside of an individual app. The problem, the frustration is they can only see a small slice of the project. Remember, you're getting slacked about all these things. You're getting emails from your customer. They're not inside of these specialized apps, and so you still have to copy and paste stuff into these tools to give the model the full context for what's going on.

It's even worse when AI's in a central chat. And again, I love using ChatGPT, like it's, I love the prompting. It's so much fun to craft the perfect prompt. But you have to do it. You have to get the prompt right? You have to get the follow up, right? You have to do the manual cleanup, and now you have 50 chat threads to go along with your 72, browser windows and you're now you've turned a project manager into a copy paste monkey again.

Instead of being the strategic leader that we were meant to be. Gosh, like really I have 50 different ChatGPT things and I don't know which one is the one I'm supposed to working on. And then the output. It's really good. It's better than I am, but it's 90% of it is right and 10% of it is wrong.

And you gotta be, you gotta put all this time into fixing that last 10%. And so does it save you time? Yeah, it saves you time, but it's you still have to put that effort in. So this is like the most magical technology. And you use it once, you use it occasionally, but you put it into your day-to-day workflow and all of a sudden.

So the thing that you were doing consistently is now clunky and it's not the same experience every time. It's not that same magical experience unless you get it. So it's getting fed the data that it needs from this unified cross tool context. So I love AI, but man does it suck today. We're gonna make that better.

Galen Low: It's very relatable and like I, my ChatGPT is a mess. It's like very disorganized. I was even just taking the PMI prompt engineering course. Lovely course. And it's kinda hey, like just create a spreadsheet of all your prompts and how they're working for you. I'm like, that's a good idea. Also, that thing you said about being a copy and base monkey and getting lost in all the prompts that I wanted to test and all the data because I need it in a central spot because I'm using all these different LLMs 'cause I'm testing them.

There's actually a lot more in common with onboarding a new team member. Woo. Who has their blinders on for whatever reason than actually like using software because it's like, cool. Let me give you the context. Lemme describe the thing that I'm trying to do. Okay. Yeah. Not that we need to refine.

It's not exactly like a tool workflow, it's an interaction. It's a sort of colleague style interaction, right? To kinda get the results and frankly, a lot of us just aren't great at that or haven't been trained at that, and it's a bit of a different thing. The other thing is just yes, like we're still figuring out.

All of the tools in tech, like there is a myriad of tools out there right now and the current guidance is try 'em all and see what works best for you and then keep refining. And the last thing that I wanna do when I'm adding all this time to figure all this out is okay, how am I gonna shuttle this information back and forth between some of the tools, some of which have AI features, like models that don't know what conversations I had with ChatGPT.

Like you mentioned, it is just it's clunky. It's amazing and it's clunky, right? It could be two things at once. Yeah. And I think it's I think it's important because I think we're very impressed with the output. It's fair that we are impressed by the output. A, it's not the end, it is just we haven't reached the like final goal standard of what AI looks like for project management.

And also it's like the way we're using it today is not necessarily how we're gonna use it in the future. Like even just the usability.

Devin Mahoney: I totally agree and I can't wait for that future, but also you have the tool you have now and yeah, I gotta figure out how to use it.

Galen Low: And the other thing I was gonna say we need to build it as well, which is what you're doing, which I love, I wonder if I could take a bit of a side quest and I for folks listening, I will tie it back.

But one of the things, Devin, that I notice about QTalo is that like you've got a really strong focus on privacy. You have a bit of an unorthodox take on the matter. I was wondering if you could just like talk to me about like why privacy is important to you and why it should be important to people who lead projects, not just sensitive data, but just the way we work.

Devin Mahoney: Okay, good question. And Galen, I'm a cybersecurity guy and so like privacy is, it's in my DNA and I could talk your air off about SOC two, which I'm not gonna do because this podcast is only so long. But let me talk about privacy for a project manager, because for a project manager to do their job, we keep a private working memory and some of us use our notes app.

Some of us use our spreadsheets, some of us use actual paper. This is, these is my notes as a project manager, and this is where your half-baked ideas go. This is where you're scribbling your notes before you actually write an email or commit something to your system of record like Jira or Salesforce.

There's no cost to use it because it's just for you. You don't have to worry about whether it's tagged. You don't have to worry about whether it's even correct. It's a liminal workspace. It's gotta stay private. It's where your critical thinking goes. It's where your rough drafts happen. It's where the real risk planning begins.

And our goal at QTalo is to honor this liminal zone. We help you pull insight. From these drafts without prematurely publishing them, it gives you this opportunity to think aloud safely and still benefit from this shared context of what's going on in your system or record. So we're projecting this creative buffer.

We're helping bridge this gap, and our goal is to yield cleaner, accurate updates for teams, for your leadership, for your customers, all your stakeholders.

Galen Low: I love that so much because there's yeah, there's stuff in my notebooks I don't really want anyone else to see ever. And I love that notion that privacy, we always think of like sensitive client information or, sensitive financial data or, personal identifiable information from, like in healthcare.

But I really like this notion of me as a user. I want to benefit, I want that notebook that is an LLM, right? Where I'm like writing stuff and it's okay, cool. Do you want me to like correlate that for you? How about this? Asking me questions. But that's my like working context.

It's not my presentation context. And I would love to know that the broader model in my tool is not training on all of my like rough draft nodes. And then someone's going Hey, what kind of project manager is Galen? They're like scatterbrained really? Like it's a loose cannon. He starts sentences and he doesn't finish them.

Like it's wild. Like I don't want that entering the ether, of my tool and like coming as a lay person in this conversation where I'm like, I don't know. It seems like all these models are training on pretty much everything. I don't really have that much line of sight without getting into the sort of compliance side of things.

I don't always have line of sight of what's being shared where. Honestly, I'm not like committing to memory all the terms and conditions for all the tools that I've signed up for. I probably should, but I'm okay I'm taking for granted the idea that I should probably approach it with caution, but that it's for the greater good.

Whereas I think what I like about what your your angle is yeah, like there should be this layer where you still benefit from what you're training your personal sort of model on within your tool. Ideally not just jumping around to all these things. That should be like a thing that's known.

It's don't worry, you're in the zone where like this won't get shared with your colleagues and you're like, cool. And then it's would you like me to print this to your colleagues? I was like, yes, now. Now it's fully baked. Let's go. Just that level of clarity I think is just, it demonstrates that well, to pay you a compliment.

It demonstrates that you understand the way project managers work. You're not just building software, which I think is like the real IT thing. The thing that gets me excited about what you're doing.

Devin Mahoney: Thanks Galen. Really appreciate it.

Galen Low: I'm gonna pay you a compliment and then I'm gonna backhand you with the devil's advocate thing, which is we've been talking about how there's so many like productivity tools out there.

There's so many AI tools out there. Part of your criticism, if I'm picking up correctly, like part of your criticism of modern efficiency is that we are using too many disparate tools. So my devil's advocate question is like. Why did you feel like the world needed one more tool in QTalo?

Devin Mahoney: It's a great question, and everybody asks that question of every tool.

These productivity tools, these communication tools, they multiply faster than anybody can possibly integrate them. And the budget that a company has for these new tools, it hasn't kept pace with the tool acquisition budget. So what I mean is like we got all these. This information that's spread out across all these tools, but there's no budget for consolidation, and so where does it have to happen?

It's on the project manager, and so now we are having to do this consolidation by hand. Thankfully, it's a lot easier to implement because of AI. It's a lot easier for us to do this by hand. It's almost worse. It's almost worse because it's possible for us to just copy, paste everything into ChatGPT. Now it's our job to do that instead of thinking through like where all the data is.

So QTalo isn't just one another task application. In fact, our goal is to get you into QTalo and get you out of QTalo as soon as possible. We're making this the connective tissue so that your existing stack can work as a single system. I actually think there's plenty of room for other consolidation tools besides QTalo.

We, we need more of them because efficiency is really about every, making everything work together. And so by sitting next to all these other tools it eliminates this like swivel chair work. It reduces the sprawl of licenses all over the place 'cause it's really only the PMs who need this and it pays for itself in recovery time.

You something because a lot of s who work with engineers, there's this concept of technical debt that accumulates during the engineering process. There's operational debt too. Every time we add a tool, every time another team is using a new tool. We're adding to the operational debt and this consolidation effort helps us pay down that operational debt so that we can have our communication channel focused.

That's the goal. That's why the world needs QTalo and other tools that do consolidation.

Galen Low: I love that notion of operational debt, like it's so true, but I also love that sort of like clarity of recognition that. We're gonna have tools, but also that it's not that all of our tools need to string together into one sort of big brain tool that's the tool to end all tools.

It's kinda tie it all together. It's like a web. You have to make sure that like your important tools that are related to one another connect to the same node. That Node could be QTalo. Doesn't mean it's your only piece of software that you're opening every day. It just means that, yeah, this is a node that is strategically stringing together.

Some of the software that you're using, because like you said, we can't integrate with every tool as it comes out, maybe Zapier and Make, but even then, like that is that must be such a severe, intense process to try and keep pace with every API versus okay, I. Here, we've made a decision on these tools.

We don't want to incur a lot of operational debt, but we do need them talking to each other better so that we can do our jobs better. Otherwise, we're really blunting the like overall advantage that we have, where AI's gonna come and take over all the admin and you're gonna be strategic. Just kidding.

You're copying and pasting. Like it's a, it, you know it, it's a bit of a bait and switch actually how it works right now. It is. It is. I'm wondering, maybe you could just talk to us about like what's coming up for QTalo. In what ways are you like attempting to solve this problem and just what you're excited about?

I'm

Devin Mahoney: actually pretty excited about this command center that we're building, you said at the top of the podcast Galen, but like we are project managers. We are building for project managers and that let us have a very narrow focus on only things that project managers need. For instance, we've got AI prioritization, so like a PM you just started your day.

Other people have been working in other time zones. You wanna know what is on fire today. What signals do I need to pay attention to across email and chat and ticketing that I need to work on right now? This is my day. I need summaries. 'cause like lots of stuff happens. I'm not on top of everything all the time.

I need automatic summaries of all the key facts, the next steps, the links to the source so I can get right back to it. I need a unified search 'cause I can't tell you Galen, how often this literally happened this morning where somebody sent me something, it was trying to find it, and I didn't know if it was an email or in some random Slack channel.

And the unify searched is the thing that saved me because it, I'm getting all my information all over the place. I need workflow checklists, PMs, like when we get a notification, it's like a lot of work. And so like normal people you get an email, you're like, okay, fine, I'm gonna respond. I'm done. A PM gets an email.

You gotta do five to seven different things. It is such a lot of work and no one really appreciates that. And so these, the workflow checklists allow you to build a list of tasks and your life kind of sucks because you have to do the seven things because at least you can enumerate the seven things and you can check them off your list so you can finally get rid of that email.

You can take it. Out of your world and we're providing context that all the timeline, the files, all the decisions. So PMs can get up to speed. They're just switching context into it and you don't have to scroll through all these apps to in order to get there. So that's exactly what our command center does.

It's really focused on the PM we're getting you in, telling you the things you need to do next and getting you right back into the work that you're doing in the other apps.

Galen Low: I love that. And yes, very relatable. The number, like if you look at my search history across tools, it's the same search. It's just, I was like, where was this? Where said, yeah, so I'm searching the same keyword across multiple tools to find it. That sounds really exciting. I love what you're doing.

Devin, thank you so much for this chat. It's been a lot of fun getting your perspective on just AI, our AI clutter, AI usability in the future.

Devin Mahoney: Thank you, Galen. It's been a pleasure talking to you.

Galen Low: Alright folks, there you have it. As always, if you'd like to join the conversation with over a thousand like-minded project management champions, come join our collective! Head on over to thedpm.com/membership to learn more. And if you like what you heard today, please subscribe and stay in touch on thedigitalprojectmanager.com.

Until next time, thanks for listening!