In an era where back-to-back meetings and fragmented schedules are the norm, how can teams reclaim focus time and achieve deep work? Matt Martin, co-founder and CEO of Clockwise, is tackling this problem head-on with an AI-powered calendar assistant designed to create smarter schedules. In this conversation with Nataraj, Matt delves into the complexities of modern work, from the “maker versus manager” schedule conflict to the surge in meetings post-pandemic. He offers his perspective on the evolving SaaS landscape, the real-world impact of AI agents, and why many new tools feel half-baked. Matt also provides a look inside Clockwise, explaining how they leverage AI to not only optimize individual calendars but to orchestrate entire organizational workflows, ultimately giving teams back their most valuable asset: time. This discussion is essential for anyone interested in the future of work, productivity, and the practical application of AI.
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Nataraj: To get started, can you describe to the audience what Clockwise is and how your customers use it?
Matt Martin: At its core, Clockwise is a very advanced scheduling brain. We connect to your calendar, whether that’s Google Calendar or Outlook, and you can use it as an individual. We start to analyze your calendar when you connect it, understanding the cadence of your meetings, when you tend to work, your working hours, and when you like to take breaks. We ask you a few questions to get to know you a little bit better. Based on that information, we start giving you suggestions on how to optimize your schedule for more time for high-impact work. Where Clockwise really hits its groove is when you start to use it among a larger group of people. Clockwise can look at the interconnection between you, other attendees, their preferences, and how to optimize calendars holistically. We do this at scale for some of the best companies in the world, like Netflix, Uber, and Atlassian, where we help optimize schedules for almost the whole company or complete engineering departments to give more time for high-impact work, meet with the right people, and have a sane work life.
Nataraj: You are living in this world of calendars and meetings. This reminds me of an instance a couple of years back when Shopify CEO Tobi sent out a memo saying you can cancel any meeting you want and we want to reduce the number of meetings happening in our organization. What is your general take on the frequency or number of meetings happening in a company? What trends are you seeing in how companies are optimizing their meetings?
Matt Martin: In a lot of ways, Clockwise goes all the way back to a famous article by Paul Graham called “Maker’s Schedule, Manager’s Schedule.” The reflection in his article was that, often inside software engineering organizations, the two modes of operation conflict. The managers control the schedules because they’re setting the cadence of meetings—syncs, standups, one-on-ones, team meetings—and they get a lot of their productivity done in meetings. Whereas for makers, people like software engineers and designers, they need large chunks of time to go heads-down on a project and get in flow to be able to tackle things. The first thing I would observe is that different people have different demands on their schedule, so there’s not really a one-size-fits-all here. I love Tobi’s memo because I think it’s always a good idea to clean out the cruft on a regular cadence and reset the baseline because things build up over time. But I would also caution that meetings aren’t inherently bad; it’s just another way of collaborating with peers and making sure you can get your work done. The question is, what are you trying to accomplish and who is the audience for it?
There are some almost gravitational forces when it comes to meetings. One is that we’ve seen in our data that the larger the company gets, the higher percentage of time people tend to spend in meetings. As you have more people in your orbit, the cost of collaboration and coordination goes up. Another thing that happened is when COVID hit, the quantity of meetings spiked way up because as people went remote and hybrid, they were trying to figure out how to replace a lot of the content of an in-office environment with meetings. That subdued a little bit, but it never came all the way back down. There’s an overhang from companies going remote, and even today, you do see some split between in-office companies and remote companies in terms of volume of meetings.
Nataraj: Is there any interesting trend? One of the things that happened after COVID, for me at least, is an increase in non-scheduled meetings. You just have a question and you all get on a call spontaneously, sort of replicating the hallway chat remotely. Do you have any statistics on a spike in those and how they’re doing right now?
Matt Martin: That tends to be one of the sources of the split between remote and in-office because when you’re in the office, those conversations still happen, they just don’t get recorded formally on the calendar. If you’re remote, you do have to reach out. There are informal ways to do that, like a quick Slack huddle, or you could move some of that to asynchronous conversation, which is a good pattern. But one of the phenomena is just that there’s a shift in the medium. Instead of bumping into someone in the hallway or going over to their desk, you have to find a Zoom meeting or schedule something on Google Meet. The frequency goes up. The amount of time spent in synchronous conversation, however, doesn’t actually vary as much with remote or in-office because it’s just a different type of synchronous conversation. It depends a lot on the culture. At a place like Apple, where it’s not uncommon for software engineers to have their own dedicated private offices, that sort of synchronous conversation in the office is much lower than a place that’s a wide-open office environment.
Nataraj: Clockwise started before ChatGPT and all the LLM mania started. It feels to me that there’s now this rethinking in organizations about what type of tools we are adopting. A typical thousand-person organization might have 100 to 200 SaaS products. We are seeing a shift in how many products you’re adopting, and there’s also an accelerated pace of launching new features. Do you see this happening in your perception of how sales are going for your product or other products when you’re talking to other founders or customers? Is this a change in narrative, or is it more of a narrative than it’s real?
Matt Martin: It’s interesting that you bring up Zoom in the context of AI tooling and acceleration of feature adoption because I think there’s a more significant undercurrent that’s not related to AI, which is the correction a couple of years ago from a zero-interest-rate environment to an environment where money isn’t free. That had a significant impact on SaaS buying, renewal, and adoption cycles, especially among more mature organizations. We saw a huge wave of consolidation, removal, and re-evaluation of tools that we hadn’t seen in the lifecycle of our business before. I think Zoom’s proliferation of product development is downstream of that consolidation effort, not AI. They saw that if you’re just video conferencing software, it’s easier to rip you out. Everybody pays for Microsoft 365 or Google for basic email and calendar, and both come with video conferencing. So Zoom is trying to replace that office suite. It remains to be seen if they can be successful, but I think that’s the more significant trend.
When it comes to AI tools and adoption, that has been a bit of a resurgence and a correction in that downturn in buying. There’s definitely been top-down appetite to find ways to add to the productivity and capacity of the organization with those tools. I will say, however, the trying and retention is way different. I’m quite proud of Clockwise’s retention; people use it and they like it. But as I’ve talked to IT leaders and CISOs, there’s a lot of experimentation, but there’s a lot of churn. A lot of these AI tools look interesting at the outset, but it’s hard to measure what they’re contributing to the bottom line. It’s an interesting mindset where you have this massive constriction in what people are willing to spend for software, but then a real increase in experimentation. Some of that conservatism in terms of what they’re actually buying is still there.
Nataraj: I ask because there’s also this hype around what an AI agent can do. Every new AI agent platform offers things like optimizing your calendar or increasing productivity. The problem I see is the form factor isn’t fitting the promise. When you get into things like revenue management, where a CIO wants to see the number, it’s not yet easily correlated, especially in these agentic, chat-based form factors. Could you talk a little bit about that disconnect between what AI agents are promising and why that disconnect is there?
Matt Martin: A lot of this is the basics of software selling that have been around for a while. Ultimately, the buyer needs to see the case for the return on investment. The reason there’s so much hype around AI is that people have seen the impact it can have in various facets of their job, so they’re clamoring to find other areas for that application. But to your point, if there’s revenue acceleration that the CRO isn’t actually seeing, they’re not going to buy the software, whether it’s an agent or a piece of SaaS. In many of these areas, the efficiency gains are notoriously difficult to measure. Clockwise undeniably helps people be more productive, but our ROI measurement problem has always been there. We’re productivity software. We can tell you about all the dedicated time we put back in schedules, which to some extent is a measurable hard ROI, but some buyers look at that and ask, “Okay, you made their schedule more flexible, but did they actually get more done?”
There are interesting new pricing models being experimented with. You see places like Sierra doing outcome-based pricing; for each ticket they take off a customer service person’s desk, that’s what you’re paying for. That’s much closer to hard ROI because you’re offsetting real employee time and salary in a concrete way. I think it’s difficult to find those measurables often, though. It’s difficult to find that hard translation of outcome and to have accountability all the way back. People are experimenting, and it’ll be interesting to see where it lands, but a lot of these problems echo through software sales since the 70s.
Nataraj: How are you leveraging AI in terms of creating new features and products? Can you give examples of how you’re using AI within Clockwise as a product?
Matt Martin: I’ll answer in two ways. First is operationally, how we are developing product. The second is how Clockwise as technology actually uses AI. On the first point, we have a truly AI-native product development cycle where people are utilizing tools at every stage to accelerate results. One of the clearest points of leverage for me is the collapsing of product research and prototyping. I have designers who are literally spinning up their own interactive prototypes, whether in Figma, v0, or Lovable, and putting them in front of somebody. Previously, that was quite costly. Now you can do it quickly without worrying about bugs. That accelerates development cycles. With all the tooling we have, you can spin up a lot of paths and experiment with the best one because you can get there faster. It still requires a lot of human review, or you’ll create a really hairy code base, but you can really accelerate your experimentation cycles.
On the Clockwise front, what are we actually doing with AI? There are multiple levels. One is we have a product in the field right now that allows AI-based scheduling. You can chat with Clockwise and say, “Hey, I want to schedule a time with Nikita, Aaron, and Joe next week.” We have our own fine-tuned model that we fine-tune to pay attention to time and time-based requests. It can parse the user’s intent and give it to our back-end systems to conduct the scheduling. We’re also about to launch our own MCP server that connects up our scheduling engine to frontier models or whatever MCP client you might be using. It’s been fascinating to see, especially with MCP, the combinatorial power of having different tools that can be called into from a pretty intelligent base model.
Nataraj: You mentioned becoming babysitters for half-baked tools in a LinkedIn post. What trend are you seeing? Why are a lot of these tools looking half-baked?
Matt Martin: I’m so energized by what’s happening in the industry right now because I love experimentation. When you have an explosion of new technology, it’s exciting. But with that explosion comes chaos. People are trying out new things and trying to connect them. When you look at LLMs, the ability to call into other tools is an obvious need. Anthropic developed MCP, and it’s an interesting and elegant first attempt, but it’s cumbersome. It is not for my mom. The more tools you add, the slower the LLM gets, the more complicated it gets. It’s clearly not a pattern that will extend into infinity, but it is a jumpstart on experimentation. So I think we’re in this early phase where getting a workflow completed in an AI-based way is often more cumbersome than just using a pre-existing piece of software. Some skeptics look at that and say this is all BS, just a more complicated way to do things we already know how to do. But the ability of the base model to intelligently reason and navigate these workflows is transformational. We just haven’t gotten there with the interface, with how we put those workflows together, or with the accessibility and usability for the average user.
Nataraj: My take has always been that it’s an evolution. First, we saw the base models, and then a bunch of engineers built V0 versions of everything. Now you really need product thinkers who understand the market and use cases to build the next generation of products. We are still early in terms of the apps leveraging AI. There’s an opportunity to rethink fundamental apps. Can you rewrite Outlook with AI being first? Notion rethought how a note-taking tool should be for the internet. Can you rethink even Notion with AI in place instead of added on top? There’s a lot more experimentation to come.
Matt Martin: I agree with that. We’re definitely in the phase where there’s a lot of bolt-on. There’s a lot of looking at current products and asking, now that I have this additional technology, what can I do on top of this product to augment it? The note-taking example is interesting. Notion has added on its own AI product. It’s one of the more interesting ones I’ve seen, but the frequency with which I use Notion’s AI features versus Notion as just a note-taking tool is maybe 100 to 1. In the future, note-taking probably looks more like something that is an omniscient collection of information that you can query and talk to about surfacing the right information at the right time. Most technology is additive. When we got smartphones, we didn’t get rid of laptops. There’s going to be an evolution where a completely new category and feel of software emerges from AI. Right now, outside of the frontier models like ChatGPT and Claude, I haven’t seen that many things that genuinely feel very new instead of augmentative.
Nataraj: I think we’re almost at the end of our time. What are the best ways for our audience to discover you and the work you are doing?
Matt Martin: The first place to go is clockwise.ai or getclockwise.com. You can start with Clockwise today; it takes about 30 seconds to get up and running. It’s amazing. You’ll get time back in your day, and it’s free to start. If you want to get into contact with me personally, I’m always happy to connect. LinkedIn is actually where I post the most. You can find me, Matt Martin, at Clockwise. On basically any social media, I’m /voxmatt, V-O-X-M-A-T-T. You can find me on Mastodon, which I tend to post to a little bit. I’m a little bit on Threads, a little bit on Blue Sky, a little bit on X. The fracturing social ecosystem has not done well for me in terms of one channel, but LinkedIn’s probably the most consistent.
Nataraj: This was a very fun conversation. Excited to see what Clockwise does next. Thanks for coming on the show.
Matt Martin: Thank you very much. This was a lot of fun.
Matt Martin’s insights reveal a clear vision for a future where AI doesn’t just assist but actively manages our schedules to enhance productivity and well-being. This conversation is a must-listen for anyone looking to reclaim their time and understand the practical applications of AI in the modern workplace.
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