Matt Martin, Co-Founder & CEO of Clockwise – Interview Series

Matt Martin, Co-Founder & CEO of Clockwise is a former lawyer turned engineer and entrepreneur who has built one of the most advanced AI-powered scheduling platforms in the world. Since founding Clockwise in 2016, he has led the company on a mission to reimagine how knowledge workers manage their time, helping more than 40,000 companies—including Atlassian, Asana, and Uber. With a career that has spanned law, product leadership, and software engineering, Matt combines a unique mix of analytical rigor and technical expertise to tackle one of the workplace’s most overlooked challenges: making time for what truly matters.

You’ve had a unique path from lawyer to software engineer to founder — what ultimately led you to start Clockwise in 2016, and how did that background shape the company’s mission?

Well, there’s a non-obvious through-line: I’ve always been a huge nerd! From building websites on the early web to building teams, when I see an interesting problem, I get sucked in. Moving from law to tech in the Bay Area allowed me a unique perspective on a universal problem: how broken calendar management had become. The back-to-back meetings, double bookings, and complete lack of time to actually do meaningful work.

I do value my legal education, but I can’t claim that it’s directly applicable to my day-to-day any longer. It was really my startup years, working at companies that couldn’t scale effectively partly because everyone was trapped in meeting hell, that crystallized the opportunity.

What shaped Clockwise’s mission — to help people make time for what matters most in their days — was realizing, contrary to popular belief, that productivity is not an individual problem, but a fundamental business efficiency issue. The best companies in the world have brilliant people, but if those people can’t find time to think and create because they’re constantly context-switching between meetings, that’s a massive drag on innovation and growth.

We built Clockwise to give companies back what matters most: focused time for their people to do their best work.

What gap did you see in workplace productivity and scheduling that convinced you it was worth dedicating nearly a decade to solving?

I was running a front-end engineering team, and I got sick of spending countless hours recruiting, onboarding, and integrating new engineers just to have them come to me a few months later complaining about how little time they have in the week to code. Like, what is this!? They want to be doing great work, we’re paying them (a lot) to do great work, and yet no one in the company was taking any responsibility for the horrific impact bad schedules were having on these folks. It just felt insane.

We treat time management like an individual burden, but that’s such a cop out. This “sink or swim” approach to time management represents systematic organizational failure disguised as personal accountability. In reality, employees don’t actually control much of their time! That’s because time is a networked system. When one person schedules a meeting, its impact ripples across every attendee’s calendar, plus everyone they are meeting with, too. A single schedule change can affect productivity across entire teams.

The primary input to a knowledge economy is the time and attention of individual employees. A company that can increase the amount of impactful employee time is going to have an incredible advantage on the market. And any piece of software that can enable that productivity will be insanely valuable. That’s the problem worth dedicating nearly a decade to solve.

Clockwise is now used by over 40,000 organizations, including names like Atlassian, Uber, and Netflix. What do you think has resonated most with enterprise customers?

As teams grow, decision-making, progress, and productivity slow. Not to mention scheduling becomes even more complex.

Companies like Uber and Atlassian immediately understand that less time spent on coordinating schedules means more time for impactful work -– that’s why they rely on us to handle the complexities of optimizing calendars org-wide.

Say I want to schedule an hour-long sync with my team. On the surface, seems pretty simple, right? But there are quite a few constraints to consider when it comes to finding a time that will work for everyone:

• 8 people across 3 time zones
• 2 people have “no meetings before 10am” preferences
• 1 person is traveling next week
• 3 participants require prep time

Clockwise internalizes all the requirements and moves conflicting events to make space for the new meeting. What resonates with customers is that they don’t have to deal with the requisite calendar Tetris. They know important meetings will happen, non-pressing items will get rescheduled, and conflicts will be resolved — all automatically.

To date, we’ve created over 7 million hours of time for deep work and rescheduled over 18 million meetings. For enterprises, that’s a measurable ROI on productivity.

This week you’re announcing a new generation of your scheduling brain and MCP server. Which aspects of this launch do you feel will make the biggest immediate impact for users?

As the AI ecosystem explodes, it seems like every company under the sun has released an assistant, but then fails at the most basic assistant task: scheduling meetings. We’re fixing that.

Clockwise MCP gives AI agents access to the world’s most advanced scheduling brain (which we’ve spent 9 years building), enabling them to reason about time with human-level nuance. For the first time, AI will be able to make scheduling decisions and implement calendar changes based on deep contextual understanding, not just what time is available.

The immediate impact is that you can now tell Claude, ChatGPT, or Cursor: “Schedule a 90-minute product review with my distributed team this week, respecting everyone’s focus blocks and time zones” and it actually works like you’d expect a human assistant to handle it.

Beyond straightforward scheduling, leveraging the unique capabilities of LLMs alongside Clockwise MCP also unlocks entire new workflows. For example, you could ask Claude to show you what your team’s productivity looks like over the last month, optimize your schedule following Cal Newport’s Deep Work methodology, or review your kid’s school newsletter and block all important dates on your calendar.

It’s the difference between AI that can read your calendar and AI that can think like a seasoned EA. That distinction transforms these tools from impressive demos into genuinely useful workplace assistants.

Many AI assistants can generate text or code but stumble on scheduling. Why is time such a difficult problem for AI to handle?

Manipulating time is something that humans handle intuitively with nuance. But ask an AI assistant to schedule a team meeting next week, and it’ll suggest a time when half the team is asleep or in deep focus blocks.

That’s because most calendar integrations treat scheduling like database queries. They can find empty slots and fill them, but they can’t make the smart decisions that actual scheduling requires.

The problem is context. Effective scheduling demands understanding human work patterns beyond simple availability. AI needs to know that Alex likes to grab coffee after dropping his kids at school, making that window perfect for a casual phone chat but not a Zoom presentation. Or that Johanna needs 10 minutes between meetings to handle action items, and her frequent travel requires async meeting formats.

Controversial take: but I don’t think that throwing more data and compute at this problem is going to result in a good solution anytime soon.

How does the new scheduling brain differ from earlier versions of Clockwise, and what kind of improvements can users expect?

We’re always working on improving our scheduling brain, and this next generation of intelligence is notable in its ability to be contextually aware and accessible on-demand.

The biggest shift is moving from reactive to proactive scheduling. Previously, Clockwise would optimize your calendar on a fixed daily schedule; now you can generate optimizations on demand, whenever you need them.

We’ve also enabled the brain to think more holistically around your complete workload. The new Tasks integration allows Clockwise to coordinate time for your to-dos alongside meetings, while respecting deadlines and focus block preferences. It’s not just managing meetings anymore; it’s managing all the important work you need to get done in between those meetings.

And we’ve dramatically improved the underlying algorithm’s ability to process multiple scheduling changes simultaneously. Let’s say you want to reschedule all your 1:1s for the week. This single request prompts Clockwise to take action across multiple calendar events. These algorithm improvements are resulting in higher success rates for creating Focus Time and improving outcomes for users.

The update introduces features like on-demand optimizations, task integrations, and analytics. How do these enhancements change the way individuals and teams can work with their calendars?

On-demand optimizations are a game changer for individuals who want to take immediate action, rather than waiting for the system to decide when to help. Task integration is huge because it finally bridges the gap between meeting schedules and making time for actual work to get done.

For teams, the analytics capabilities are transformative. Managers can now spot patterns they’ve never seen before – like identifying when someone’s constantly in back-to-back meetings or when the team’s collective Focus Time is being eroded by meeting creep. Now leaders can make data-driven decisions about workload distribution and meeting hygiene instead of just hoping everyone’s managing their time well.

The combination of these enhancements means teams can move from reactive calendar management to proactive time strategy.

What role does data — like the 17 million monthly calendar events Clockwise analyzes — play in enabling human-level scheduling intelligence?

There are two layers to this answer.

First, in a very direct way, the massive amount of data we process and analyze enables us to deliver a better, more nuanced scheduling brain. Clockwise analyzes over 160 million calendar data points every day, testing millions of calendar arrangements and orchestrating optimizations to keep teams productive. The system aggregates that information to better understand how and when individuals, teams, and entire organizations actually do their best work. This is then reincorporated into the product in everything from algorithmic improvements to better UI/UX.

Second, given the scale of calendar data — both hard data that flows from APIs, but just as importantly, soft data in the form of individual preferences — inside modern organizations makes it literally impossible for any single human to navigate.

While the best human assistants are great at decisioning based on contextual knowledge, they really can only optimize for one, two, maybe three individuals at once. It’s simply too complex to navigate the combinatorial constraints of all attendees. An AI calendar assistant, on the other hand, can effectively schedule at enterprise scale, by combining systems with domain knowledge and the processing of tons of data efficiently.

Traditional scheduling asks: “When is everyone free?” But the better question is: “When is the best time for this work to get done, and how do we make that happen?” You can really only handle that question for everyone if you operate across the network of everyone’s schedules simultaneously.

How do you see companies leveraging Clockwise MCP with agents from Anthropic, OpenAI, and others? Are we moving toward every enterprise running its own AI-powered executive assistant?

It’s anyone’s guess right now, but my bet is that there will be two assistant layers in the enterprise: one layer will provide each employee with an orchestrating agent — this might be similar to a super-powered EA or Chief of Staff — that will call into multiple different agents that are domain experts in specific areas. I think it’s likely that a few different providers will emerge for the orchestrating agent. Unlike the consumer space where ChatGPT is emerging as dominant, enterprise tends to fracture based on the specific needs of different organizations.

The domain specific agent space will be much more diverse and interesting. Just like you don’t necessarily want Microsoft to provide every piece of software for your organization (although, Microsoft would certainly like to!), it’s clear that we’ll all want the help of specific agents provided by specific software vendors to handle specialized tasks

Scheduling and time management is definitely one of those specialized cases. To get it right, AI needs the skills to deliver what people actually need to make their workdays more productive. Imagine a calendar agent that knows your entire team’s deliverables, personal energy patterns, and organizational priorities, and then automatically orchestrates everyone’s schedule to optimize outcomes. No back-and-forth emails, no scheduling conflicts, no context switching. Assistants will evolve from “Hey, you have a meeting in 10 minutes” to “I’ve prepared your talking points, cleared conflicting priorities, and ensured all stakeholders have the pre-read materials.”

The companies that commit to integrating temporal reasoning into their AI workflows won’t just save us from bad meetings; they’ll unlock a new frontier of productivity powered by human-AI collaboration.

What safeguards or ethical considerations come into play when building an AI that reasons about how people use their time?

First, from a privacy standpoint, we never allow models access to customer data for training. Never. And we go to great lengths to ensure this is the case. Customer trust is absolutely paramount not only to our commercial success, but it’s also central to our company values.

Second, we optimize for human wellbeing (like focus blocks, meeting breaks, and lunch) over traditional productivity metrics. We explicitly avoid features that enable micromanagement or workplace surveillance: no dashboards about team scheduling habits, no “productivity scores” for performance reviews. While user preferences inform Clockwise’s optimizations, people maintain control of their calendars while getting intelligent recommendations they can accept or ignore. We’re reducing scheduling friction while maintaining human agency over people’s most precious resource: their time.

Looking ahead, how do you see the relationship between AI assistants and human productivity evolving over the next five years, and where does Clockwise fit into that future?

At a very high-level, I fundamentally see AI as another tool. The abilities it enables will augment and empower millions, but will also inevitably shift where humans are most valuable. I hope that we, as a society, can be more thoughtful about the human impact of major shifts in our economy than we have been in the past. But I have to say that the current political environment does not inspire optimism on that front.

At a more tactical level, I think we’ll see a few shifts.

First, as agent workflows become more reliable and commonplace — a trend that is currently starting, but has a long way to go — we’ll see an evolution from reactive to proactive workflows. For example, as Clockwise’s scheduling brain has advanced in its reliability, we’ve been able to conduct more proactive and aggressive interventions on behalf of a user. To do this, the technology has to be robust, confident, and nuanced enough to work without human input. As AI agents more broadly become less fiddly, more deterministic, and more resilient, I think they’ll make the same shift.

Second, we’ll see the settling of platforms. Right now, there’s an open race for who can be the orchestrating agent in the enterprise. As I mentioned earlier, I think there’s room for more than one dominant player in the enterprise, but as we’ve seen in prior technological shifts, it’s difficult for end-users to access new technology until platform wars have settled a bit. As a third-party software provider, you need to know what platforms are worth investing in, and as a software buyer, you need to have confidence that the choice you make will be a good investment. So, until that settles, we’ll all be expending a bit of our entrepreneurial resources making bets and experimenting. By the way, that also likely means one cycle of bubble-popping and rebuilding.

Third, we’ll see the evolution of the current standards in a direction that makes true platforms possible. Right now MCP is a good-enough solution for third-party tool calling, but it has a lot of wrinkles to iron out. On top of that, I think we will need to see a standard for injecting third-party interfaces into agentic workflows and chat interfaces. Humans are visual creatures and software providers are experts in the best way for users to efficiently interact with their software (well, they are often experts…).

Imagine an AI that doesn’t just analyze calendar conflicts but automatically visualizes team availability and scheduling options in your project management tool, or one that transforms budget discussions in Slack into real-time financial dashboards where stakeholders can explore scenarios together. These types of sophisticated, interconnected systems will understand context deeply enough to know when to stay invisible and when to surface insights through the most effective medium—whether that’s a notification, a visual interface, or direct action. In this future, AI becomes infrastructure rather than a destination.

The ultimate vision: AI that amplifies human creativity by removing friction between intention and execution. When scheduling intelligence becomes invisible infrastructure, people focus entirely on work that only humans can do. Success won’t be measured by how impressive the AI feels, but by how effortless complex coordination becomes—the technology disappearing into the background while human potential moves to the spotlight.

Thank you for the great interview, readers who wish to learn more should visit Clockwise.