Follow enough parents on social media, and you’ll eventually come across a version of this statement: “Check on your friends with kids. They are not OK!”

The fact that it’s often followed by a crying-laughing emoji just highlights the quiet desperation behind it. Parents are stressed the expletive out—so much so that this year the United States Surgeon General released an advisory about parental stress like it has for tobacco, drunk driving, and video game violence.

“It’s time to recognize [the stress and mental health challenges faced by parents] constitute a serious public health concern for our country.” Surgeon General Dr. Vivek Murthy wrote in a New York Times op-ed. “Parents who feel pushed to the brink deserve more than platitudes. They need tangible support.”

Ashley Chang couldn’t agree more. Last year, she launched her company Sundays to connect overwhelmed parents and care providers with human executive assistants. The team of 20 helps with work and family matters, from organizing your inbox to setting up play dates to calling your elderly parents’ insurance company. 

“Our goal is to take off some of that mental and time burden people have and give them a little bit more time back to focus at work and more quality time with their families,” Chang says. 

Sundays does the impossible for more than 120 clients: Organize the chaos and minutiae of work and caregiving, greatly reducing the stress that comes with both. (As a client told Chang via text, “I was moved to tears [from] relief.”)

“One of the hardest things about supporting families is that every family has so much context you have to understand,” Chang explains. “They’re like, ‘I’m so overwhelmed… [but] I don’t know how to get everything out of my brain and into your brain.’”

Dropbox and Dropbox Sign help Sundays make that transfer of knowledge possible. After an in-depth onboarding call, every client gets a Dropbox folder that holds the ins and outs of their lives. School forms and medical records are signed and shared easily; pitch decks, pictures, screenshots, videos, contracts, and documents are organized, secured, and easily searchable.

“Security is one of the most important things for what we do because people are trusting us with their family’s information,” Chang says. “We know what their schedule is, what allergies they have… Taking good care of that information and being good stewards of their trust is really, really important to us.”

By diving into working parents’ lives, Chang has become a thought leader in the space, calling attention to the many structural issues that take women out of the workforce. According to the National Institute of Health, “on average, 24% … exit the labor market in their first year of motherhood.”  

“It can’t be only moms fighting for moms,” she says. 

Chang walks us through how Sundays started from her early conversations with parents, what it’s like to build a business from the ground up, and how tools like Dropbox help her team lighten the mental load for busy families.

We found that a lot of our client’s mental load was because they were only handing things off at the execution phase. We wanted to be at the conceiving level, but with this kind of to-do list version, we weren't there. So now we focus a lot more on building relationships. We always intend to be human-first with a little bit of technology to be more efficient in the background.

How does Sundays use tech to help your families be more efficient?
People told me, “You have this space in the back of your brain where you think about hard work problems. But once I have a kid, all of that brain space is now taken up by things about my kid.”  I think it's really easy for people to not give themselves any space for emotional processing right now. Over time, that all builds up, and you become less effective and less happy. I think having someone take on things for you so that you can be in a better place to manage it is really helpful.

Each executive assistant works really closely with a few families. There's so much information that we need to share between our team and them, we needed a system to store all that data. Dropbox felt like a natural place. We treat that as the home base for all the information that we're sharing between the two of us. 

As we were building up trust with families, they started asking us to do more things, and some of those things were like filling out government forms on their behalf. I have learned while working with families that there are so many forms you have to sign for kids and it's exhausting. So we use Dropbox Sign for that instead of them printing everything out at their house.

If you could describe a future that was heavily affected by Sundays being in the world, what would that look like?
More moms in leadership roles—like if you look at an exec team, there are 50% women and more than 50% of the people are parents. That would be my dream world. 

This interview was edited and condensed for clarity.

Back in early 2021, a PhD candidate in electrical engineering at UT Dallas named Roshni Anna Jacob was developing a proposal with her advisor to study the resilience of Texas’ power grid. Her special approach involved using AI to look at the incredibly complex questions around how energy gets delivered to millions of homes and businesses. Then, in February of that year, a polar vortex hit, sending the temperature to record lows, overwhelming the grid, and throwing most of Texas—including Dr. Jacob—into darkness.

Dr. Jacob, who completed her PhD this summer, has a warm presence and can amiably explain graph neural networks to a reporter without a computer science degree. She chuckled at the irony of spending a few days without electricity or water while studying grid resiliency. But many in Texas had a worse time of it. Some 11 million people lost power for as long as three days. Temperatures went down to 0 degrees Fahrenheit, and officials put the estimated death toll at 246—two thirds from hypothermia—though some experts put the total as high as 700.

Unusually frigid temperatures took a number of power plants offline precisely when consumers were turning their space heaters on full blast. Some were so cold they used hair dryers to keep warm. The Texas grid operator—which, unlike in every other state, functions independently of the Federal Energy Regulatory Commission (FERC)—began massive load shedding, creating intentional blackouts to prevent the grid from failing.

Most people don’t think too hard about where their power comes from. Decades of consistent, reliable electricity have created the illusion that when you plug something in it’s basically guaranteed to turn on. This is not the case globally. In 2022, Pakistan averaged 22 power outages a month. Operating the grid is, on the one hand, incredibly complex—involving hundreds of power plants, half a million miles of high-voltage transmission lines, transformers that bring the voltage down so that it can be distributed to 336 million people, with the added twist of increasingly popular solar panels and batteries creating and storing power locally. On the other hand, the grid is also pretty analog, at least technologically speaking. It is, at some level, about switching power on and off such that the supply matches demand.

People refer to the US power grid as the largest machine in the world, which is awe-inspiring. But much of it is comparatively ancient, built decades ago. And, as innumerable sources report, it’s in desperate need of upgrades. Yet with so many of our decarbonization goals linked to switching from fossil fuels to electricity—from oil burning furnaces to heat pumps, and from gas-powered cars to EVs—the grid is experiencing a surge in demand, or load growth, unlike anything we’ve seen in recent history. 

One factor is the proliferation of data centers used for AI, with Goldman Sachs predicting that AI could drive a 160% increase in data center power demand. But this is one of the core contradictions of the energy transition. While AI is part of the problem, more and more people are asking an interesting question: Can it also be part of the solution?

~ ~ ~

Like other deeply-entrenched, highly-regulated industries, the utilities that deliver our power are resistant to change. Theirs is a high-stakes job with little room for error. With tragedies like the Texas blackout always back of mind, they prefer the reliability of good old gas plants—which, unlike wind and solar, aren’t subject to changes in the weather. That means they’re cautious any time an ambitious group of people attempt to build a new wind farm, like the one led by Matt Perkins outside Anchorage, Alaska. Before Perkins’ power can come online, the regional grid operator must study the impact of the new project on the rest of the grid. This process prioritizes safety, and it functioned better back when new projects came along at a trickle. Now there are hundreds waiting in line.

Each planning study includes other proposed projects in the interconnection queue in order to evaluate what their collective impact would be. If one project drops out, they have to redo the study. This leads us to the second big contradiction at the heart of the energy transition: The wattage of renewable energy waiting to be plugged into the grid is twice our current capacity. 

It is the bottleneck of all bottlenecks—a bureaucratic morass so behind schedule that it now takes an average of four years for a project to get approval, and can take as long as seven. That’s double the time it took ten years ago. Fewer than one in five proposals actually make it through. Former FERC Commissioner Allison Clements called it an “irrational barrier to entry” on the Volts podcast.

Alp Kucukelbir, the chief scientist at Fero Labs and an adjunct professor at Columbia University, thinks AI can expedite the process. “The business of working within the grid is largely documents and text, communication between people and bodies and entities and regulators,” Kucukelbir said on a Zoom call. “All that is up for significant acceleration with AI.”

Kucukelbir—pronounced “cue-chew-kell-beer”—co-authored a 334-page report compiling use cases for AI in mitigating climate change. Among its recommendations, it suggests using language models and AI-based simulations to expedite the planning for new projects. “Can we make permitting faster?” Kucukelbir asked with a hint of exasperation. “Can we go through regulatory steps faster? How do we accelerate the entire process?”

Interconnection planning involves both complex engineering challenges and regular old workflow challenges. The process for reviewing interconnection applications is manual and labor-intensive. AI tools could streamline this by automating data integration, generating preliminary study models, and identifying grid constraints more efficiently. Some people are already working on this. Pearl Street Technologies developed a software tool to accelerate modeling and simulation studies. “This type of analysis is very complex and can take weeks-to-months of engineering time to get to a solved state,” explained David Bromberg, Pearl Street’s CEO, during a recent interview. “Our software was developed to automate these types of time-consuming processes.”

As if to validate the importance of this work, the Department of Energy just announced $30 million in funding for projects using AI to speed up the interconnection queue. With the help of AI, grid operators might be able to race through the worst of the planning process speed bumps. That would mean less busywork, and more time to focus on the real, pressing engineering questions, potentially cutting the wait time down by a matter of years.

In case this is starting to feel like a fusty municipal planning meeting, let’s add some table stakes: For the US to meet its climate goals, the country aims to generate 44% of its power from renewable resources by 2050. That means doubling the amount of clean energy currently hooked up to the grid. Author David Wallace-Wells only underscores the urgency in his book The Uninhabitable Earth; it puts the number of climate refugees somewhere between 200 million to 1 billion if we don’t limit warming to 2 degrees Celsius in the next 25 years.

~ ~ ~

One company—Utilidata—found a way to earn the trust of the utilities, who often get a bad rap in climate circles. But it didn’t happen for them right away. At first, they tried to offer a software solution to help operators optimize the grid. “But then we were asking utilities to become really great at deploying software, and they're not good at that,” Utilidata CEO Josh Brumberger said over Zoom. “But you know what utilities are really good at? Deploying hardware.”

So Utilidata partnered with NVIDIA to develop a chip that could be installed directly on the meter. With AI hardware deployed on site, Utilidata was able to create a platform that gave utilities insight into what is actually happening on the grid—something they’d never had before. Once power is behind the meter—that is, charging iPhones and nuking frozen burritos—the utility is riding blind, at least traditionally. But as the grid becomes more decentralized and distributed, knowing what’s going on becomes increasingly essential. That’s especially true when it comes to big power draws like EV charging.

“How smart is the grid?” Brumberger said. “The answer is, it's not. Period. So what do we do about it? How do you bring the grid to life? Imagine taking a system that's pretty blind today to one 5-10 years from now that can see everything and control everything.”

It’s a vision of a future grid in which AI chips are distributed throughout our energy infrastructure, constantly evaluating how to maximize efficiency. 

~ ~ ~

Reducing emissions in our power system is essential—but so is grid resiliency. What the National Oceanic and Atmospheric Administration (NOAA) calls “billion-dollar disaster events” are increasingly common as global temperatures rise. And the Texas outage made all these wonky policy questions real for people on the ground.

Not long after her power came back on and the water started running from the taps again, Dr. Roshni Anna Jacob began working on a new project with a team of researchers at UT Dallas. To prepare for the next outage, they had a vision of connecting an advanced machine learning model to their clunky, sprawling grid, and teaching the grid to do something new: learn how to heal itself.

“We represent the power grid as a graph,” Dr. Yulia Gel, one of the co-authors and now a professor at Virginia Tech, explained on a Zoom call. “And we use graph theory tools to better understand what the optimal action will be.”

The model can “detect outages or faulty events and then automatically take action to reduce the impact,” Dr. Jacob said. “There will still be outages but it can reduce that with emergency load shedding. Once the outage has been somewhat mitigated, it can take other actions to restore power. […] This requires good decision making on what switches to open and what switches to close, and has to be done very quickly—almost at the speed of light.”

The grid already has some of these capabilities. The issue is that existing algorithms aren’t able to solve problems in real time—especially as the proliferation of distributed energy resources (DERs), such as residential rooftop solar panels and batteries, increase the complexity of the system. During outages, this new model creates microgrids powered by DERs. “From a resilience perspective, the smaller the unit, the easier it is to control. You contain the outages. It’s a more local solution,” Dr. Jacob said.

It takes time, however, for experimental new models like this to migrate from academia to the daily work of operating a power grid—which raises the issue of trust. Kucukelbir, the chief scientist at Fero Labs, is passionate about this subject. AI, he emphasized, is something assistive—a tool that you work with. Take the impact of AI on NOAA’s advanced weather modeling: “We're not throwing our national labs away anytime soon,” Kucukelbir says. “NOAA's here to stay. But if you can accelerate that with AI, that becomes a parallel tool.”

It can be an uphill battle getting large, traditional industrial and institutional players to integrate new technologies such as AI into their workflows—which makes the trust factor all the more essential.

“As we encourage the adoption of AI in industry, we need to recognize that there's someone there whose job is to make sure that there isn't a blackout, that this pot of steel doesn't explode molten metal, that this chemical doesn't leak into Mexico,” Kucukelbir said. “All of these things are someone's job, and they will only trust technology that they understand.”

Last year, we launched Dropbox Ventures, a $50 million initiative to invest in startups that are building the next generation of AI-powered apps and tools. Since then, we’ve invested in several companies, including Augie, LlamaIndex, Bardeen and LightBeam, that are reshaping modern work. We’ve also expanded our partnerships with our portfolio companies by introducing integrations to benefit both sets of customers. 

Today, we’re excited to highlight three new investments in Highnote, JustPaid, and Lakera.

New investments in Highnote, JustPaid, and Lakera

Our first investment is in Highnote, an audio collaboration tool that provides a dedicated space for creators and musicians to collaborate and give feedback in the post-creation audio process. The tool helps streamline and simplify the entire audio workflow process from the initial demo creation to final distribution. Millions of creatives and artists trust Dropbox to do their best work, which is why we also introduced an integration with Highnote that allows users to sync their files directly from Dropbox, creating a seamless audio layer on top of their existing storage file system. Dropbox and Highnote creatives alike can stay in sync across their accounts while making progress on their music.

We’re also investing in JustPaid, a financial platform that gives businesses the ability to manage their entire sales and invoicing workflow from contract signing to payment collection. JustPaid’s AI-powered technology makes it easy for businesses to handle invoicing, financial reporting, and more. We recently introduced an integration with Dropbox Sign and JustPaid, allowing users to streamline their document signing process and automate invoicing—all within a few clicks.

Finally, we’re excited to partner with Lakera, a GenAI security platform that helps companies block prompt attacks, data loss, and inappropriate content with its low-latency AI application firewall. In addition to our investment, Dropbox uses Lakera Guard as our security solution to help safeguard our LLM-powered applications, secure and protect user data, and—as outlined in our AI principles—uphold the reliability and trustworthiness of our intelligent features.

Deepening our strategic partnerships beyond investments 

Dropbox Ventures is more than just a funding program—it’s a strategic partnership. We work closely with our portfolio companies, providing mentorship and potential exposure to over 700 million registered Dropbox users who can benefit from their product. 

We also recently expanded our partnership with Augie through an integration with Dropbox Replay. Replay is now a part of Augie’s video creation studio, setting a new standard for video production workflows. This integration helps creators streamline their workflows, improve collaboration, and execute projects in less time.

Over a year in, we’re excited about the progress we’ve made in building our Dropbox Ventures portfolio. We look forward to supporting innovative AI initiatives that shape the future of work in 2025 and beyond.

To learn more about Dropbox Ventures or if you’d like to get in touch, visit dropbox.com/ventures.

We’re excited to announce that Ashraf Alkarmi is joining Dropbox as our new Senior Vice President and General Manager of Dropbox Core. In this role, Ashraf will lead the teams working on our file, sync, and share (FSS) business, in addition to Sign and DocSend. 

We’re entering a new chapter for Dropbox as both our FSS business and the overall category mature. To meet the evolving needs of modern work, we’re focused on both improving our existing product experiences, while investing in our next phase of growth. For our FSS business, this means strengthening the product and continuing to improve the reliability and security of our platform, leaning into the qualities that make us a trusted, easy-to-use solution for millions of customers. This renewed focus is all in service of delivering an even better experience, so customers can do their best work.

That’s where Ashraf comes in — he’s spent his career rethinking how to maintain a dedicated customer base, find new paths for growth, and manage large teams through times of transition. His background spans a unique combination of business-to-consumer, product-led, and sales-led enterprise models. Most importantly, he has a customer-first mindset. Ashraf brings extensive experience in building and adapting products within companies at scale, positioning him to play an instrumental role as we strengthen our core product.

Ashraf joins us from Vimeo, where he was Chief Product Officer. Before that, he was at Meta and Amazon, where he was General Manager of Amazon’s Freevee product, leading a team of several hundred people to grow the business to scale.

We’re thrilled to welcome Ashraf to the team!

Today, our cofounder and CEO Drew Houston shared the difficult news that we’ll be making reductions to our global workforce. He sent the following email to all employees:
 

Hi everyone,

I’m writing to let you all know that after careful consideration, we've decided to reduce our global workforce by approximately 20% or 528 Dropboxers.

As CEO, I take full responsibility for this decision and the circumstances that led to it, and I’m truly sorry to those impacted by this change.

Why we're making this decision

As we've shared over the last year, we're in a transitional period as a company. Our FSS business has matured, and we've been working to build our next phase of growth with products like Dash. However, navigating this transition while maintaining our current structure and investment levels is no longer sustainable.

We continue to see softening demand and macro headwinds in our core business. But external factors are only part of the story. We’ve heard from many of you that our organizational structure has become overly complex, with excess layers of management slowing us down.

And while I'm proud of the progress we’ve made in the last couple years, in some parts of the business, we’re still not delivering at the level our customers deserve or performing in line with industry peers. So we're making more significant cuts in areas where we're over-invested or underperforming while designing a flatter, more efficient team structure overall.

The opportunity ahead

The changes we're making today, while difficult, come at a pivotal moment when the market is accelerating precisely where we've placed our biggest bets. It's been tremendously rewarding over the last few weeks to see customers and prospects light up when using Dash for Business for the first time, much like people did when we first launched Dropbox. 

And this time we're starting from a position of strength. Millions of customers trust us as the home for their most important files, making the leap to organizing all their cloud content a natural evolution.

But we're not operating on our own schedule. This market is moving fast and investors are pouring hundreds of millions of dollars into this space. This both validates the opportunity we've been pursuing and underscores the need for even more urgency, even more aggressive investment, and decisive action.

The steps we’re taking today are necessary to both strengthen our core product and accelerate the growth of our new products. We’ll share more about our 2025 strategy in the days ahead.

Taking care of impacted employees

To those leaving Dropbox, we're committed to supporting you through this transition. You’ll be eligible to receive the following benefits and support:

Severance, equity, and transition payment 

• All impacted employees will be eligible for sixteen weeks of pay, starting today, with one additional week of pay for each completed year of tenure at Dropbox. Internationally, severance packages will vary depending on regional practices and statutory requirements.
• All impacted employees will receive their Q4 equity vest.
• Those on the Corporate Bonus plan will be eligible to receive a pro-rated lump sum transition payment equivalent to their 2024 bonus target based on company performance forecasts and aligned with their level.
• We will pay out eligible remaining current and approved upcoming paid leaves, including medical or family leaves.
• We will support impacted visa holders by providing additional time to transition and access to 1:1 immigration consultation.

Healthcare and benefits

• US employees will be eligible for up to six months of COBRA.
• Canada-based employees will be eligible for a one-month healthcare extension.
• All employees will continue to have access to Modern Health to support their mental well-being.

Devices

• Impacted employees will be eligible to keep company devices (phones, tablets, laptops, and peripherals) for personal use.

Job placement

• Job placement services and career coaching will be available at no cost.

Next steps

We'll be sharing more details on high-level changes later today and will host company-wide Town Halls later this week to answer questions and discuss our plans in more detail.

I know this is incredibly difficult and unwelcome news. To everyone leaving Dropbox, I’m deeply grateful for everything you've done for our company and our customers.

Drew

Ahead of the launch of Dash for Business, our new AI-powered universal search product for teams, we partnered with the McLaren Formula 1 Team to put Dash’s capabilities—including its advanced content access control—to the test in a high-stakes environment that demands efficiency as every second counts.

In conversation about one of the world’s fastest-growing spectator sports, Dropbox CEO Drew Houston and CEO of McLaren Racing Zak Brown chat about pushing the boundary of where people and technology intersect.

Teams interested in Dash for Business can visit https://dash.dropbox.com/ to learn more.

Have you ever racked your brain trying to track down an important piece of information for work—like, “Where is that thing?” Was it an email? A doc in the cloud? A Dropbox folder? A message on Slack? Your stuff probably lives across dozens of disconnected apps and browser tabs testing the limits of your laptop’s battery life—and your patience. This is the reality of modern work, but it doesn’t have to be this way.

Today, we’re introducing Dash for Business, our new AI-powered universal search tool, which makes it easy for teams to search, organize, share, and protect content from across their connected apps, all in one place. Dash for Business combines universal search and organization with in-depth content access control for businesses big and small, giving IT admins visibility and control over the content people share and access.

Productivity apps have revolutionized the way we work, and the AI boom has created even more platforms and products designed to streamline our processes. But these tools are often siloed from one another, contributing to the big, messy problem of information fragmentation. And having to track stuff down isn’t just a minor inconvenience—it’s a persistent and costly toll on your time and your attention.

Dash, which we launched last year, has already helped users save time they would’ve spent searching for documents like needles in a haystack. Dash for Business goes further by improving the search experience and helping businesses reduce security risks, both with in-depth content access controls and by ensuring sensitive company information isn’t surfaced unintentionally. It’s a product experience we’ve spent years developing and improving—our early partners like McLaren Racing already consider it a “game-changer”—and we’re excited to finally share it with you.

Search all of your stuff in one place

Dash for Business is AI-powered universal search that finds the answers your team needs, no matter where they’re stored in the cloud. And just like Dropbox, we designed Dash for Business to be intuitive and easy to use. Give Dash for Business a keyword, a question, a description, or a command, and it will not only understand what you mean, but, more importantly, find what you‘re looking for. With improvements to search within and beyond Dropbox, Dash uses machine intelligence to improve search results and provide real-time answers.

When you need an answer fast, you can ask Dash a question or have it summarize content, in some cases without ever having to open a file, tab, or doc. And the best part is that Dash for Business is platform agnostic, so it works not only with Dropbox but also with apps like Google Drive, OneDrive, Notion, Asana, and more. Add email, calendars, files, and more to search them all in one place. The more apps you connect, the more useful and time-saving Dash for Business becomes. 

Dash for Business also updates many of the features Dash users already love while introducing some new ones. Stacks—smart collections that allow you to group, organize, and share content with all of your colleagues—can now be used at the company level and have in-depth sharing permissions for both internal and external viewers. Your stacks help you corral everything from the same project together, and your start page can surface when someone on your team has made edits to these files.

The start page is a dashboard that gives you access to universal search, stacks, shortcuts to recent work, and meetings, making it easier to navigate your day. You can also use it to access the activity feed, which consolidates your work streams. Lastly, answers is our new AI-powered feature that allows you to ask questions about your content, helps you uncover deeper insights by generating follow-up questions, and surfaces related content links based on your original search query.

Dash for Business can help you find one specific document just as easily as it can help you stay on top of the work that’s happening around you. It takes the thinking—and the wasted hours of distraction—out of finding what you need so that you can focus on the important stuff.

Advanced content access control

We developed Dash for Business with both employees and business admins in mind. We understand that manually moderating access permissions can be tedious and time-consuming, often requiring significant manpower to stay on top of potential security risks. And the more products and apps we introduce to our workplaces, the more daunting this problem becomes. 

Dash for Business makes sure only the right people and right teams have access to certain company data while ensuring others don’t. Admins can view who has access at the individual document level or update permissions in bulk in just seconds.

We’re powering these features and protecting cloud files from unauthorized access using Nira, our recently acquired content governance platform. With Nira, we built a custom solution directly into Dash, allowing IT admins to easily protect confidential documents with just a few clicks. Nira’s capabilities let you decrease and close security gaps—and even shut them down altogether. Control which apps and services are connected to Dash, be alerted when files are shared with folks outside of your organization, and more.

We know privacy is top of mind for our customers. More than a trillion pieces of content are stored on Dropbox, and we are committed to being worthy of trust as we enter this next phase of our growth as a company. Dropbox Dash will use self-hosted AI by default, ensuring that customer data remains within Dropbox's trust boundary without reliance on third-party AI platforms.

Building for the future at Dropbox

Dash for Business is the natural progression of our product journey. Dropbox was founded because we needed a better way of storing and accessing our content. With Dash for Business, we’re harnessing AI to create a more streamlined and secure solution to the knowledge fragmentation problem. And we’ve heard great things from companies like McLaren Formula 1 Team, which has already seen meaningful results.

McLaren is a huge operation of strategists, marketers, designers, and more who work tirelessly behind the scenes to make every race a success—and they can’t be successful without pushing the boundary of where people and technology intersect. Dropbox collaborated closely with the McLaren team to begin testing Dash for Business earlier this summer, ensuring we were designing it in a way that really served the needs of teams and IT admins. 

“Dash has been a game-changer for us because it doesn’t lock us into a single ecosystem. Instead, it seamlessly connects the various apps and tools our team relies on, centralizing all that information in one place. For a team always seeking improvements, the ability to bring everything together has been valuable,” said Dan Keyworth, Director of Business Technology, McLaren Racing.

“Dash provides critical visibility into where outdated permissions may have access to sensitive data,” Keyworth added. “This insight is essential for safeguarding intellectual property, including data, creative campaigns, and commercial assets, allowing us to enhance our security and maintain tighter control over our most valuable information.”

Dash for Business* is available in the US in English only on web and desktop, with availability in additional markets in early 2025. Teams interested can visit https://dash.dropbox.com/ to learn more.

*Customers using previous versions of Dropbox Dash in Beta can visit https://dash.dropbox.com/ to learn more about trying Dash for Business.

In our First Draft series, creatives look back on their first projects and share what they’ve learned from the experience.

In New York City, there are unspoken—if you’re lucky—rules of the sidewalk: Walk with the flow of pedestrians, not against it; move to the side to stop instead of standing still abruptly; and steamroll past anyone who isn’t following those rules—even if they're breaking them for a good cause. 

Jia Rizvi often found herself on the business end of that third rule in 2015. Back then, she and a friend were planning a fundraiser for Adnan Syed’s Legal Defense Fund. (Syed’s wrongful conviction in his ex-girlfriend’s 1999 murder was the focus of Serial, a 2014 podcast that riveted Rizvi and millions.)

“We were canvassing the streets and handing out flyers, telling people to come and help us raise money for Adnan,” she recalls now from her home office. “Most people ignored us or took the flyer and threw it away.”

In 2016, Rizvi took the Amtrak from New York to Baltimore to attend a hearing that could grant Syed a new trial. Cameras were everywhere—a crew of four even followed Rizvi and the Syed family to dinner. It wasn’t until she had to sign a release that she understood what they were for: The Case Against Adnan Syed, an HBO docuseries that would be released in 2019. That small crew was a revelation to Rizvi.

“I was thinking, That’s all it takes?!” she says now. “I have a camera. I know a few people. I can do this, too! This is how we can get people to care! So, so dumb and so naive.”

On the train ride back to New York, she became an aspiring documentarian. When her son was born in 2017, Rizvi enrolled in a documentary workshop program at the New York Film Academy the following year. (She also enrolled her son in a nearby daycare for easy drop offs and pick ups.)

At NYFA, Rizvi learned what she couldn’t tell from watching the documentary crew in 2016: Just because you have a camera, doesn’t mean you have a film. And just because you have a film, doesn’t mean anyone is going to see it.

“Only 1% of films ever make it into a film festival. One percent. Thank God I didn’t know anything,” she says, “because… had I known what I know today, I would have never switched careers.”

But Rizvi’s drive coupled with her teachers’ instruction kept her from being deterred. For her final project, she did a 20-minute short about Jeff Deskovic, a man she met while planning the fundraiser for Syed. Like Syed, Deskovic had been wrongfully convicted as a teen in the murder of a high-school classmate. He was released after serving 16 years.

Dropbox became a bridge between Rizvi and her team’s on-set and on-laptop days, keeping files, clips, and contracts organized and shareable from shoot to shoot. Sign was clutch when it came to getting crew and interview subjects to sign contracts and release forms. And when a special-effects editor in Pakistan introduced her to Dropbox Replay, it superpowered the team’s post-production work, she says.

“Sometimes a minute-and-a-half-long video would have a novel of notes. [Now] there’s no guess work,” Rizvi explains. “We could pause it, make a note right there, and it would timestamp it for us. It sped up the process so, so much and there’s much less miscommunication.”

This came in handy when her film editor moved to Los Angeles mid-project to work on a Netflix project.

“Conviction is a lot stronger because of the way we were able to quickly address and share these things remotely,” Rizvi says now. “There were definitely many, many times [he] would watch a cut of the film and come back and say, ‘This footage is not good enough.’ It’s a 20-second fix for me to go through other footage, drop it in, and be like, ‘Okay, open up the folder. There’s three other options in there,’ and he can quickly replace it in his editing software.”

The film was completed in 2019, and became a part of the 1% when it was named an official selection at not one, not two, but 17 film festivals. Crushed when the 2020 COVID lockdown delayed its theatrical run, Rizvi found out she could pitch Conviction for streaming distribution. It made its debut on Amazon Prime that year. (You can still add it to your queue!)

Since then, Rizvi has wrapped production on her first feature film, Sixteen Years. The documentary dives deeper into Deskovic’s story and puts pieces together that the short couldn’t. Rizvi just signed on to turn Sixteen Years into a book, and the film is currently being reviewed by three of the big streaming platforms, “so fingers crossed one of them is interested and takes it,” she says.

It’s a lot to juggle—and definitely takes more people than a casual observer would see on any given shoot day. That’s why Rizvi prioritizes efficiency when it comes to getting her work done.

“There’s no way that I would have been able to direct the film and do the press outreach if things weren’t simplified,” she says, “if I wasn’t able to utilize tools like Dropbox to save so much time.”

Rizvi tells us what she’s learned from expanding her short into a feature-length documentary.

On capturing more than you need for your feature

If you’re making a short and think, Oh, I don’t need to shoot this, you probably do if you’re ever going to expand it. So just film everything: all the B-roll, all the events. I couldn’t be at Jeff’s graduation from law school, but we had someone go there and shoot it because we were going to need it at some point—it’s just too big of an event.

When we got to making the feature, we realized very quickly that we were very short on B-roll. Ninety minutes is a lot of video to fill, and you don’t realize how much B roll you truly need. So any time you’re mapping out your storyboards, know that you’re going to need endless B-roll, think about what B-roll would go with every person’s interview, and shoot that as you go.

We had to get through a good portion of our edit, stop, go back, and film more B-roll, and then bring it back in and start editing again. It’s great if you don’t have to do that so it doesn’t slow down your editing process.

On keeping it all organized

It’s huge. If you don’t do that, the editing process is going to be an absolute nightmare.

Within Dropbox, we label every shoot by the date and location. Within that, you have your B-roll, your A-roll. Audio, same thing. Then you make folders for your backup audio, your main audio. If you have multiple mics, there’s a different folder for every single mic. Then we send those off to the editors, PAs, audio engineers, and anyone else who needs them.

Naming those files is so critical. With the short it was easy, because it was only a few interviews, so we were like, “Oh, we’ll be able to find everything.” When we made the feature, we did 20 more interviews with eight other people. We made the mistake of not properly labeling the audio files. When we had to go find, let’s say, Jeff’s or Jeff’s mom’s interviews, it was all labeled by mic with nothing else, so we couldn’t search for anything quickly. We also were editing with Premiere Pro, and it wouldn’t sync up because all the audio files were named the same: It couldn’t recognize where to go to get those files.

So the organization with your file folders—and then the names of those files—is critical to the speed of your editing, and, if anything goes wrong, your ability to troubleshoot it.

On getting to the next project

I’m a type-A Virgo, total perfectionist: If I waited for Conviction to be perfect, it would have never seen the light of day.

I read a quote—I’m sure everyone’s heard it: “Perfectionism is the enemy of progress”—and it just struck a chord with me. I’m still a perfectionist for sure; to some degree, you have to be to put out quality work, right? Where I have to stop and have an internal dialog with myself is when it’s like, Is the experience for the viewer going to be really any different if I leave it as is? Or is that just me checking my box for like, "Oh no, it’s not perfect yet"?

What I tell myself now is, if I keep working on this scene, I won’t be able to tell the next person’s story. So you just have to cut it off and say, “No, this is finished. We’re moving on to the next scene. And if we watch the whole thing at the end, and something doesn’t seem right, we can always come back to it for a quick minute.”

This interview has been edited and condensed for clarity.

Want to share your story? Email aakitunde@dropbox.com with First Draft in the subject.
 

In the year 79, when Mt. Vesuvius erupted and buried Pompeii in a pyroclastic surge, killing thousands with more thermal energy than 100,000 atomic bombs, it also dumped twenty meters of hot mud and ash on a nearby town called Herculaneum, which was something like the Malibu of ancient Rome. In this town was a luxurious villa with a massive library of papyrus scrolls. When the volcano went off, each one of these got turned into a Kingsford charcoal briquette, carbonized by the searing heat. Pyroclastic material is an excellent preservation method, making Herculaneum, like Pompeii, a near pristine museum of ancient objects—except that when Italian papyrologists tried to crack open the scrolls, they crumbled. Using traditional archaeological methods, this was a dead end. 

That is, until an ambitious computer scientist from the University of Kentucky named Brent Seales proposed something radical: Pop one of these scrolls in a CT scan—a particle accelerator the size of Madison Square Garden—and unwrap it virtually with AI.

Archaeology is not a resource-rich field. And particle accelerators are expensive. So Seales created the Vesuvius Challenge: a competition between research teams to read the scans and win over $1M in prize money raised from big donors. Each step turns out to be incredibly complicated. After scanning there’s “segmentation,” which involves tracing the crumpled layers of the rolled papyrus in the 3D scan and then unrolling them. Then there’s “ink detection,” identifying which areas of the charred papyri, which look black to the naked eye, held ink and which did not using machine learning. A Discord community with over 4,000 members sprung up around this project. More than 1,000 teams jumped in. To make sure that teams weren’t hoarding intermediate discoveries from each other, they blended competition and cooperation by giving out “progress prizes” along the way.

Last year, three young students pulled it off, won the money, and revealed to the world a small portion of text—5% of just one of around 1,800 scrolls—that had been locked away for two millennia. The papyrology team determined that it was not a duplicate of an existing work, meaning that the scroll contained never-before-seen text from antiquity.

What did it say? As the Vesuvius Challenge website cheekily put it, they found a “2000-year-old blog post about how to enjoy life.” The big theme was pleasure, which, properly understood, was the highest good in Epicurean philosophy. 

The arrival of widely accessible AI tools in the last ten years marks a turning point in the field of archaeology—arguably the most esoteric academic discipline. It’s old and literally dusty, and, traditionally, it requires vast input of attention hours for relatively modest outcomes. The questions are big: How did we get here? Why did cities start showing up 10,000 years ago? And they come with equally big implications for contemporary problems. But the pace of discovery and progress is torturously slow. That is until recently—thanks to developments like machine learning tools for analyzing satellite data and drone imagery, language models that sift through undeciphered scripts, and algorithms for reading crispy papyrus. These are the first steps in automating the most time-intensive aspects of archaeology with technology, giving way for archaeologists to do what humans do best: look at the bigger picture. 

What we‘re getting wrong about our past

As Dr. Sarah Parcak wrote in her punchy archaeology newsletter, Future of Our Past, “Archaeology teaches us that we have been here before, many times, facing nearly identical problems.” The little fragments of pottery and papyrus that experts like her dig up out of the ground “show our resilience, our creativity, and our adaptability in the face of enormous challenges. People and their cultures can survive, and do, often in the most unlikely of ways.”

Recent findings suggest that our contemporary understanding of how we got here might be wrong. In the Dawn of Everything (2021), David Graeber and David Wengrow argue that many commonplace narratives about our deep past—the relative utopia of hunter-gatherer societies, on the one hand, and the Hobbesian vision of all against all on the other—have been debunked, or complicated, by the last decade of archaeological research. It simply wasn’t the case that all life prior to the advent of agriculture was confined to small bands wandering through the woods. And the arrival of farming didn’t necessarily “create” private property, as tempting as that theory might be. 

“On the contrary,” Graeber and Wengrow write, “the world of hunter-gatherers as it existed before the coming of agriculture was one of bold social experiments, resembling a carnival parade of political forms, far more than it does the drab abstractions of evolutionary theory… And far from setting class differences in stone, a surprising number of the world's earliest cities were organized on robustly egalitarian lines, with no need for authoritarian rulers, ambitious warrior-politicians, or even bossy administrators.”

Graeber and Wengrow make the case that if our understanding of the past, and therefore of human nature, is slightly off, maybe we aren’t as locked in to the way things are now as it sometimes feels we are.

Big shifts in narrative like this require lots of evidence. Fifteen years ago the mood in archaeology was very different. The emphasis was niche. Young PhD candidates would focus intently on a small area and become experts at a very high level of detail. Then something changed. New and highly powered, if somewhat clumsy, AI tools began to automate the most labor-intensive busywork. 

The dawn of a new kind of collaboration

Call it the dawn of the golden age of computational archaeology. Dr. Hector A. Orengo was one of the pioneers. He’s a professor at the Catalan Institute of Classical Archaeology where he applies machine learning to his research using cloud computing and big data. As an archaeologist, “your expertise is not to be able to identify little fragments of pottery,” he explained. “That can be done by a child. The expertise is to analyze: What is the significance?”

Two of Orengo’s most cited papers show a glimpse of what AI might be able to unlock here. In one, he took satellite data and trained an algorithm to identify archaeological mounds in the Cholistan Desert of Pakistan which might indicate Indus settlements from ca. 3300 to 1500 BC. Pre-AI, that would require having graduate students painstakingly pore over data, piling up man hours which means piling expenses. Also, it’s boring. The results spit out by the algorithm still require human verification. (Grad students can do that!) Then Orengo’s job is to interpret: What does the pattern of ancient settlements say about how they adapted to changes in their environment over time?

In the other paper, he trained another algorithm to scan high-resolution drone imagery and detect shards of pottery. This goes beyond saving a few grad student man-hours. The traditional method for pottery shard detection involves walking large tracts of land on foot, eyes trained on the ground, recording as you go. Using photogrammetry—taking measurements from photos—with geospatial analysis run off the Google Earth Engine, Orengo was able to dramatically reduce the time it takes to analyze a given landscape, proving that AI tools can take care of vast amounts of legwork, and enable the experts to do what they do best.

The dawn of computational archaeology is also the dawn of a new kind of collaboration. A team of researchers from the University of Bologna developed a human + AI workflow for discovering new archaeological sites. The model predicts sites with 80% accuracy on its own and becomes even more precise with a human expert. Keeping the human in the loop is essential, they argue. This also points to one of the stickiest problems with using AI to solve complex problems in the material world. The level of sophistication required both from a computer science perspective and from an archaeological perspective means that progress so far hasn’t been as rapid as in other areas of AI application. Plus, as Orengo drily mentioned, “You don't get into archaeology because you want to make money.”

The machine learning technology is both extremely powerful and relatively simple—not unlike the hot dog/not hot dog app from HBO’s Silicon Valley. (Orengo calls it “shooting flies with cannons.”) Yet while flashier generative AI tools have been getting their makers in hot water for misunderstanding basic things about human history, these image recognition algorithms may have a more immediate chance of helping us understand ourselves and where we came from. 

Automating the legwork

They can also help us figure out what to do next. Dr. Iris Kramer has leveraged her expertise in computational archaeology to break out of academia and start a company—Arch AI—where she’s essentially building a Google Maps for everything beneath the surface. It got her on the Forbes 30 Under 30 list for Europe and Tedx Talk. It also caught the attention of the United Kingdom’s Forestry Commission. 

England wants to increase its woodlands from 14.5% to 16.5% by 2050. (For context, the European average is 44%. By comparison, England is bald.) Two percent is more than half a million acres. Rewilding land, regenerating biodiversity, re-meandering rivers to prevent flooding, reintroducing salt marshes to sequester carbon—these are all really hard to pull off. Especially in the UK where people are extra particular about what’s going on in their backyard. The trick to reintroducing woodland is to place it in an area that was woodland not too long ago. 

This required Kramer to pivot and begin using machine learning to scan old maps from the turn of the century. “Instead of just doing archeological site detections, we're now modeling the entire historic environment in the landscape,” Kramer said. “We know exactly where woodlands used to be and those locations are more likely to sustainably grow back because the seed banks and the mushrooms are still in the ground.” (Fungi are essential to healthy forests.)

Commercial applications for archaeology aren’t many—although Orengo has helped large hydroelectric companies place power lines. Kramer sees an opportunity for Arch AI to assist in the housing development process in the UK—which often gets bogged down in the approval process. It’s essential, with any new buildings, to avoid historically significant sites.

“Development needs to be sustainable,” Kramer said. But, “I'm also keen for development to speed up because people don't have enough houses in the UK. There's a massive housing crisis. So it's important that places are being built faster through understanding risk at an earlier stage.” There’s something very interesting happening here: Kramer is applying a niche technology in a niche research field and finding out that it might be useful in solving some of the biggest issues we’re facing in the present—another reason this is an exciting moment for archaeology. 

But even just within academia, the old methods are getting a turbo boost from these technologies. Automating that time-intensive legwork opens up the field to new possibilities and allows the experts to return to unsolved mysteries with increased processing power. “We have lost the big picture,” Orengo said. “We have lost the beautiful narratives… the big questions, like, how do civilizations start? What is the origin of urbanism? In order to address these questions it is absolutely necessary to take a new approach.”

From that perspective, AI might be giving archaeologists a simpler gift: the time to do the actual work of archaeology—interpreting evidence, reexamining dusty old narratives, and seeking out new ones.